1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
1001
1002
1003
1004
1005
1006
1007
1008
1009
1010
1011
1012
1013
1014
1015
1016
1017
1018
1019
1020
1021
1022
1023
1024
1025
1026
1027
1028
1029
1030
1031
1032
1033
1034
1035
1036
1037
1038
1039
1040
1041
1042
1043
1044
1045
1046
1047
1048
1049
1050
1051
1052
1053
1054
1055
1056
1057
1058
1059
1060
1061
1062
1063
1064
1065
1066
1067
1068
1069
1070
1071
1072
1073
1074
1075
1076
1077
1078
1079
1080
1081
1082
1083
1084
1085
1086
1087
1088
1089
1090
1091
1092
1093
1094
1095
1096
1097
1098
1099
1100
1101
1102
1103
1104
1105
1106
1107
1108
1109
1110
1111
1112
1113
1114
1115
1116
1117
1118
1119
1120
1121
1122
1123
1124
1125
1126
1127
1128
1129
1130
1131
1132
1133
1134
1135
1136
1137
1138
1139
1140
1141
1142
1143
1144
1145
1146
1147
1148
1149
1150
1151
1152
1153
1154
1155
1156
1157
1158
1159
1160
1161
1162
1163
1164
1165
1166
1167
1168
1169
1170
1171
1172
1173
1174
1175
1176
1177
1178
1179
1180
1181
1182
1183
1184
1185
1186
1187
1188
1189
1190
1191
1192
1193
1194
1195
1196
1197
1198
1199
1200
1201
1202
1203
1204
1205
1206
1207
1208
1209
1210
1211
1212
1213
1214
1215
1216
1217
1218
1219
1220
1221
1222
1223
1224
1225
1226
1227
1228
1229
1230
1231
1232
1233
1234
1235
1236
1237
1238
1239
1240
1241
1242
1243
1244
1245
1246
1247
1248
1249
1250
1251
1252
1253
1254
1255
1256
1257
1258
1259
1260
1261
1262
1263
1264
1265
1266
1267
1268
1269
1270
1271
1272
1273
1274
1275
1276
1277
1278
1279
1280
1281
1282
1283
1284
1285
1286
1287
1288
1289
1290
1291
1292
1293
1294
1295
1296
1297
1298
1299
1300
1301
1302
1303
1304
1305
1306
1307
1308
1309
1310
1311
1312
1313
1314
1315
1316
1317
1318
1319
1320
1321
1322
1323
|
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
<html xmlns="http://www.w3.org/1999/xhtml">
<head>
<meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/>
<meta http-equiv="X-UA-Compatible" content="IE=9"/>
<meta name="generator" content="Doxygen 1.8.6"/>
<title>ViennaCL - The Vienna Computing Library: viennacl/linalg/opencl/vector_operations.hpp Source File</title>
<link href="tabs.css" rel="stylesheet" type="text/css"/>
<script type="text/javascript" src="jquery.js"></script>
<script type="text/javascript" src="dynsections.js"></script>
<link href="navtree.css" rel="stylesheet" type="text/css"/>
<script type="text/javascript" src="resize.js"></script>
<script type="text/javascript" src="navtree.js"></script>
<script type="text/javascript">
$(document).ready(initResizable);
$(window).load(resizeHeight);
</script>
<link href="search/search.css" rel="stylesheet" type="text/css"/>
<script type="text/javascript" src="search/search.js"></script>
<script type="text/javascript">
$(document).ready(function() { searchBox.OnSelectItem(0); });
</script>
<link href="doxygen.css" rel="stylesheet" type="text/css" />
</head>
<body>
<div id="top"><!-- do not remove this div, it is closed by doxygen! -->
<div id="titlearea">
<table cellspacing="0" cellpadding="0">
<tbody>
<tr style="height: 56px;">
<td style="padding-left: 0.5em;">
<div id="projectname">ViennaCL - The Vienna Computing Library
 <span id="projectnumber">1.7.1</span>
</div>
<div id="projectbrief">Free open-source GPU-accelerated linear algebra and solver library.</div>
</td>
<td> <div id="MSearchBox" class="MSearchBoxInactive">
<span class="left">
<img id="MSearchSelect" src="search/mag_sel.png"
onmouseover="return searchBox.OnSearchSelectShow()"
onmouseout="return searchBox.OnSearchSelectHide()"
alt=""/>
<input type="text" id="MSearchField" value="Search" accesskey="S"
onfocus="searchBox.OnSearchFieldFocus(true)"
onblur="searchBox.OnSearchFieldFocus(false)"
onkeyup="searchBox.OnSearchFieldChange(event)"/>
</span><span class="right">
<a id="MSearchClose" href="javascript:searchBox.CloseResultsWindow()"><img id="MSearchCloseImg" border="0" src="search/close.png" alt=""/></a>
</span>
</div>
</td>
</tr>
</tbody>
</table>
</div>
<!-- end header part -->
<!-- Generated by Doxygen 1.8.6 -->
<script type="text/javascript">
var searchBox = new SearchBox("searchBox", "search",false,'Search');
</script>
</div><!-- top -->
<div id="side-nav" class="ui-resizable side-nav-resizable">
<div id="nav-tree">
<div id="nav-tree-contents">
<div id="nav-sync" class="sync"></div>
</div>
</div>
<div id="splitbar" style="-moz-user-select:none;"
class="ui-resizable-handle">
</div>
</div>
<script type="text/javascript">
$(document).ready(function(){initNavTree('opencl_2vector__operations_8hpp_source.html','');});
</script>
<div id="doc-content">
<!-- window showing the filter options -->
<div id="MSearchSelectWindow"
onmouseover="return searchBox.OnSearchSelectShow()"
onmouseout="return searchBox.OnSearchSelectHide()"
onkeydown="return searchBox.OnSearchSelectKey(event)">
<a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(0)"><span class="SelectionMark"> </span>All</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(1)"><span class="SelectionMark"> </span>Classes</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(2)"><span class="SelectionMark"> </span>Namespaces</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(3)"><span class="SelectionMark"> </span>Files</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(4)"><span class="SelectionMark"> </span>Functions</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(5)"><span class="SelectionMark"> </span>Variables</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(6)"><span class="SelectionMark"> </span>Typedefs</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(7)"><span class="SelectionMark"> </span>Enumerations</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(8)"><span class="SelectionMark"> </span>Enumerator</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(9)"><span class="SelectionMark"> </span>Friends</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(10)"><span class="SelectionMark"> </span>Macros</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(11)"><span class="SelectionMark"> </span>Pages</a></div>
<!-- iframe showing the search results (closed by default) -->
<div id="MSearchResultsWindow">
<iframe src="javascript:void(0)" frameborder="0"
name="MSearchResults" id="MSearchResults">
</iframe>
</div>
<div class="header">
<div class="headertitle">
<div class="title">vector_operations.hpp</div> </div>
</div><!--header-->
<div class="contents">
<a href="opencl_2vector__operations_8hpp.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="preprocessor">#ifndef VIENNACL_LINALG_OPENCL_VECTOR_OPERATIONS_HPP_</span></div>
<div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="preprocessor">#define VIENNACL_LINALG_OPENCL_VECTOR_OPERATIONS_HPP_</span></div>
<div class="line"><a name="l00003"></a><span class="lineno"> 3</span> </div>
<div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">/* =========================================================================</span></div>
<div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="comment"> Copyright (c) 2010-2016, Institute for Microelectronics,</span></div>
<div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="comment"> Institute for Analysis and Scientific Computing,</span></div>
<div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="comment"> TU Wien.</span></div>
<div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="comment"> Portions of this software are copyright by UChicago Argonne, LLC.</span></div>
<div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="comment"></span></div>
<div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="comment"> -----------------</span></div>
<div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="comment"> ViennaCL - The Vienna Computing Library</span></div>
<div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="comment"> -----------------</span></div>
<div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="comment"></span></div>
<div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="comment"> Project Head: Karl Rupp rupp@iue.tuwien.ac.at</span></div>
<div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="comment"></span></div>
<div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="comment"> (A list of authors and contributors can be found in the manual)</span></div>
<div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="comment"></span></div>
<div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="comment"> License: MIT (X11), see file LICENSE in the base directory</span></div>
<div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="comment">============================================================================= */</span></div>
<div class="line"><a name="l00020"></a><span class="lineno"> 20</span> </div>
<div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="preprocessor">#include <cmath></span></div>
<div class="line"><a name="l00026"></a><span class="lineno"> 26</span> </div>
<div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="preprocessor">#include "<a class="code" href="forwards_8h.html">viennacl/forwards.h</a>"</span></div>
<div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="preprocessor">#include "<a class="code" href="vector__def_8hpp.html">viennacl/detail/vector_def.hpp</a>"</span></div>
<div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="preprocessor">#include "<a class="code" href="device_8hpp.html">viennacl/ocl/device.hpp</a>"</span></div>
<div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="preprocessor">#include "<a class="code" href="ocl_2handle_8hpp.html">viennacl/ocl/handle.hpp</a>"</span></div>
<div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="preprocessor">#include "<a class="code" href="kernel_8hpp.html">viennacl/ocl/kernel.hpp</a>"</span></div>
<div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="preprocessor">#include "<a class="code" href="scalar_8hpp.html">viennacl/scalar.hpp</a>"</span></div>
<div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="preprocessor">#include "<a class="code" href="tools_8hpp.html">viennacl/tools/tools.hpp</a>"</span></div>
<div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="preprocessor">#include "<a class="code" href="linalg_2opencl_2common_8hpp.html">viennacl/linalg/opencl/common.hpp</a>"</span></div>
<div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="preprocessor">#include "<a class="code" href="linalg_2opencl_2kernels_2vector_8hpp.html">viennacl/linalg/opencl/kernels/vector.hpp</a>"</span></div>
<div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="preprocessor">#include "<a class="code" href="vector__element_8hpp.html">viennacl/linalg/opencl/kernels/vector_element.hpp</a>"</span></div>
<div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="preprocessor">#include "<a class="code" href="scan_8hpp.html">viennacl/linalg/opencl/kernels/scan.hpp</a>"</span></div>
<div class="line"><a name="l00038"></a><span class="lineno"> 38</span> <span class="preprocessor">#include "<a class="code" href="predicate_8hpp.html">viennacl/meta/predicate.hpp</a>"</span></div>
<div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="preprocessor">#include "<a class="code" href="enable__if_8hpp.html">viennacl/meta/enable_if.hpp</a>"</span></div>
<div class="line"><a name="l00040"></a><span class="lineno"> 40</span> <span class="preprocessor">#include "<a class="code" href="size_8hpp.html">viennacl/traits/size.hpp</a>"</span></div>
<div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="preprocessor">#include "<a class="code" href="start_8hpp.html">viennacl/traits/start.hpp</a>"</span></div>
<div class="line"><a name="l00042"></a><span class="lineno"> 42</span> <span class="preprocessor">#include "<a class="code" href="traits_2handle_8hpp.html">viennacl/traits/handle.hpp</a>"</span></div>
<div class="line"><a name="l00043"></a><span class="lineno"> 43</span> <span class="preprocessor">#include "<a class="code" href="stride_8hpp.html">viennacl/traits/stride.hpp</a>"</span></div>
<div class="line"><a name="l00044"></a><span class="lineno"> 44</span> </div>
<div class="line"><a name="l00045"></a><span class="lineno"> 45</span> <span class="keyword">namespace </span>viennacl</div>
<div class="line"><a name="l00046"></a><span class="lineno"> 46</span> {</div>
<div class="line"><a name="l00047"></a><span class="lineno"> 47</span> <span class="keyword">namespace </span>linalg</div>
<div class="line"><a name="l00048"></a><span class="lineno"> 48</span> {</div>
<div class="line"><a name="l00049"></a><span class="lineno"> 49</span> <span class="keyword">namespace </span>opencl</div>
<div class="line"><a name="l00050"></a><span class="lineno"> 50</span> {</div>
<div class="line"><a name="l00051"></a><span class="lineno"> 51</span> </div>
<div class="line"><a name="l00052"></a><span class="lineno"> 52</span> <span class="comment">//</span></div>
<div class="line"><a name="l00053"></a><span class="lineno"> 53</span> <span class="comment">// Introductory note: By convention, all dimensions are already checked in the dispatcher frontend. No need to double-check again in here!</span></div>
<div class="line"><a name="l00054"></a><span class="lineno"> 54</span> <span class="comment">//</span></div>
<div class="line"><a name="l00055"></a><span class="lineno"> 55</span> <span class="keyword">template</span><<span class="keyword">typename</span> DestNumericT, <span class="keyword">typename</span> SrcNumericT></div>
<div class="line"><a name="l00056"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1opencl.html#a541e559b22fd19a7a453af6beca00b2b"> 56</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#a4e7dbe07ee5433438da8435cdb1a08ee">convert</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<DestNumericT></a> & dest, <a class="code" href="classviennacl_1_1vector__base.html">vector_base<SrcNumericT></a> <span class="keyword">const</span> & src)</div>
<div class="line"><a name="l00057"></a><span class="lineno"> 57</span> {</div>
<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  assert(viennacl::traits::opencl_handle(dest).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() == viennacl::traits::opencl_handle(src).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() && <span class="keywordtype">bool</span>(<span class="stringliteral">"Vectors do not reside in the same OpenCL context. Automatic migration not yet supported!"</span>));</div>
<div class="line"><a name="l00059"></a><span class="lineno"> 59</span> </div>
<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  std::string kernel_name(<span class="stringliteral">"convert_"</span>);</div>
<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  kernel_name += <a class="code" href="structviennacl_1_1ocl_1_1type__to__string.html">viennacl::ocl::type_to_string<DestNumericT>::apply</a>();</div>
<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  kernel_name += <span class="stringliteral">"_"</span>;</div>
<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  kernel_name += <a class="code" href="structviennacl_1_1ocl_1_1type__to__string.html">viennacl::ocl::type_to_string<SrcNumericT>::apply</a>();</div>
<div class="line"><a name="l00064"></a><span class="lineno"> 64</span> </div>
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> & ctx = <span class="keyword">const_cast<</span><a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> &<span class="keyword">></span>(viennacl::traits::opencl_handle(dest).context());</div>
<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector__convert.html#a5b181b269925c10d0a7ed4e258393566">viennacl::linalg::opencl::kernels::vector_convert::init</a>(ctx);</div>
<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a>& k = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector__convert.html#aa9b325a3e08a54c231d0aaa17f9162f4">viennacl::linalg::opencl::kernels::vector_convert::program_name</a>(), kernel_name);</div>
<div class="line"><a name="l00068"></a><span class="lineno"> 68</span> </div>
<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(k( dest, cl_uint(dest.<a class="code" href="classviennacl_1_1vector__base.html#aaabd2cd126b77ee09b80b4c447bcbd3e">start</a>()), cl_uint(dest.<a class="code" href="classviennacl_1_1vector__base.html#af1e0bd20ec7254908f6d49df07785cf4">stride</a>()), cl_uint(dest.<a class="code" href="classviennacl_1_1vector__base.html#a15c47ae4326098aeaa4ed6b91fc6df9b">size</a>()),</div>
<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  src, cl_uint( src.<a class="code" href="classviennacl_1_1vector__base.html#aaabd2cd126b77ee09b80b4c447bcbd3e">start</a>()), cl_uint( src.<a class="code" href="classviennacl_1_1vector__base.html#af1e0bd20ec7254908f6d49df07785cf4">stride</a>())</div>
<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  ) );</div>
<div class="line"><a name="l00072"></a><span class="lineno"> 72</span> </div>
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span> }</div>
<div class="line"><a name="l00074"></a><span class="lineno"> 74</span> </div>
<div class="line"><a name="l00075"></a><span class="lineno"> 75</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T, <span class="keyword">typename</span> ScalarType1></div>
<div class="line"><a name="l00076"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1opencl.html#a0501c423f35eb16759db2c3028ae4857"> 76</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#a0501c423f35eb16759db2c3028ae4857">av</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> & vec1,</div>
<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> <span class="keyword">const</span> & vec2, ScalarType1 <span class="keyword">const</span> & alpha, <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> len_alpha, <span class="keywordtype">bool</span> reciprocal_alpha, <span class="keywordtype">bool</span> flip_sign_alpha)</div>
<div class="line"><a name="l00078"></a><span class="lineno"> 78</span> {</div>
<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  assert(viennacl::traits::opencl_handle(vec1).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() == viennacl::traits::opencl_handle(vec2).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() && <span class="keywordtype">bool</span>(<span class="stringliteral">"Vectors do not reside in the same OpenCL context. Automatic migration not yet supported!"</span>));</div>
<div class="line"><a name="l00080"></a><span class="lineno"> 80</span> </div>
<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> & ctx = <span class="keyword">const_cast<</span><a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> &<span class="keyword">></span>(viennacl::traits::opencl_handle(vec1).context());</div>
<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html#a803233f6aed07b9ef954c30257d7a75f">viennacl::linalg::opencl::kernels::vector<T>::init</a>(ctx);</div>
<div class="line"><a name="l00083"></a><span class="lineno"> 83</span> </div>
<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  cl_uint options_alpha = <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a685282399bcfb05ee912c02fed7f922f">detail::make_options</a>(len_alpha, reciprocal_alpha, flip_sign_alpha);</div>
<div class="line"><a name="l00085"></a><span class="lineno"> 85</span> </div>
<div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a> & k = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html">viennacl::linalg::opencl::kernels::vector<T>::program_name</a>(),</div>
<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  (<a class="code" href="structviennacl_1_1is__cpu__scalar.html">viennacl::is_cpu_scalar<ScalarType1>::value</a> ? <span class="stringliteral">"av_cpu"</span> : <span class="stringliteral">"av_gpu"</span>));</div>
<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#a0144c18ae9f07722e5b5697335b7cff5">global_work_size</a>(0, std::min<vcl_size_t>(128 * k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>(),</div>
<div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  viennacl::tools::align_to_multiple<vcl_size_t>(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec1), k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>()) ) );</div>
<div class="line"><a name="l00090"></a><span class="lineno"> 90</span> </div>
<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html">viennacl::ocl::packed_cl_uint</a> size_vec1;</div>
<div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  size_vec1.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a7991987e7676fabb8d1cbc54eaa0ba01">start</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec1));</div>
<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  size_vec1.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a457e1f554ae439501613c843b6dad189">stride</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec1));</div>
<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  size_vec1.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a5f4dcdfd54664fb7859b27f3dec641c0">size</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec1));</div>
<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  size_vec1.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#ab4fed39d6fdda2db5bcb5ec29c2537d0">internal_size</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a0cd530f8a76a5fb3d60a9230bea30bca">viennacl::traits::internal_size</a>(vec1));</div>
<div class="line"><a name="l00096"></a><span class="lineno"> 96</span> </div>
<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html">viennacl::ocl::packed_cl_uint</a> size_vec2;</div>
<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  size_vec2.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a7991987e7676fabb8d1cbc54eaa0ba01">start</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec2));</div>
<div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  size_vec2.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a457e1f554ae439501613c843b6dad189">stride</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec2));</div>
<div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  size_vec2.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a5f4dcdfd54664fb7859b27f3dec641c0">size</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec2));</div>
<div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  size_vec2.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#ab4fed39d6fdda2db5bcb5ec29c2537d0">internal_size</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a0cd530f8a76a5fb3d60a9230bea30bca">viennacl::traits::internal_size</a>(vec2));</div>
<div class="line"><a name="l00102"></a><span class="lineno"> 102</span> </div>
<div class="line"><a name="l00103"></a><span class="lineno"> 103</span> </div>
<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(k(viennacl::traits::opencl_handle(vec1),</div>
<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  size_vec1,</div>
<div class="line"><a name="l00106"></a><span class="lineno"> 106</span> </div>
<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  viennacl::traits::opencl_handle(viennacl::tools::promote_if_host_scalar<T>(alpha)),</div>
<div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  options_alpha,</div>
<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  viennacl::traits::opencl_handle(vec2),</div>
<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  size_vec2 )</div>
<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  );</div>
<div class="line"><a name="l00112"></a><span class="lineno"> 112</span> }</div>
<div class="line"><a name="l00113"></a><span class="lineno"> 113</span> </div>
<div class="line"><a name="l00114"></a><span class="lineno"> 114</span> </div>
<div class="line"><a name="l00115"></a><span class="lineno"> 115</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T, <span class="keyword">typename</span> ScalarType1, <span class="keyword">typename</span> ScalarType2></div>
<div class="line"><a name="l00116"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1opencl.html#ad22775c47f41c305da21168d1cb92236"> 116</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#ad22775c47f41c305da21168d1cb92236">avbv</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> & vec1,</div>
<div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> <span class="keyword">const</span> & vec2, ScalarType1 <span class="keyword">const</span> & alpha, <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> len_alpha, <span class="keywordtype">bool</span> reciprocal_alpha, <span class="keywordtype">bool</span> flip_sign_alpha,</div>
<div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> <span class="keyword">const</span> & vec3, ScalarType2 <span class="keyword">const</span> & beta, <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> len_beta, <span class="keywordtype">bool</span> reciprocal_beta, <span class="keywordtype">bool</span> flip_sign_beta)</div>
<div class="line"><a name="l00119"></a><span class="lineno"> 119</span> {</div>
<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  assert(viennacl::traits::opencl_handle(vec1).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() == viennacl::traits::opencl_handle(vec2).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() && <span class="keywordtype">bool</span>(<span class="stringliteral">"Vectors do not reside in the same OpenCL context. Automatic migration not yet supported!"</span>));</div>
<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  assert(viennacl::traits::opencl_handle(vec2).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() == viennacl::traits::opencl_handle(vec3).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() && <span class="keywordtype">bool</span>(<span class="stringliteral">"Vectors do not reside in the same OpenCL context. Automatic migration not yet supported!"</span>));</div>
<div class="line"><a name="l00122"></a><span class="lineno"> 122</span> </div>
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> & ctx = <span class="keyword">const_cast<</span><a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> &<span class="keyword">></span>(viennacl::traits::opencl_handle(vec1).context());</div>
<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html#a803233f6aed07b9ef954c30257d7a75f">viennacl::linalg::opencl::kernels::vector<T>::init</a>(ctx);</div>
<div class="line"><a name="l00125"></a><span class="lineno"> 125</span> </div>
<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  std::string kernel_name;</div>
<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  <span class="keywordflow">if</span> (<a class="code" href="structviennacl_1_1is__cpu__scalar.html">viennacl::is_cpu_scalar<ScalarType1>::value</a> && <a class="code" href="structviennacl_1_1is__cpu__scalar.html">viennacl::is_cpu_scalar<ScalarType2>::value</a>)</div>
<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  kernel_name = <span class="stringliteral">"avbv_cpu_cpu"</span>;</div>
<div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (<a class="code" href="structviennacl_1_1is__cpu__scalar.html">viennacl::is_cpu_scalar<ScalarType1>::value</a> && !<a class="code" href="structviennacl_1_1is__cpu__scalar.html">viennacl::is_cpu_scalar<ScalarType2>::value</a>)</div>
<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  kernel_name = <span class="stringliteral">"avbv_cpu_gpu"</span>;</div>
<div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (!<a class="code" href="structviennacl_1_1is__cpu__scalar.html">viennacl::is_cpu_scalar<ScalarType1>::value</a> && <a class="code" href="structviennacl_1_1is__cpu__scalar.html">viennacl::is_cpu_scalar<ScalarType2>::value</a>)</div>
<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  kernel_name = <span class="stringliteral">"avbv_gpu_cpu"</span>;</div>
<div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  kernel_name = <span class="stringliteral">"avbv_gpu_gpu"</span>;</div>
<div class="line"><a name="l00135"></a><span class="lineno"> 135</span> </div>
<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  cl_uint options_alpha = <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a685282399bcfb05ee912c02fed7f922f">detail::make_options</a>(len_alpha, reciprocal_alpha, flip_sign_alpha);</div>
<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  cl_uint options_beta = <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a685282399bcfb05ee912c02fed7f922f">detail::make_options</a>(len_beta, reciprocal_beta, flip_sign_beta);</div>
<div class="line"><a name="l00138"></a><span class="lineno"> 138</span> </div>
<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a> & k = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html">viennacl::linalg::opencl::kernels::vector<T>::program_name</a>(), kernel_name);</div>
<div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#a0144c18ae9f07722e5b5697335b7cff5">global_work_size</a>(0, std::min<vcl_size_t>(128 * k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>(),</div>
<div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  viennacl::tools::align_to_multiple<vcl_size_t>(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec1), k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>()) ) );</div>
<div class="line"><a name="l00142"></a><span class="lineno"> 142</span> </div>
<div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html">viennacl::ocl::packed_cl_uint</a> size_vec1;</div>
<div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  size_vec1.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a7991987e7676fabb8d1cbc54eaa0ba01">start</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec1));</div>
<div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  size_vec1.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a457e1f554ae439501613c843b6dad189">stride</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec1));</div>
<div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  size_vec1.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a5f4dcdfd54664fb7859b27f3dec641c0">size</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec1));</div>
<div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  size_vec1.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#ab4fed39d6fdda2db5bcb5ec29c2537d0">internal_size</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a0cd530f8a76a5fb3d60a9230bea30bca">viennacl::traits::internal_size</a>(vec1));</div>
<div class="line"><a name="l00148"></a><span class="lineno"> 148</span> </div>
<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html">viennacl::ocl::packed_cl_uint</a> size_vec2;</div>
<div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  size_vec2.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a7991987e7676fabb8d1cbc54eaa0ba01">start</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec2));</div>
<div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  size_vec2.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a457e1f554ae439501613c843b6dad189">stride</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec2));</div>
<div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  size_vec2.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a5f4dcdfd54664fb7859b27f3dec641c0">size</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec2));</div>
<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  size_vec2.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#ab4fed39d6fdda2db5bcb5ec29c2537d0">internal_size</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a0cd530f8a76a5fb3d60a9230bea30bca">viennacl::traits::internal_size</a>(vec2));</div>
<div class="line"><a name="l00154"></a><span class="lineno"> 154</span> </div>
<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html">viennacl::ocl::packed_cl_uint</a> size_vec3;</div>
<div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  size_vec3.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a7991987e7676fabb8d1cbc54eaa0ba01">start</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec3));</div>
<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  size_vec3.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a457e1f554ae439501613c843b6dad189">stride</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec3));</div>
<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  size_vec3.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a5f4dcdfd54664fb7859b27f3dec641c0">size</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec3));</div>
<div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  size_vec3.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#ab4fed39d6fdda2db5bcb5ec29c2537d0">internal_size</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a0cd530f8a76a5fb3d60a9230bea30bca">viennacl::traits::internal_size</a>(vec3));</div>
<div class="line"><a name="l00160"></a><span class="lineno"> 160</span> </div>
<div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(k(viennacl::traits::opencl_handle(vec1),</div>
<div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  size_vec1,</div>
<div class="line"><a name="l00163"></a><span class="lineno"> 163</span> </div>
<div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  viennacl::traits::opencl_handle(viennacl::tools::promote_if_host_scalar<T>(alpha)),</div>
<div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  options_alpha,</div>
<div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  viennacl::traits::opencl_handle(vec2),</div>
<div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  size_vec2,</div>
<div class="line"><a name="l00168"></a><span class="lineno"> 168</span> </div>
<div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  viennacl::traits::opencl_handle(viennacl::tools::promote_if_host_scalar<T>(beta)),</div>
<div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  options_beta,</div>
<div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  viennacl::traits::opencl_handle(vec3),</div>
<div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  size_vec3 )</div>
<div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  );</div>
<div class="line"><a name="l00174"></a><span class="lineno"> 174</span> }</div>
<div class="line"><a name="l00175"></a><span class="lineno"> 175</span> </div>
<div class="line"><a name="l00176"></a><span class="lineno"> 176</span> </div>
<div class="line"><a name="l00177"></a><span class="lineno"> 177</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T, <span class="keyword">typename</span> ScalarType1, <span class="keyword">typename</span> ScalarType2></div>
<div class="line"><a name="l00178"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1opencl.html#a3acee3fef422c2c2abee2f4e1d67c350"> 178</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#a3acee3fef422c2c2abee2f4e1d67c350">avbv_v</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> & vec1,</div>
<div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> <span class="keyword">const</span> & vec2, ScalarType1 <span class="keyword">const</span> & alpha, <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> len_alpha, <span class="keywordtype">bool</span> reciprocal_alpha, <span class="keywordtype">bool</span> flip_sign_alpha,</div>
<div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> <span class="keyword">const</span> & vec3, ScalarType2 <span class="keyword">const</span> & beta, <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> len_beta, <span class="keywordtype">bool</span> reciprocal_beta, <span class="keywordtype">bool</span> flip_sign_beta)</div>
<div class="line"><a name="l00181"></a><span class="lineno"> 181</span> {</div>
<div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  assert(viennacl::traits::opencl_handle(vec1).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() == viennacl::traits::opencl_handle(vec2).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() && <span class="keywordtype">bool</span>(<span class="stringliteral">"Vectors do not reside in the same OpenCL context. Automatic migration not yet supported!"</span>));</div>
<div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  assert(viennacl::traits::opencl_handle(vec2).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() == viennacl::traits::opencl_handle(vec3).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() && <span class="keywordtype">bool</span>(<span class="stringliteral">"Vectors do not reside in the same OpenCL context. Automatic migration not yet supported!"</span>));</div>
<div class="line"><a name="l00184"></a><span class="lineno"> 184</span> </div>
<div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  <a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> & ctx = <span class="keyword">const_cast<</span><a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> &<span class="keyword">></span>(viennacl::traits::opencl_handle(vec1).context());</div>
<div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  <a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html#a803233f6aed07b9ef954c30257d7a75f">viennacl::linalg::opencl::kernels::vector<T>::init</a>(ctx);</div>
<div class="line"><a name="l00187"></a><span class="lineno"> 187</span> </div>
<div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  std::string kernel_name;</div>
<div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  <span class="keywordflow">if</span> (<a class="code" href="structviennacl_1_1is__cpu__scalar.html">viennacl::is_cpu_scalar<ScalarType1>::value</a> && <a class="code" href="structviennacl_1_1is__cpu__scalar.html">viennacl::is_cpu_scalar<ScalarType2>::value</a>)</div>
<div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  kernel_name = <span class="stringliteral">"avbv_v_cpu_cpu"</span>;</div>
<div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (<a class="code" href="structviennacl_1_1is__cpu__scalar.html">viennacl::is_cpu_scalar<ScalarType1>::value</a> && !<a class="code" href="structviennacl_1_1is__cpu__scalar.html">viennacl::is_cpu_scalar<ScalarType2>::value</a>)</div>
<div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  kernel_name = <span class="stringliteral">"avbv_v_cpu_gpu"</span>;</div>
<div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (!<a class="code" href="structviennacl_1_1is__cpu__scalar.html">viennacl::is_cpu_scalar<ScalarType1>::value</a> && <a class="code" href="structviennacl_1_1is__cpu__scalar.html">viennacl::is_cpu_scalar<ScalarType2>::value</a>)</div>
<div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  kernel_name = <span class="stringliteral">"avbv_v_gpu_cpu"</span>;</div>
<div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  kernel_name = <span class="stringliteral">"avbv_v_gpu_gpu"</span>;</div>
<div class="line"><a name="l00197"></a><span class="lineno"> 197</span> </div>
<div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  cl_uint options_alpha = <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a685282399bcfb05ee912c02fed7f922f">detail::make_options</a>(len_alpha, reciprocal_alpha, flip_sign_alpha);</div>
<div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  cl_uint options_beta = <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a685282399bcfb05ee912c02fed7f922f">detail::make_options</a>(len_beta, reciprocal_beta, flip_sign_beta);</div>
<div class="line"><a name="l00200"></a><span class="lineno"> 200</span> </div>
<div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a> & k = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html">viennacl::linalg::opencl::kernels::vector<T>::program_name</a>(), kernel_name);</div>
<div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#a0144c18ae9f07722e5b5697335b7cff5">global_work_size</a>(0, std::min<vcl_size_t>(128 * k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>(),</div>
<div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  viennacl::tools::align_to_multiple<vcl_size_t>(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec1), k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>()) ) );</div>
<div class="line"><a name="l00204"></a><span class="lineno"> 204</span> </div>
<div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  <a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html">viennacl::ocl::packed_cl_uint</a> size_vec1;</div>
<div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  size_vec1.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a7991987e7676fabb8d1cbc54eaa0ba01">start</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec1));</div>
<div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  size_vec1.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a457e1f554ae439501613c843b6dad189">stride</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec1));</div>
<div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  size_vec1.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a5f4dcdfd54664fb7859b27f3dec641c0">size</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec1));</div>
<div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  size_vec1.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#ab4fed39d6fdda2db5bcb5ec29c2537d0">internal_size</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a0cd530f8a76a5fb3d60a9230bea30bca">viennacl::traits::internal_size</a>(vec1));</div>
<div class="line"><a name="l00210"></a><span class="lineno"> 210</span> </div>
<div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  <a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html">viennacl::ocl::packed_cl_uint</a> size_vec2;</div>
<div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  size_vec2.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a7991987e7676fabb8d1cbc54eaa0ba01">start</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec2));</div>
<div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  size_vec2.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a457e1f554ae439501613c843b6dad189">stride</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec2));</div>
<div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  size_vec2.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a5f4dcdfd54664fb7859b27f3dec641c0">size</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec2));</div>
<div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  size_vec2.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#ab4fed39d6fdda2db5bcb5ec29c2537d0">internal_size</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a0cd530f8a76a5fb3d60a9230bea30bca">viennacl::traits::internal_size</a>(vec2));</div>
<div class="line"><a name="l00216"></a><span class="lineno"> 216</span> </div>
<div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  <a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html">viennacl::ocl::packed_cl_uint</a> size_vec3;</div>
<div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  size_vec3.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a7991987e7676fabb8d1cbc54eaa0ba01">start</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec3));</div>
<div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  size_vec3.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a457e1f554ae439501613c843b6dad189">stride</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec3));</div>
<div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  size_vec3.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a5f4dcdfd54664fb7859b27f3dec641c0">size</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec3));</div>
<div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  size_vec3.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#ab4fed39d6fdda2db5bcb5ec29c2537d0">internal_size</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a0cd530f8a76a5fb3d60a9230bea30bca">viennacl::traits::internal_size</a>(vec3));</div>
<div class="line"><a name="l00222"></a><span class="lineno"> 222</span> </div>
<div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(k(viennacl::traits::opencl_handle(vec1),</div>
<div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  size_vec1,</div>
<div class="line"><a name="l00225"></a><span class="lineno"> 225</span> </div>
<div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  viennacl::traits::opencl_handle(viennacl::tools::promote_if_host_scalar<T>(alpha)),</div>
<div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  options_alpha,</div>
<div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  viennacl::traits::opencl_handle(vec2),</div>
<div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  size_vec2,</div>
<div class="line"><a name="l00230"></a><span class="lineno"> 230</span> </div>
<div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  viennacl::traits::opencl_handle(viennacl::tools::promote_if_host_scalar<T>(beta)),</div>
<div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  options_beta,</div>
<div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  viennacl::traits::opencl_handle(vec3),</div>
<div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  size_vec3 )</div>
<div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  );</div>
<div class="line"><a name="l00236"></a><span class="lineno"> 236</span> }</div>
<div class="line"><a name="l00237"></a><span class="lineno"> 237</span> </div>
<div class="line"><a name="l00238"></a><span class="lineno"> 238</span> </div>
<div class="line"><a name="l00245"></a><span class="lineno"> 245</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div>
<div class="line"><a name="l00246"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1opencl.html#a964528bcf7fca1f0e63be4b81d9a1a4b"> 246</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#a964528bcf7fca1f0e63be4b81d9a1a4b">vector_assign</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> & vec1, <span class="keyword">const</span> T & alpha, <span class="keywordtype">bool</span> up_to_internal_size = <span class="keyword">false</span>)</div>
<div class="line"><a name="l00247"></a><span class="lineno"> 247</span> {</div>
<div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  <a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> & ctx = <span class="keyword">const_cast<</span><a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> &<span class="keyword">></span>(viennacl::traits::opencl_handle(vec1).context());</div>
<div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  <a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html#a803233f6aed07b9ef954c30257d7a75f">viennacl::linalg::opencl::kernels::vector<T>::init</a>(ctx);</div>
<div class="line"><a name="l00250"></a><span class="lineno"> 250</span> </div>
<div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a> & k = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html">viennacl::linalg::opencl::kernels::vector<T>::program_name</a>(), <span class="stringliteral">"assign_cpu"</span>);</div>
<div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#a0144c18ae9f07722e5b5697335b7cff5">global_work_size</a>(0, std::min<vcl_size_t>(128 * k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>(),</div>
<div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  viennacl::tools::align_to_multiple<vcl_size_t>(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec1), k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>()) ) );</div>
<div class="line"><a name="l00254"></a><span class="lineno"> 254</span> </div>
<div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  cl_uint <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a> = up_to_internal_size ? cl_uint(vec1.<a class="code" href="classviennacl_1_1vector__base.html#a47350ccdc4b0a24eaea0e8d5f9fe7fec">internal_size</a>()) : cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec1));</div>
<div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(k(viennacl::traits::opencl_handle(vec1),</div>
<div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec1)),</div>
<div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec1)),</div>
<div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  size,</div>
<div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  cl_uint(vec1.<a class="code" href="classviennacl_1_1vector__base.html#a47350ccdc4b0a24eaea0e8d5f9fe7fec">internal_size</a>()), <span class="comment">//Note: Do NOT use traits::internal_size() here, because vector proxies don't require padding.</span></div>
<div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  viennacl::traits::opencl_handle(T(alpha)) )</div>
<div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  );</div>
<div class="line"><a name="l00263"></a><span class="lineno"> 263</span> }</div>
<div class="line"><a name="l00264"></a><span class="lineno"> 264</span> </div>
<div class="line"><a name="l00265"></a><span class="lineno"> 265</span> </div>
<div class="line"><a name="l00271"></a><span class="lineno"> 271</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div>
<div class="line"><a name="l00272"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1opencl.html#a8d0663f2f9916ed1ec639bcd1d240a7d"> 272</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#a8d0663f2f9916ed1ec639bcd1d240a7d">vector_swap</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> & vec1, <a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> & vec2)</div>
<div class="line"><a name="l00273"></a><span class="lineno"> 273</span> {</div>
<div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  assert(viennacl::traits::opencl_handle(vec1).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() == viennacl::traits::opencl_handle(vec2).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() && <span class="keywordtype">bool</span>(<span class="stringliteral">"Vectors do not reside in the same OpenCL context. Automatic migration not yet supported!"</span>));</div>
<div class="line"><a name="l00275"></a><span class="lineno"> 275</span> </div>
<div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  <a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> & ctx = <span class="keyword">const_cast<</span><a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> &<span class="keyword">></span>(viennacl::traits::opencl_handle(vec1).context());</div>
<div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  <a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html#a803233f6aed07b9ef954c30257d7a75f">viennacl::linalg::opencl::kernels::vector<T>::init</a>(ctx);</div>
<div class="line"><a name="l00278"></a><span class="lineno"> 278</span> </div>
<div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a> & k = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html">viennacl::linalg::opencl::kernels::vector<T>::program_name</a>(), <span class="stringliteral">"swap"</span>);</div>
<div class="line"><a name="l00280"></a><span class="lineno"> 280</span> </div>
<div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(k(viennacl::traits::opencl_handle(vec1),</div>
<div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec1)),</div>
<div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec1)),</div>
<div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec1)),</div>
<div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  viennacl::traits::opencl_handle(vec2),</div>
<div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec2)),</div>
<div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec2)),</div>
<div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec2)))</div>
<div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  );</div>
<div class="line"><a name="l00290"></a><span class="lineno"> 290</span> }</div>
<div class="line"><a name="l00291"></a><span class="lineno"> 291</span> </div>
<div class="line"><a name="l00293"></a><span class="lineno"> 293</span> </div>
<div class="line"><a name="l00299"></a><span class="lineno"> 299</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T, <span class="keyword">typename</span> OP></div>
<div class="line"><a name="l00300"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1opencl.html#a3676fb99f0f09069c00a2d5eebeb9a3e"> 300</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#a8dd7386eb70a19d9d818b5ba57512d57">element_op</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> & vec1,</div>
<div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  <a class="code" href="classviennacl_1_1vector__expression.html">vector_expression</a><<span class="keyword">const</span> <a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a>, <span class="keyword">const</span> <a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a>, <a class="code" href="structviennacl_1_1op__element__binary.html">op_element_binary<OP></a> > <span class="keyword">const</span> & proxy)</div>
<div class="line"><a name="l00302"></a><span class="lineno"> 302</span> {</div>
<div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  assert(viennacl::traits::opencl_handle(vec1).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() == viennacl::traits::opencl_handle(proxy.lhs()).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() && bool(<span class="stringliteral">"Vectors do not reside in the same OpenCL context. Automatic migration not yet supported!"</span>));</div>
<div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  assert(viennacl::traits::opencl_handle(vec1).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() == viennacl::traits::opencl_handle(proxy.rhs()).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() && bool(<span class="stringliteral">"Vectors do not reside in the same OpenCL context. Automatic migration not yet supported!"</span>));</div>
<div class="line"><a name="l00305"></a><span class="lineno"> 305</span> </div>
<div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  <a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> & ctx = <span class="keyword">const_cast<</span><a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> &<span class="keyword">></span>(viennacl::traits::opencl_handle(vec1).context());</div>
<div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  <a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector__element.html#a18d9e0cc1f4e6235008503386f584414">viennacl::linalg::opencl::kernels::vector_element<T>::init</a>(ctx);</div>
<div class="line"><a name="l00308"></a><span class="lineno"> 308</span> </div>
<div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  std::string kernel_name = <span class="stringliteral">"element_pow"</span>;</div>
<div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  cl_uint op_type = 2; <span class="comment">//0: product, 1: division, 2: power</span></div>
<div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  <span class="keywordflow">if</span> (<a class="code" href="structviennacl_1_1is__division.html">viennacl::is_division<OP>::value</a>)</div>
<div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  {</div>
<div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  op_type = 1;</div>
<div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  kernel_name = <span class="stringliteral">"element_div"</span>;</div>
<div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  }</div>
<div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (<a class="code" href="structviennacl_1_1is__product.html">viennacl::is_product<OP>::value</a>)</div>
<div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  {</div>
<div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  op_type = 0;</div>
<div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  kernel_name = <span class="stringliteral">"element_prod"</span>;</div>
<div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  }</div>
<div class="line"><a name="l00321"></a><span class="lineno"> 321</span> </div>
<div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a> & k = ctx.get_kernel(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector__element.html">viennacl::linalg::opencl::kernels::vector_element<T>::program_name</a>(), kernel_name);</div>
<div class="line"><a name="l00323"></a><span class="lineno"> 323</span> </div>
<div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(k(viennacl::traits::opencl_handle(vec1),</div>
<div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec1)),</div>
<div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec1)),</div>
<div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec1)),</div>
<div class="line"><a name="l00328"></a><span class="lineno"> 328</span> </div>
<div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  viennacl::traits::opencl_handle(proxy.lhs()),</div>
<div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(proxy.lhs())),</div>
<div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(proxy.lhs())),</div>
<div class="line"><a name="l00332"></a><span class="lineno"> 332</span> </div>
<div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  viennacl::traits::opencl_handle(proxy.rhs()),</div>
<div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(proxy.rhs())),</div>
<div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(proxy.rhs())),</div>
<div class="line"><a name="l00336"></a><span class="lineno"> 336</span> </div>
<div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  op_type)</div>
<div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  );</div>
<div class="line"><a name="l00339"></a><span class="lineno"> 339</span> }</div>
<div class="line"><a name="l00340"></a><span class="lineno"> 340</span> </div>
<div class="line"><a name="l00342"></a><span class="lineno"> 342</span> </div>
<div class="line"><a name="l00348"></a><span class="lineno"> 348</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T, <span class="keyword">typename</span> OP></div>
<div class="line"><a name="l00349"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1opencl.html#a0a42d79551b9a8a6f294211a655048ce"> 349</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#a8dd7386eb70a19d9d818b5ba57512d57">element_op</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> & vec1,</div>
<div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  <a class="code" href="classviennacl_1_1vector__expression.html">vector_expression</a><<span class="keyword">const</span> <a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a>, <span class="keyword">const</span> <a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a>, <a class="code" href="structviennacl_1_1op__element__unary.html">op_element_unary<OP></a> > <span class="keyword">const</span> & proxy)</div>
<div class="line"><a name="l00351"></a><span class="lineno"> 351</span> {</div>
<div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  assert(viennacl::traits::opencl_handle(vec1).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() == viennacl::traits::opencl_handle(proxy.lhs()).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() && bool(<span class="stringliteral">"Vectors do not reside in the same OpenCL context. Automatic migration not yet supported!"</span>));</div>
<div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  assert(viennacl::traits::opencl_handle(vec1).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() == viennacl::traits::opencl_handle(proxy.rhs()).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() && bool(<span class="stringliteral">"Vectors do not reside in the same OpenCL context. Automatic migration not yet supported!"</span>));</div>
<div class="line"><a name="l00354"></a><span class="lineno"> 354</span> </div>
<div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  <a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> & ctx = <span class="keyword">const_cast<</span><a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> &<span class="keyword">></span>(viennacl::traits::opencl_handle(vec1).context());</div>
<div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  <a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector__element.html#a18d9e0cc1f4e6235008503386f584414">viennacl::linalg::opencl::kernels::vector_element<T>::init</a>(ctx);</div>
<div class="line"><a name="l00357"></a><span class="lineno"> 357</span> </div>
<div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a> & k = ctx.get_kernel(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector__element.html">viennacl::linalg::opencl::kernels::vector_element<T>::program_name</a>(), <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#aaeb876e922457f997cd0e7f2a51c4e1d">detail::op_to_string</a>(OP()) + <span class="stringliteral">"_assign"</span>);</div>
<div class="line"><a name="l00359"></a><span class="lineno"> 359</span> </div>
<div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  <a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html">viennacl::ocl::packed_cl_uint</a> size_vec1;</div>
<div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  size_vec1.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a7991987e7676fabb8d1cbc54eaa0ba01">start</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec1));</div>
<div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  size_vec1.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a457e1f554ae439501613c843b6dad189">stride</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec1));</div>
<div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  size_vec1.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a5f4dcdfd54664fb7859b27f3dec641c0">size</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec1));</div>
<div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  size_vec1.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#ab4fed39d6fdda2db5bcb5ec29c2537d0">internal_size</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a0cd530f8a76a5fb3d60a9230bea30bca">viennacl::traits::internal_size</a>(vec1));</div>
<div class="line"><a name="l00365"></a><span class="lineno"> 365</span> </div>
<div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  <a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html">viennacl::ocl::packed_cl_uint</a> size_vec2;</div>
<div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  size_vec2.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a7991987e7676fabb8d1cbc54eaa0ba01">start</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(proxy.lhs()));</div>
<div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  size_vec2.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a457e1f554ae439501613c843b6dad189">stride</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(proxy.lhs()));</div>
<div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  size_vec2.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a5f4dcdfd54664fb7859b27f3dec641c0">size</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(proxy.lhs()));</div>
<div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  size_vec2.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#ab4fed39d6fdda2db5bcb5ec29c2537d0">internal_size</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a0cd530f8a76a5fb3d60a9230bea30bca">viennacl::traits::internal_size</a>(proxy.lhs()));</div>
<div class="line"><a name="l00371"></a><span class="lineno"> 371</span> </div>
<div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(k(viennacl::traits::opencl_handle(vec1),</div>
<div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  size_vec1,</div>
<div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  viennacl::traits::opencl_handle(proxy.lhs()),</div>
<div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  size_vec2)</div>
<div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  );</div>
<div class="line"><a name="l00377"></a><span class="lineno"> 377</span> }</div>
<div class="line"><a name="l00378"></a><span class="lineno"> 378</span> </div>
<div class="line"><a name="l00380"></a><span class="lineno"> 380</span> </div>
<div class="line"><a name="l00387"></a><span class="lineno"> 387</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div>
<div class="line"><a name="l00388"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1opencl.html#a1adcbf3b6d428fc941484c35ce7e083a"> 388</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#a1adcbf3b6d428fc941484c35ce7e083a">inner_prod_impl</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> <span class="keyword">const</span> & vec1,</div>
<div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> <span class="keyword">const</span> & vec2,</div>
<div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> & partial_result)</div>
<div class="line"><a name="l00391"></a><span class="lineno"> 391</span> {</div>
<div class="line"><a name="l00392"></a><span class="lineno"> 392</span>  assert(viennacl::traits::opencl_handle(vec1).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() == viennacl::traits::opencl_handle(vec2).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() && <span class="keywordtype">bool</span>(<span class="stringliteral">"Vectors do not reside in the same OpenCL context. Automatic migration not yet supported!"</span>));</div>
<div class="line"><a name="l00393"></a><span class="lineno"> 393</span>  assert(viennacl::traits::opencl_handle(vec2).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() == viennacl::traits::opencl_handle(partial_result).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() && <span class="keywordtype">bool</span>(<span class="stringliteral">"Vectors do not reside in the same OpenCL context. Automatic migration not yet supported!"</span>));</div>
<div class="line"><a name="l00394"></a><span class="lineno"> 394</span> </div>
<div class="line"><a name="l00395"></a><span class="lineno"> 395</span>  <a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> & ctx = <span class="keyword">const_cast<</span><a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> &<span class="keyword">></span>(viennacl::traits::opencl_handle(vec1).context());</div>
<div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  <a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html#a803233f6aed07b9ef954c30257d7a75f">viennacl::linalg::opencl::kernels::vector<T>::init</a>(ctx);</div>
<div class="line"><a name="l00397"></a><span class="lineno"> 397</span> </div>
<div class="line"><a name="l00398"></a><span class="lineno"> 398</span>  assert( (<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec1) == <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec2))</div>
<div class="line"><a name="l00399"></a><span class="lineno"> 399</span>  && <span class="keywordtype">bool</span>(<span class="stringliteral">"Incompatible vector sizes in inner_prod_impl()!"</span>));</div>
<div class="line"><a name="l00400"></a><span class="lineno"> 400</span> </div>
<div class="line"><a name="l00401"></a><span class="lineno"> 401</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a> & k = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html">viennacl::linalg::opencl::kernels::vector<T>::program_name</a>(), <span class="stringliteral">"inner_prod1"</span>);</div>
<div class="line"><a name="l00402"></a><span class="lineno"> 402</span> </div>
<div class="line"><a name="l00403"></a><span class="lineno"> 403</span>  assert( (k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#a0144c18ae9f07722e5b5697335b7cff5">global_work_size</a>() / k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>() <= partial_result.<a class="code" href="classviennacl_1_1vector__base.html#a15c47ae4326098aeaa4ed6b91fc6df9b">size</a>()) && <span class="keywordtype">bool</span>(<span class="stringliteral">"Size mismatch for partial reduction in inner_prod_impl()"</span>) );</div>
<div class="line"><a name="l00404"></a><span class="lineno"> 404</span> </div>
<div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  <a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html">viennacl::ocl::packed_cl_uint</a> size_vec1;</div>
<div class="line"><a name="l00406"></a><span class="lineno"> 406</span>  size_vec1.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a7991987e7676fabb8d1cbc54eaa0ba01">start</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec1));</div>
<div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  size_vec1.stride = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec1));</div>
<div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  size_vec1.size = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec1));</div>
<div class="line"><a name="l00409"></a><span class="lineno"> 409</span>  size_vec1.internal_size = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a0cd530f8a76a5fb3d60a9230bea30bca">viennacl::traits::internal_size</a>(vec1));</div>
<div class="line"><a name="l00410"></a><span class="lineno"> 410</span> </div>
<div class="line"><a name="l00411"></a><span class="lineno"> 411</span>  <a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html">viennacl::ocl::packed_cl_uint</a> size_vec2;</div>
<div class="line"><a name="l00412"></a><span class="lineno"> 412</span>  size_vec2.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a7991987e7676fabb8d1cbc54eaa0ba01">start</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec2));</div>
<div class="line"><a name="l00413"></a><span class="lineno"> 413</span>  size_vec2.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a457e1f554ae439501613c843b6dad189">stride</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec2));</div>
<div class="line"><a name="l00414"></a><span class="lineno"> 414</span>  size_vec2.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a5f4dcdfd54664fb7859b27f3dec641c0">size</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec2));</div>
<div class="line"><a name="l00415"></a><span class="lineno"> 415</span>  size_vec2.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#ab4fed39d6fdda2db5bcb5ec29c2537d0">internal_size</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a0cd530f8a76a5fb3d60a9230bea30bca">viennacl::traits::internal_size</a>(vec2));</div>
<div class="line"><a name="l00416"></a><span class="lineno"> 416</span> </div>
<div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(k(viennacl::traits::opencl_handle(vec1),</div>
<div class="line"><a name="l00418"></a><span class="lineno"> 418</span>  size_vec1,</div>
<div class="line"><a name="l00419"></a><span class="lineno"> 419</span>  viennacl::traits::opencl_handle(vec2),</div>
<div class="line"><a name="l00420"></a><span class="lineno"> 420</span>  size_vec2,</div>
<div class="line"><a name="l00421"></a><span class="lineno"> 421</span>  <a class="code" href="classviennacl_1_1ocl_1_1local__mem.html">viennacl::ocl::local_mem</a>(<span class="keyword">sizeof</span>(<span class="keyword">typename</span> <a class="code" href="structviennacl_1_1result__of_1_1cl__type.html#a340db346857782e06f4eefb3934f28c9">viennacl::result_of::cl_type<T>::type</a>) * k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>()),</div>
<div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  viennacl::traits::opencl_handle(partial_result)</div>
<div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  )</div>
<div class="line"><a name="l00424"></a><span class="lineno"> 424</span>  );</div>
<div class="line"><a name="l00425"></a><span class="lineno"> 425</span> }</div>
<div class="line"><a name="l00426"></a><span class="lineno"> 426</span> </div>
<div class="line"><a name="l00427"></a><span class="lineno"> 427</span> </div>
<div class="line"><a name="l00428"></a><span class="lineno"> 428</span> <span class="comment">//implementation of inner product:</span></div>
<div class="line"><a name="l00429"></a><span class="lineno"> 429</span> <span class="comment">//namespace {</span></div>
<div class="line"><a name="l00436"></a><span class="lineno"> 436</span> <span class="comment"></span><span class="keyword">template</span> <<span class="keyword">typename</span> T></div>
<div class="line"><a name="l00437"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1opencl.html#a21cf46147faedd5a95037598b93cf694"> 437</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#a1adcbf3b6d428fc941484c35ce7e083a">inner_prod_impl</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> <span class="keyword">const</span> & vec1,</div>
<div class="line"><a name="l00438"></a><span class="lineno"> 438</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> <span class="keyword">const</span> & vec2,</div>
<div class="line"><a name="l00439"></a><span class="lineno"> 439</span>  <a class="code" href="classviennacl_1_1scalar.html">scalar<T></a> & result)</div>
<div class="line"><a name="l00440"></a><span class="lineno"> 440</span> {</div>
<div class="line"><a name="l00441"></a><span class="lineno"> 441</span>  assert(viennacl::traits::opencl_handle(vec1).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() == viennacl::traits::opencl_handle(vec2).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() && <span class="keywordtype">bool</span>(<span class="stringliteral">"Vectors do not reside in the same OpenCL context. Automatic migration not yet supported!"</span>));</div>
<div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  assert(viennacl::traits::opencl_handle(vec1).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() == viennacl::traits::opencl_handle(result).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() && <span class="keywordtype">bool</span>(<span class="stringliteral">"Operands do not reside in the same OpenCL context. Automatic migration not yet supported!"</span>));</div>
<div class="line"><a name="l00443"></a><span class="lineno"> 443</span> </div>
<div class="line"><a name="l00444"></a><span class="lineno"> 444</span>  <a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> & ctx = <span class="keyword">const_cast<</span><a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> &<span class="keyword">></span>(viennacl::traits::opencl_handle(vec1).context());</div>
<div class="line"><a name="l00445"></a><span class="lineno"> 445</span> </div>
<div class="line"><a name="l00446"></a><span class="lineno"> 446</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> work_groups = 128;</div>
<div class="line"><a name="l00447"></a><span class="lineno"> 447</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<T></a> temp(work_groups, <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(vec1));</div>
<div class="line"><a name="l00448"></a><span class="lineno"> 448</span>  temp.<a class="code" href="classviennacl_1_1vector.html#a1b73aadf0c7b6c0028fd237ebb30c767">resize</a>(work_groups, ctx); <span class="comment">// bring default-constructed vectors to the correct size:</span></div>
<div class="line"><a name="l00449"></a><span class="lineno"> 449</span> </div>
<div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  <span class="comment">// Step 1: Compute partial inner products for each work group:</span></div>
<div class="line"><a name="l00451"></a><span class="lineno"> 451</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#a1adcbf3b6d428fc941484c35ce7e083a">inner_prod_impl</a>(vec1, vec2, temp);</div>
<div class="line"><a name="l00452"></a><span class="lineno"> 452</span> </div>
<div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  <span class="comment">// Step 2: Sum partial results:</span></div>
<div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a> & ksum = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html">viennacl::linalg::opencl::kernels::vector<T>::program_name</a>(), <span class="stringliteral">"sum"</span>);</div>
<div class="line"><a name="l00455"></a><span class="lineno"> 455</span> </div>
<div class="line"><a name="l00456"></a><span class="lineno"> 456</span>  ksum.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#a0144c18ae9f07722e5b5697335b7cff5">global_work_size</a>(0, ksum.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>(0));</div>
<div class="line"><a name="l00457"></a><span class="lineno"> 457</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(ksum(viennacl::traits::opencl_handle(temp),</div>
<div class="line"><a name="l00458"></a><span class="lineno"> 458</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(temp)),</div>
<div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(temp)),</div>
<div class="line"><a name="l00460"></a><span class="lineno"> 460</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(temp)),</div>
<div class="line"><a name="l00461"></a><span class="lineno"> 461</span>  cl_uint(1),</div>
<div class="line"><a name="l00462"></a><span class="lineno"> 462</span>  <a class="code" href="classviennacl_1_1ocl_1_1local__mem.html">viennacl::ocl::local_mem</a>(<span class="keyword">sizeof</span>(<span class="keyword">typename</span> <a class="code" href="structviennacl_1_1result__of_1_1cl__type.html#a340db346857782e06f4eefb3934f28c9">viennacl::result_of::cl_type<T>::type</a>) * ksum.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>()),</div>
<div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  viennacl::traits::opencl_handle(result) )</div>
<div class="line"><a name="l00464"></a><span class="lineno"> 464</span>  );</div>
<div class="line"><a name="l00465"></a><span class="lineno"> 465</span> }</div>
<div class="line"><a name="l00466"></a><span class="lineno"> 466</span> </div>
<div class="line"><a name="l00467"></a><span class="lineno"> 467</span> <span class="keyword">namespace </span>detail</div>
<div class="line"><a name="l00468"></a><span class="lineno"> 468</span> {</div>
<div class="line"><a name="l00469"></a><span class="lineno"> 469</span>  <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00470"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a66ecf8efa0b41147e85710db81cc9e37"> 470</a></span>  <a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html">viennacl::ocl::packed_cl_uint</a> <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a66ecf8efa0b41147e85710db81cc9e37">make_layout</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & vec)</div>
<div class="line"><a name="l00471"></a><span class="lineno"> 471</span>  {</div>
<div class="line"><a name="l00472"></a><span class="lineno"> 472</span>  <a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html">viennacl::ocl::packed_cl_uint</a> ret;</div>
<div class="line"><a name="l00473"></a><span class="lineno"> 473</span>  ret.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a7991987e7676fabb8d1cbc54eaa0ba01">start</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec));</div>
<div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  ret.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a457e1f554ae439501613c843b6dad189">stride</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec));</div>
<div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  ret.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a5f4dcdfd54664fb7859b27f3dec641c0">size</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec));</div>
<div class="line"><a name="l00476"></a><span class="lineno"> 476</span>  ret.<a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html#ab4fed39d6fdda2db5bcb5ec29c2537d0">internal_size</a> = cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a0cd530f8a76a5fb3d60a9230bea30bca">viennacl::traits::internal_size</a>(vec));</div>
<div class="line"><a name="l00477"></a><span class="lineno"> 477</span>  <span class="keywordflow">return</span> ret;</div>
<div class="line"><a name="l00478"></a><span class="lineno"> 478</span>  }</div>
<div class="line"><a name="l00479"></a><span class="lineno"> 479</span> }</div>
<div class="line"><a name="l00480"></a><span class="lineno"> 480</span> </div>
<div class="line"><a name="l00487"></a><span class="lineno"> 487</span> <span class="keyword">template</span> <<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00488"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1opencl.html#a5b18ba2b0fe0d7f393d99d6c0d0cc3f0"> 488</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#a1adcbf3b6d428fc941484c35ce7e083a">inner_prod_impl</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & x,</div>
<div class="line"><a name="l00489"></a><span class="lineno"> 489</span>  <a class="code" href="classviennacl_1_1vector__tuple.html">vector_tuple<NumericT></a> <span class="keyword">const</span> & vec_tuple,</div>
<div class="line"><a name="l00490"></a><span class="lineno"> 490</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & result)</div>
<div class="line"><a name="l00491"></a><span class="lineno"> 491</span> {</div>
<div class="line"><a name="l00492"></a><span class="lineno"> 492</span>  assert(viennacl::traits::opencl_handle(x).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() == viennacl::traits::opencl_handle(result).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() && <span class="keywordtype">bool</span>(<span class="stringliteral">"Operands do not reside in the same OpenCL context. Automatic migration not yet supported!"</span>));</div>
<div class="line"><a name="l00493"></a><span class="lineno"> 493</span> </div>
<div class="line"><a name="l00494"></a><span class="lineno"> 494</span>  <a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> & ctx = <span class="keyword">const_cast<</span><a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> &<span class="keyword">></span>(viennacl::traits::opencl_handle(x).context());</div>
<div class="line"><a name="l00495"></a><span class="lineno"> 495</span>  <a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html#a803233f6aed07b9ef954c30257d7a75f">viennacl::linalg::opencl::kernels::vector<NumericT>::init</a>(ctx);</div>
<div class="line"><a name="l00496"></a><span class="lineno"> 496</span>  <a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector__multi__inner__prod.html#abb6e0bf18d527d2a9d075b28e0b89d93">viennacl::linalg::opencl::kernels::vector_multi_inner_prod<NumericT>::init</a>(ctx);</div>
<div class="line"><a name="l00497"></a><span class="lineno"> 497</span> </div>
<div class="line"><a name="l00498"></a><span class="lineno"> 498</span>  <a class="code" href="structviennacl_1_1ocl_1_1packed__cl__uint.html">viennacl::ocl::packed_cl_uint</a> layout_x = <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a66ecf8efa0b41147e85710db81cc9e37">detail::make_layout</a>(x);</div>
<div class="line"><a name="l00499"></a><span class="lineno"> 499</span> </div>
<div class="line"><a name="l00500"></a><span class="lineno"> 500</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a> & ksum = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector__multi__inner__prod.html">viennacl::linalg::opencl::kernels::vector_multi_inner_prod<NumericT>::program_name</a>(), <span class="stringliteral">"sum_inner_prod"</span>);</div>
<div class="line"><a name="l00501"></a><span class="lineno"> 501</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a> & inner_prod_kernel_1 = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html">viennacl::linalg::opencl::kernels::vector<NumericT>::program_name</a>(), <span class="stringliteral">"inner_prod1"</span>);</div>
<div class="line"><a name="l00502"></a><span class="lineno"> 502</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a> & inner_prod_kernel_2 = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector__multi__inner__prod.html">viennacl::linalg::opencl::kernels::vector_multi_inner_prod<NumericT>::program_name</a>(), <span class="stringliteral">"inner_prod2"</span>);</div>
<div class="line"><a name="l00503"></a><span class="lineno"> 503</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a> & inner_prod_kernel_3 = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector__multi__inner__prod.html">viennacl::linalg::opencl::kernels::vector_multi_inner_prod<NumericT>::program_name</a>(), <span class="stringliteral">"inner_prod3"</span>);</div>
<div class="line"><a name="l00504"></a><span class="lineno"> 504</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a> & inner_prod_kernel_4 = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector__multi__inner__prod.html">viennacl::linalg::opencl::kernels::vector_multi_inner_prod<NumericT>::program_name</a>(), <span class="stringliteral">"inner_prod4"</span>);</div>
<div class="line"><a name="l00505"></a><span class="lineno"> 505</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a> & inner_prod_kernel_8 = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector__multi__inner__prod.html">viennacl::linalg::opencl::kernels::vector_multi_inner_prod<NumericT>::program_name</a>(), <span class="stringliteral">"inner_prod8"</span>);</div>
<div class="line"><a name="l00506"></a><span class="lineno"> 506</span> </div>
<div class="line"><a name="l00507"></a><span class="lineno"> 507</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> work_groups = inner_prod_kernel_8.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#a0144c18ae9f07722e5b5697335b7cff5">global_work_size</a>(0) / inner_prod_kernel_8.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>(0);</div>
<div class="line"><a name="l00508"></a><span class="lineno"> 508</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<NumericT></a> temp(8 * work_groups, <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(x));</div>
<div class="line"><a name="l00509"></a><span class="lineno"> 509</span> </div>
<div class="line"><a name="l00510"></a><span class="lineno"> 510</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> current_index = 0;</div>
<div class="line"><a name="l00511"></a><span class="lineno"> 511</span>  <span class="keywordflow">while</span> (current_index < vec_tuple.<a class="code" href="classviennacl_1_1vector__tuple.html#a9f2fc8200f0199e396eaeca310f8e9f4">const_size</a>())</div>
<div class="line"><a name="l00512"></a><span class="lineno"> 512</span>  {</div>
<div class="line"><a name="l00513"></a><span class="lineno"> 513</span>  <span class="keywordflow">switch</span> (vec_tuple.<a class="code" href="classviennacl_1_1vector__tuple.html#a9f2fc8200f0199e396eaeca310f8e9f4">const_size</a>() - current_index)</div>
<div class="line"><a name="l00514"></a><span class="lineno"> 514</span>  {</div>
<div class="line"><a name="l00515"></a><span class="lineno"> 515</span>  <span class="keywordflow">case</span> 7:</div>
<div class="line"><a name="l00516"></a><span class="lineno"> 516</span>  <span class="keywordflow">case</span> 6:</div>
<div class="line"><a name="l00517"></a><span class="lineno"> 517</span>  <span class="keywordflow">case</span> 5:</div>
<div class="line"><a name="l00518"></a><span class="lineno"> 518</span>  <span class="keywordflow">case</span> 4:</div>
<div class="line"><a name="l00519"></a><span class="lineno"> 519</span>  {</div>
<div class="line"><a name="l00520"></a><span class="lineno"> 520</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & y0 = vec_tuple.<a class="code" href="classviennacl_1_1vector__tuple.html#a9e4b9367232f8937dfaddeaeca64e0e0">const_at</a>(current_index );</div>
<div class="line"><a name="l00521"></a><span class="lineno"> 521</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & y1 = vec_tuple.<a class="code" href="classviennacl_1_1vector__tuple.html#a9e4b9367232f8937dfaddeaeca64e0e0">const_at</a>(current_index + 1);</div>
<div class="line"><a name="l00522"></a><span class="lineno"> 522</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & y2 = vec_tuple.<a class="code" href="classviennacl_1_1vector__tuple.html#a9e4b9367232f8937dfaddeaeca64e0e0">const_at</a>(current_index + 2);</div>
<div class="line"><a name="l00523"></a><span class="lineno"> 523</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & y3 = vec_tuple.<a class="code" href="classviennacl_1_1vector__tuple.html#a9e4b9367232f8937dfaddeaeca64e0e0">const_at</a>(current_index + 3);</div>
<div class="line"><a name="l00524"></a><span class="lineno"> 524</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(inner_prod_kernel_4( viennacl::traits::opencl_handle(x), layout_x,</div>
<div class="line"><a name="l00525"></a><span class="lineno"> 525</span>  viennacl::traits::opencl_handle(y0), <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a66ecf8efa0b41147e85710db81cc9e37">detail::make_layout</a>(y0),</div>
<div class="line"><a name="l00526"></a><span class="lineno"> 526</span>  viennacl::traits::opencl_handle(y1), <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a66ecf8efa0b41147e85710db81cc9e37">detail::make_layout</a>(y1),</div>
<div class="line"><a name="l00527"></a><span class="lineno"> 527</span>  viennacl::traits::opencl_handle(y2), <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a66ecf8efa0b41147e85710db81cc9e37">detail::make_layout</a>(y2),</div>
<div class="line"><a name="l00528"></a><span class="lineno"> 528</span>  viennacl::traits::opencl_handle(y3), <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a66ecf8efa0b41147e85710db81cc9e37">detail::make_layout</a>(y3),</div>
<div class="line"><a name="l00529"></a><span class="lineno"> 529</span>  <a class="code" href="classviennacl_1_1ocl_1_1local__mem.html">viennacl::ocl::local_mem</a>(<span class="keyword">sizeof</span>(<span class="keyword">typename</span> <a class="code" href="structviennacl_1_1result__of_1_1cl__type.html#a340db346857782e06f4eefb3934f28c9">viennacl::result_of::cl_type<NumericT>::type</a>) * 4 * inner_prod_kernel_4.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>()),</div>
<div class="line"><a name="l00530"></a><span class="lineno"> 530</span>  viennacl::traits::opencl_handle(temp)</div>
<div class="line"><a name="l00531"></a><span class="lineno"> 531</span>  ) );</div>
<div class="line"><a name="l00532"></a><span class="lineno"> 532</span> </div>
<div class="line"><a name="l00533"></a><span class="lineno"> 533</span>  ksum.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#a0144c18ae9f07722e5b5697335b7cff5">global_work_size</a>(0, 4 * ksum.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>(0));</div>
<div class="line"><a name="l00534"></a><span class="lineno"> 534</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(ksum(viennacl::traits::opencl_handle(temp),</div>
<div class="line"><a name="l00535"></a><span class="lineno"> 535</span>  cl_uint(work_groups),</div>
<div class="line"><a name="l00536"></a><span class="lineno"> 536</span>  <a class="code" href="classviennacl_1_1ocl_1_1local__mem.html">viennacl::ocl::local_mem</a>(<span class="keyword">sizeof</span>(<span class="keyword">typename</span> <a class="code" href="structviennacl_1_1result__of_1_1cl__type.html#a340db346857782e06f4eefb3934f28c9">viennacl::result_of::cl_type<NumericT>::type</a>) * 4 * ksum.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>()),</div>
<div class="line"><a name="l00537"></a><span class="lineno"> 537</span>  viennacl::traits::opencl_handle(result),</div>
<div class="line"><a name="l00538"></a><span class="lineno"> 538</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(result) + current_index * <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(result)),</div>
<div class="line"><a name="l00539"></a><span class="lineno"> 539</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(result))</div>
<div class="line"><a name="l00540"></a><span class="lineno"> 540</span>  )</div>
<div class="line"><a name="l00541"></a><span class="lineno"> 541</span>  );</div>
<div class="line"><a name="l00542"></a><span class="lineno"> 542</span>  }</div>
<div class="line"><a name="l00543"></a><span class="lineno"> 543</span>  current_index += 4;</div>
<div class="line"><a name="l00544"></a><span class="lineno"> 544</span>  <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00545"></a><span class="lineno"> 545</span> </div>
<div class="line"><a name="l00546"></a><span class="lineno"> 546</span>  <span class="keywordflow">case</span> 3:</div>
<div class="line"><a name="l00547"></a><span class="lineno"> 547</span>  {</div>
<div class="line"><a name="l00548"></a><span class="lineno"> 548</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & y0 = vec_tuple.<a class="code" href="classviennacl_1_1vector__tuple.html#a9e4b9367232f8937dfaddeaeca64e0e0">const_at</a>(current_index );</div>
<div class="line"><a name="l00549"></a><span class="lineno"> 549</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & y1 = vec_tuple.<a class="code" href="classviennacl_1_1vector__tuple.html#a9e4b9367232f8937dfaddeaeca64e0e0">const_at</a>(current_index + 1);</div>
<div class="line"><a name="l00550"></a><span class="lineno"> 550</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & y2 = vec_tuple.<a class="code" href="classviennacl_1_1vector__tuple.html#a9e4b9367232f8937dfaddeaeca64e0e0">const_at</a>(current_index + 2);</div>
<div class="line"><a name="l00551"></a><span class="lineno"> 551</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(inner_prod_kernel_3( viennacl::traits::opencl_handle(x), layout_x,</div>
<div class="line"><a name="l00552"></a><span class="lineno"> 552</span>  viennacl::traits::opencl_handle(y0), <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a66ecf8efa0b41147e85710db81cc9e37">detail::make_layout</a>(y0),</div>
<div class="line"><a name="l00553"></a><span class="lineno"> 553</span>  viennacl::traits::opencl_handle(y1), <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a66ecf8efa0b41147e85710db81cc9e37">detail::make_layout</a>(y1),</div>
<div class="line"><a name="l00554"></a><span class="lineno"> 554</span>  viennacl::traits::opencl_handle(y2), <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a66ecf8efa0b41147e85710db81cc9e37">detail::make_layout</a>(y2),</div>
<div class="line"><a name="l00555"></a><span class="lineno"> 555</span>  <a class="code" href="classviennacl_1_1ocl_1_1local__mem.html">viennacl::ocl::local_mem</a>(<span class="keyword">sizeof</span>(<span class="keyword">typename</span> <a class="code" href="structviennacl_1_1result__of_1_1cl__type.html#a340db346857782e06f4eefb3934f28c9">viennacl::result_of::cl_type<NumericT>::type</a>) * 3 * inner_prod_kernel_3.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>()),</div>
<div class="line"><a name="l00556"></a><span class="lineno"> 556</span>  viennacl::traits::opencl_handle(temp)</div>
<div class="line"><a name="l00557"></a><span class="lineno"> 557</span>  ) );</div>
<div class="line"><a name="l00558"></a><span class="lineno"> 558</span> </div>
<div class="line"><a name="l00559"></a><span class="lineno"> 559</span>  ksum.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#a0144c18ae9f07722e5b5697335b7cff5">global_work_size</a>(0, 3 * ksum.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>(0));</div>
<div class="line"><a name="l00560"></a><span class="lineno"> 560</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(ksum(viennacl::traits::opencl_handle(temp),</div>
<div class="line"><a name="l00561"></a><span class="lineno"> 561</span>  cl_uint(work_groups),</div>
<div class="line"><a name="l00562"></a><span class="lineno"> 562</span>  <a class="code" href="classviennacl_1_1ocl_1_1local__mem.html">viennacl::ocl::local_mem</a>(<span class="keyword">sizeof</span>(<span class="keyword">typename</span> <a class="code" href="structviennacl_1_1result__of_1_1cl__type.html#a340db346857782e06f4eefb3934f28c9">viennacl::result_of::cl_type<NumericT>::type</a>) * 3 * ksum.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>()),</div>
<div class="line"><a name="l00563"></a><span class="lineno"> 563</span>  viennacl::traits::opencl_handle(result),</div>
<div class="line"><a name="l00564"></a><span class="lineno"> 564</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(result) + current_index * <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(result)),</div>
<div class="line"><a name="l00565"></a><span class="lineno"> 565</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(result))</div>
<div class="line"><a name="l00566"></a><span class="lineno"> 566</span>  )</div>
<div class="line"><a name="l00567"></a><span class="lineno"> 567</span>  );</div>
<div class="line"><a name="l00568"></a><span class="lineno"> 568</span>  }</div>
<div class="line"><a name="l00569"></a><span class="lineno"> 569</span>  current_index += 3;</div>
<div class="line"><a name="l00570"></a><span class="lineno"> 570</span>  <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00571"></a><span class="lineno"> 571</span> </div>
<div class="line"><a name="l00572"></a><span class="lineno"> 572</span>  <span class="keywordflow">case</span> 2:</div>
<div class="line"><a name="l00573"></a><span class="lineno"> 573</span>  {</div>
<div class="line"><a name="l00574"></a><span class="lineno"> 574</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & y0 = vec_tuple.<a class="code" href="classviennacl_1_1vector__tuple.html#a9e4b9367232f8937dfaddeaeca64e0e0">const_at</a>(current_index );</div>
<div class="line"><a name="l00575"></a><span class="lineno"> 575</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & y1 = vec_tuple.<a class="code" href="classviennacl_1_1vector__tuple.html#a9e4b9367232f8937dfaddeaeca64e0e0">const_at</a>(current_index + 1);</div>
<div class="line"><a name="l00576"></a><span class="lineno"> 576</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(inner_prod_kernel_2( viennacl::traits::opencl_handle(x), layout_x,</div>
<div class="line"><a name="l00577"></a><span class="lineno"> 577</span>  viennacl::traits::opencl_handle(y0), <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a66ecf8efa0b41147e85710db81cc9e37">detail::make_layout</a>(y0),</div>
<div class="line"><a name="l00578"></a><span class="lineno"> 578</span>  viennacl::traits::opencl_handle(y1), <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a66ecf8efa0b41147e85710db81cc9e37">detail::make_layout</a>(y1),</div>
<div class="line"><a name="l00579"></a><span class="lineno"> 579</span>  <a class="code" href="classviennacl_1_1ocl_1_1local__mem.html">viennacl::ocl::local_mem</a>(<span class="keyword">sizeof</span>(<span class="keyword">typename</span> <a class="code" href="structviennacl_1_1result__of_1_1cl__type.html#a340db346857782e06f4eefb3934f28c9">viennacl::result_of::cl_type<NumericT>::type</a>) * 2 * inner_prod_kernel_2.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>()),</div>
<div class="line"><a name="l00580"></a><span class="lineno"> 580</span>  viennacl::traits::opencl_handle(temp)</div>
<div class="line"><a name="l00581"></a><span class="lineno"> 581</span>  ) );</div>
<div class="line"><a name="l00582"></a><span class="lineno"> 582</span> </div>
<div class="line"><a name="l00583"></a><span class="lineno"> 583</span>  ksum.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#a0144c18ae9f07722e5b5697335b7cff5">global_work_size</a>(0, 2 * ksum.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>(0));</div>
<div class="line"><a name="l00584"></a><span class="lineno"> 584</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(ksum(viennacl::traits::opencl_handle(temp),</div>
<div class="line"><a name="l00585"></a><span class="lineno"> 585</span>  cl_uint(work_groups),</div>
<div class="line"><a name="l00586"></a><span class="lineno"> 586</span>  <a class="code" href="classviennacl_1_1ocl_1_1local__mem.html">viennacl::ocl::local_mem</a>(<span class="keyword">sizeof</span>(<span class="keyword">typename</span> <a class="code" href="structviennacl_1_1result__of_1_1cl__type.html#a340db346857782e06f4eefb3934f28c9">viennacl::result_of::cl_type<NumericT>::type</a>) * 2 * ksum.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>()),</div>
<div class="line"><a name="l00587"></a><span class="lineno"> 587</span>  viennacl::traits::opencl_handle(result),</div>
<div class="line"><a name="l00588"></a><span class="lineno"> 588</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(result) + current_index * <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(result)),</div>
<div class="line"><a name="l00589"></a><span class="lineno"> 589</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(result))</div>
<div class="line"><a name="l00590"></a><span class="lineno"> 590</span>  )</div>
<div class="line"><a name="l00591"></a><span class="lineno"> 591</span>  );</div>
<div class="line"><a name="l00592"></a><span class="lineno"> 592</span>  }</div>
<div class="line"><a name="l00593"></a><span class="lineno"> 593</span>  current_index += 2;</div>
<div class="line"><a name="l00594"></a><span class="lineno"> 594</span>  <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00595"></a><span class="lineno"> 595</span> </div>
<div class="line"><a name="l00596"></a><span class="lineno"> 596</span>  <span class="keywordflow">case</span> 1:</div>
<div class="line"><a name="l00597"></a><span class="lineno"> 597</span>  {</div>
<div class="line"><a name="l00598"></a><span class="lineno"> 598</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & y0 = vec_tuple.<a class="code" href="classviennacl_1_1vector__tuple.html#a9e4b9367232f8937dfaddeaeca64e0e0">const_at</a>(current_index );</div>
<div class="line"><a name="l00599"></a><span class="lineno"> 599</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(inner_prod_kernel_1( viennacl::traits::opencl_handle(x), layout_x,</div>
<div class="line"><a name="l00600"></a><span class="lineno"> 600</span>  viennacl::traits::opencl_handle(y0), <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a66ecf8efa0b41147e85710db81cc9e37">detail::make_layout</a>(y0),</div>
<div class="line"><a name="l00601"></a><span class="lineno"> 601</span>  <a class="code" href="classviennacl_1_1ocl_1_1local__mem.html">viennacl::ocl::local_mem</a>(<span class="keyword">sizeof</span>(<span class="keyword">typename</span> <a class="code" href="structviennacl_1_1result__of_1_1cl__type.html#a340db346857782e06f4eefb3934f28c9">viennacl::result_of::cl_type<NumericT>::type</a>) * 1 * inner_prod_kernel_1.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>()),</div>
<div class="line"><a name="l00602"></a><span class="lineno"> 602</span>  viennacl::traits::opencl_handle(temp)</div>
<div class="line"><a name="l00603"></a><span class="lineno"> 603</span>  ) );</div>
<div class="line"><a name="l00604"></a><span class="lineno"> 604</span> </div>
<div class="line"><a name="l00605"></a><span class="lineno"> 605</span>  ksum.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#a0144c18ae9f07722e5b5697335b7cff5">global_work_size</a>(0, 1 * ksum.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>(0));</div>
<div class="line"><a name="l00606"></a><span class="lineno"> 606</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(ksum(viennacl::traits::opencl_handle(temp),</div>
<div class="line"><a name="l00607"></a><span class="lineno"> 607</span>  cl_uint(work_groups),</div>
<div class="line"><a name="l00608"></a><span class="lineno"> 608</span>  <a class="code" href="classviennacl_1_1ocl_1_1local__mem.html">viennacl::ocl::local_mem</a>(<span class="keyword">sizeof</span>(<span class="keyword">typename</span> <a class="code" href="structviennacl_1_1result__of_1_1cl__type.html#a340db346857782e06f4eefb3934f28c9">viennacl::result_of::cl_type<NumericT>::type</a>) * 1 * ksum.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>()),</div>
<div class="line"><a name="l00609"></a><span class="lineno"> 609</span>  viennacl::traits::opencl_handle(result),</div>
<div class="line"><a name="l00610"></a><span class="lineno"> 610</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(result) + current_index * <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(result)),</div>
<div class="line"><a name="l00611"></a><span class="lineno"> 611</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(result))</div>
<div class="line"><a name="l00612"></a><span class="lineno"> 612</span>  )</div>
<div class="line"><a name="l00613"></a><span class="lineno"> 613</span>  );</div>
<div class="line"><a name="l00614"></a><span class="lineno"> 614</span>  }</div>
<div class="line"><a name="l00615"></a><span class="lineno"> 615</span>  current_index += 1;</div>
<div class="line"><a name="l00616"></a><span class="lineno"> 616</span>  <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00617"></a><span class="lineno"> 617</span> </div>
<div class="line"><a name="l00618"></a><span class="lineno"> 618</span>  <span class="keywordflow">default</span>: <span class="comment">//8 or more vectors</span></div>
<div class="line"><a name="l00619"></a><span class="lineno"> 619</span>  {</div>
<div class="line"><a name="l00620"></a><span class="lineno"> 620</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & y0 = vec_tuple.<a class="code" href="classviennacl_1_1vector__tuple.html#a9e4b9367232f8937dfaddeaeca64e0e0">const_at</a>(current_index );</div>
<div class="line"><a name="l00621"></a><span class="lineno"> 621</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & y1 = vec_tuple.<a class="code" href="classviennacl_1_1vector__tuple.html#a9e4b9367232f8937dfaddeaeca64e0e0">const_at</a>(current_index + 1);</div>
<div class="line"><a name="l00622"></a><span class="lineno"> 622</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & y2 = vec_tuple.<a class="code" href="classviennacl_1_1vector__tuple.html#a9e4b9367232f8937dfaddeaeca64e0e0">const_at</a>(current_index + 2);</div>
<div class="line"><a name="l00623"></a><span class="lineno"> 623</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & y3 = vec_tuple.<a class="code" href="classviennacl_1_1vector__tuple.html#a9e4b9367232f8937dfaddeaeca64e0e0">const_at</a>(current_index + 3);</div>
<div class="line"><a name="l00624"></a><span class="lineno"> 624</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & y4 = vec_tuple.<a class="code" href="classviennacl_1_1vector__tuple.html#a9e4b9367232f8937dfaddeaeca64e0e0">const_at</a>(current_index + 4);</div>
<div class="line"><a name="l00625"></a><span class="lineno"> 625</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & y5 = vec_tuple.<a class="code" href="classviennacl_1_1vector__tuple.html#a9e4b9367232f8937dfaddeaeca64e0e0">const_at</a>(current_index + 5);</div>
<div class="line"><a name="l00626"></a><span class="lineno"> 626</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & y6 = vec_tuple.<a class="code" href="classviennacl_1_1vector__tuple.html#a9e4b9367232f8937dfaddeaeca64e0e0">const_at</a>(current_index + 6);</div>
<div class="line"><a name="l00627"></a><span class="lineno"> 627</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & y7 = vec_tuple.<a class="code" href="classviennacl_1_1vector__tuple.html#a9e4b9367232f8937dfaddeaeca64e0e0">const_at</a>(current_index + 7);</div>
<div class="line"><a name="l00628"></a><span class="lineno"> 628</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(inner_prod_kernel_8( viennacl::traits::opencl_handle(x), layout_x,</div>
<div class="line"><a name="l00629"></a><span class="lineno"> 629</span>  viennacl::traits::opencl_handle(y0), <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a66ecf8efa0b41147e85710db81cc9e37">detail::make_layout</a>(y0),</div>
<div class="line"><a name="l00630"></a><span class="lineno"> 630</span>  viennacl::traits::opencl_handle(y1), <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a66ecf8efa0b41147e85710db81cc9e37">detail::make_layout</a>(y1),</div>
<div class="line"><a name="l00631"></a><span class="lineno"> 631</span>  viennacl::traits::opencl_handle(y2), <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a66ecf8efa0b41147e85710db81cc9e37">detail::make_layout</a>(y2),</div>
<div class="line"><a name="l00632"></a><span class="lineno"> 632</span>  viennacl::traits::opencl_handle(y3), <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a66ecf8efa0b41147e85710db81cc9e37">detail::make_layout</a>(y3),</div>
<div class="line"><a name="l00633"></a><span class="lineno"> 633</span>  viennacl::traits::opencl_handle(y4), <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a66ecf8efa0b41147e85710db81cc9e37">detail::make_layout</a>(y4),</div>
<div class="line"><a name="l00634"></a><span class="lineno"> 634</span>  viennacl::traits::opencl_handle(y5), <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a66ecf8efa0b41147e85710db81cc9e37">detail::make_layout</a>(y5),</div>
<div class="line"><a name="l00635"></a><span class="lineno"> 635</span>  viennacl::traits::opencl_handle(y6), <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a66ecf8efa0b41147e85710db81cc9e37">detail::make_layout</a>(y6),</div>
<div class="line"><a name="l00636"></a><span class="lineno"> 636</span>  viennacl::traits::opencl_handle(y7), <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a66ecf8efa0b41147e85710db81cc9e37">detail::make_layout</a>(y7),</div>
<div class="line"><a name="l00637"></a><span class="lineno"> 637</span>  <a class="code" href="classviennacl_1_1ocl_1_1local__mem.html">viennacl::ocl::local_mem</a>(<span class="keyword">sizeof</span>(<span class="keyword">typename</span> <a class="code" href="structviennacl_1_1result__of_1_1cl__type.html#a340db346857782e06f4eefb3934f28c9">viennacl::result_of::cl_type<NumericT>::type</a>) * 8 * inner_prod_kernel_8.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>()),</div>
<div class="line"><a name="l00638"></a><span class="lineno"> 638</span>  viennacl::traits::opencl_handle(temp)</div>
<div class="line"><a name="l00639"></a><span class="lineno"> 639</span>  ) );</div>
<div class="line"><a name="l00640"></a><span class="lineno"> 640</span> </div>
<div class="line"><a name="l00641"></a><span class="lineno"> 641</span>  ksum.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#a0144c18ae9f07722e5b5697335b7cff5">global_work_size</a>(0, 8 * ksum.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>(0));</div>
<div class="line"><a name="l00642"></a><span class="lineno"> 642</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(ksum(viennacl::traits::opencl_handle(temp),</div>
<div class="line"><a name="l00643"></a><span class="lineno"> 643</span>  cl_uint(work_groups),</div>
<div class="line"><a name="l00644"></a><span class="lineno"> 644</span>  <a class="code" href="classviennacl_1_1ocl_1_1local__mem.html">viennacl::ocl::local_mem</a>(<span class="keyword">sizeof</span>(<span class="keyword">typename</span> <a class="code" href="structviennacl_1_1result__of_1_1cl__type.html#a340db346857782e06f4eefb3934f28c9">viennacl::result_of::cl_type<NumericT>::type</a>) * 8 * ksum.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>()),</div>
<div class="line"><a name="l00645"></a><span class="lineno"> 645</span>  viennacl::traits::opencl_handle(result),</div>
<div class="line"><a name="l00646"></a><span class="lineno"> 646</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(result) + current_index * <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(result)),</div>
<div class="line"><a name="l00647"></a><span class="lineno"> 647</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(result))</div>
<div class="line"><a name="l00648"></a><span class="lineno"> 648</span>  )</div>
<div class="line"><a name="l00649"></a><span class="lineno"> 649</span>  );</div>
<div class="line"><a name="l00650"></a><span class="lineno"> 650</span>  }</div>
<div class="line"><a name="l00651"></a><span class="lineno"> 651</span>  current_index += 8;</div>
<div class="line"><a name="l00652"></a><span class="lineno"> 652</span>  <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00653"></a><span class="lineno"> 653</span>  }</div>
<div class="line"><a name="l00654"></a><span class="lineno"> 654</span>  }</div>
<div class="line"><a name="l00655"></a><span class="lineno"> 655</span> </div>
<div class="line"><a name="l00656"></a><span class="lineno"> 656</span> }</div>
<div class="line"><a name="l00657"></a><span class="lineno"> 657</span> </div>
<div class="line"><a name="l00658"></a><span class="lineno"> 658</span> </div>
<div class="line"><a name="l00659"></a><span class="lineno"> 659</span> </div>
<div class="line"><a name="l00660"></a><span class="lineno"> 660</span> <span class="comment">//implementation of inner product:</span></div>
<div class="line"><a name="l00661"></a><span class="lineno"> 661</span> <span class="comment">//namespace {</span></div>
<div class="line"><a name="l00668"></a><span class="lineno"> 668</span> <span class="comment"></span><span class="keyword">template</span> <<span class="keyword">typename</span> T></div>
<div class="line"><a name="l00669"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1opencl.html#aa3db821922ad772f03e524d7dabc022d"> 669</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#aa3db821922ad772f03e524d7dabc022d">inner_prod_cpu</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> <span class="keyword">const</span> & vec1,</div>
<div class="line"><a name="l00670"></a><span class="lineno"> 670</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> <span class="keyword">const</span> & vec2,</div>
<div class="line"><a name="l00671"></a><span class="lineno"> 671</span>  T & result)</div>
<div class="line"><a name="l00672"></a><span class="lineno"> 672</span> {</div>
<div class="line"><a name="l00673"></a><span class="lineno"> 673</span>  assert(viennacl::traits::opencl_handle(vec1).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() == viennacl::traits::opencl_handle(vec2).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() && <span class="keywordtype">bool</span>(<span class="stringliteral">"Vectors do not reside in the same OpenCL context. Automatic migration not yet supported!"</span>));</div>
<div class="line"><a name="l00674"></a><span class="lineno"> 674</span> </div>
<div class="line"><a name="l00675"></a><span class="lineno"> 675</span>  <a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> & ctx = <span class="keyword">const_cast<</span><a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> &<span class="keyword">></span>(viennacl::traits::opencl_handle(vec1).context());</div>
<div class="line"><a name="l00676"></a><span class="lineno"> 676</span> </div>
<div class="line"><a name="l00677"></a><span class="lineno"> 677</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> work_groups = 128;</div>
<div class="line"><a name="l00678"></a><span class="lineno"> 678</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<T></a> temp(work_groups, <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(vec1));</div>
<div class="line"><a name="l00679"></a><span class="lineno"> 679</span>  temp.<a class="code" href="classviennacl_1_1vector.html#a1b73aadf0c7b6c0028fd237ebb30c767">resize</a>(work_groups, ctx); <span class="comment">// bring default-constructed vectors to the correct size:</span></div>
<div class="line"><a name="l00680"></a><span class="lineno"> 680</span> </div>
<div class="line"><a name="l00681"></a><span class="lineno"> 681</span>  <span class="comment">// Step 1: Compute partial inner products for each work group:</span></div>
<div class="line"><a name="l00682"></a><span class="lineno"> 682</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#a1adcbf3b6d428fc941484c35ce7e083a">inner_prod_impl</a>(vec1, vec2, temp);</div>
<div class="line"><a name="l00683"></a><span class="lineno"> 683</span> </div>
<div class="line"><a name="l00684"></a><span class="lineno"> 684</span>  <span class="comment">// Step 2: Sum partial results:</span></div>
<div class="line"><a name="l00685"></a><span class="lineno"> 685</span> </div>
<div class="line"><a name="l00686"></a><span class="lineno"> 686</span>  <span class="comment">// Now copy partial results from GPU back to CPU and run reduction there:</span></div>
<div class="line"><a name="l00687"></a><span class="lineno"> 687</span>  std::vector<T> temp_cpu(work_groups);</div>
<div class="line"><a name="l00688"></a><span class="lineno"> 688</span>  <a class="code" href="namespaceviennacl.html#aaa5c8726b45bc89a523ca2fa8c42107a">viennacl::fast_copy</a>(temp.<a class="code" href="classviennacl_1_1vector__base.html#a762d98e2f912fc534951f25555b6077f">begin</a>(), temp.<a class="code" href="classviennacl_1_1vector__base.html#aba8a76bd4c96435ba68cf96b9e5132a6">end</a>(), temp_cpu.begin());</div>
<div class="line"><a name="l00689"></a><span class="lineno"> 689</span> </div>
<div class="line"><a name="l00690"></a><span class="lineno"> 690</span>  result = 0;</div>
<div class="line"><a name="l00691"></a><span class="lineno"> 691</span>  <span class="keywordflow">for</span> (<span class="keyword">typename</span> std::vector<T>::const_iterator it = temp_cpu.begin(); it != temp_cpu.end(); ++it)</div>
<div class="line"><a name="l00692"></a><span class="lineno"> 692</span>  result += *it;</div>
<div class="line"><a name="l00693"></a><span class="lineno"> 693</span> }</div>
<div class="line"><a name="l00694"></a><span class="lineno"> 694</span> </div>
<div class="line"><a name="l00695"></a><span class="lineno"> 695</span> </div>
<div class="line"><a name="l00697"></a><span class="lineno"> 697</span> </div>
<div class="line"><a name="l00704"></a><span class="lineno"> 704</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div>
<div class="line"><a name="l00705"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1opencl.html#ad44f85d3504ba0dc38d734f14ec92de8"> 705</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#ad44f85d3504ba0dc38d734f14ec92de8">norm_reduction_impl</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> <span class="keyword">const</span> & vec,</div>
<div class="line"><a name="l00706"></a><span class="lineno"> 706</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> & partial_result,</div>
<div class="line"><a name="l00707"></a><span class="lineno"> 707</span>  cl_uint norm_id)</div>
<div class="line"><a name="l00708"></a><span class="lineno"> 708</span> {</div>
<div class="line"><a name="l00709"></a><span class="lineno"> 709</span>  assert(viennacl::traits::opencl_handle(vec).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() == viennacl::traits::opencl_handle(partial_result).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() && <span class="keywordtype">bool</span>(<span class="stringliteral">"Operands do not reside in the same OpenCL context. Automatic migration not yet supported!"</span>));</div>
<div class="line"><a name="l00710"></a><span class="lineno"> 710</span> </div>
<div class="line"><a name="l00711"></a><span class="lineno"> 711</span>  <a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> & ctx = <span class="keyword">const_cast<</span><a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> &<span class="keyword">></span>(viennacl::traits::opencl_handle(vec).context());</div>
<div class="line"><a name="l00712"></a><span class="lineno"> 712</span>  <a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html#a803233f6aed07b9ef954c30257d7a75f">viennacl::linalg::opencl::kernels::vector<T>::init</a>(ctx);</div>
<div class="line"><a name="l00713"></a><span class="lineno"> 713</span> </div>
<div class="line"><a name="l00714"></a><span class="lineno"> 714</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a> & k = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html">viennacl::linalg::opencl::kernels::vector<T>::program_name</a>(), <span class="stringliteral">"norm"</span>);</div>
<div class="line"><a name="l00715"></a><span class="lineno"> 715</span> </div>
<div class="line"><a name="l00716"></a><span class="lineno"> 716</span>  assert( (k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#a0144c18ae9f07722e5b5697335b7cff5">global_work_size</a>() / k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>() <= partial_result.<a class="code" href="classviennacl_1_1vector__base.html#a15c47ae4326098aeaa4ed6b91fc6df9b">size</a>()) && <span class="keywordtype">bool</span>(<span class="stringliteral">"Size mismatch for partial reduction in norm_reduction_impl()"</span>) );</div>
<div class="line"><a name="l00717"></a><span class="lineno"> 717</span> </div>
<div class="line"><a name="l00718"></a><span class="lineno"> 718</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(k(viennacl::traits::opencl_handle(vec),</div>
<div class="line"><a name="l00719"></a><span class="lineno"> 719</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec)),</div>
<div class="line"><a name="l00720"></a><span class="lineno"> 720</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec)),</div>
<div class="line"><a name="l00721"></a><span class="lineno"> 721</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec)),</div>
<div class="line"><a name="l00722"></a><span class="lineno"> 722</span>  cl_uint(norm_id),</div>
<div class="line"><a name="l00723"></a><span class="lineno"> 723</span>  <a class="code" href="classviennacl_1_1ocl_1_1local__mem.html">viennacl::ocl::local_mem</a>(<span class="keyword">sizeof</span>(<span class="keyword">typename</span> <a class="code" href="structviennacl_1_1result__of_1_1cl__type.html#a340db346857782e06f4eefb3934f28c9">viennacl::result_of::cl_type<T>::type</a>) * k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>()),</div>
<div class="line"><a name="l00724"></a><span class="lineno"> 724</span>  viennacl::traits::opencl_handle(partial_result) )</div>
<div class="line"><a name="l00725"></a><span class="lineno"> 725</span>  );</div>
<div class="line"><a name="l00726"></a><span class="lineno"> 726</span> }</div>
<div class="line"><a name="l00727"></a><span class="lineno"> 727</span> </div>
<div class="line"><a name="l00728"></a><span class="lineno"> 728</span> </div>
<div class="line"><a name="l00730"></a><span class="lineno"> 730</span> </div>
<div class="line"><a name="l00736"></a><span class="lineno"> 736</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div>
<div class="line"><a name="l00737"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1opencl.html#a1ec36a29b89412455b3392fbca312a24"> 737</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#a1ec36a29b89412455b3392fbca312a24">norm_1_impl</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> <span class="keyword">const</span> & vec,</div>
<div class="line"><a name="l00738"></a><span class="lineno"> 738</span>  <a class="code" href="classviennacl_1_1scalar.html">scalar<T></a> & result)</div>
<div class="line"><a name="l00739"></a><span class="lineno"> 739</span> {</div>
<div class="line"><a name="l00740"></a><span class="lineno"> 740</span>  assert(viennacl::traits::opencl_handle(vec).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() == viennacl::traits::opencl_handle(result).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() && <span class="keywordtype">bool</span>(<span class="stringliteral">"Operands do not reside in the same OpenCL context. Automatic migration not yet supported!"</span>));</div>
<div class="line"><a name="l00741"></a><span class="lineno"> 741</span> </div>
<div class="line"><a name="l00742"></a><span class="lineno"> 742</span>  <a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> & ctx = <span class="keyword">const_cast<</span><a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> &<span class="keyword">></span>(viennacl::traits::opencl_handle(vec).context());</div>
<div class="line"><a name="l00743"></a><span class="lineno"> 743</span> </div>
<div class="line"><a name="l00744"></a><span class="lineno"> 744</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> work_groups = 128;</div>
<div class="line"><a name="l00745"></a><span class="lineno"> 745</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<T></a> temp(work_groups, <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(vec));</div>
<div class="line"><a name="l00746"></a><span class="lineno"> 746</span> </div>
<div class="line"><a name="l00747"></a><span class="lineno"> 747</span>  <span class="comment">// Step 1: Compute the partial work group results</span></div>
<div class="line"><a name="l00748"></a><span class="lineno"> 748</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#ad44f85d3504ba0dc38d734f14ec92de8">norm_reduction_impl</a>(vec, temp, 1);</div>
<div class="line"><a name="l00749"></a><span class="lineno"> 749</span> </div>
<div class="line"><a name="l00750"></a><span class="lineno"> 750</span>  <span class="comment">// Step 2: Compute the partial reduction using OpenCL</span></div>
<div class="line"><a name="l00751"></a><span class="lineno"> 751</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a> & ksum = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html">viennacl::linalg::opencl::kernels::vector<T>::program_name</a>(), <span class="stringliteral">"sum"</span>);</div>
<div class="line"><a name="l00752"></a><span class="lineno"> 752</span> </div>
<div class="line"><a name="l00753"></a><span class="lineno"> 753</span>  ksum.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#a0144c18ae9f07722e5b5697335b7cff5">global_work_size</a>(0, ksum.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>(0));</div>
<div class="line"><a name="l00754"></a><span class="lineno"> 754</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(ksum(viennacl::traits::opencl_handle(temp),</div>
<div class="line"><a name="l00755"></a><span class="lineno"> 755</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(temp)),</div>
<div class="line"><a name="l00756"></a><span class="lineno"> 756</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(temp)),</div>
<div class="line"><a name="l00757"></a><span class="lineno"> 757</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(temp)),</div>
<div class="line"><a name="l00758"></a><span class="lineno"> 758</span>  cl_uint(1),</div>
<div class="line"><a name="l00759"></a><span class="lineno"> 759</span>  <a class="code" href="classviennacl_1_1ocl_1_1local__mem.html">viennacl::ocl::local_mem</a>(<span class="keyword">sizeof</span>(<span class="keyword">typename</span> <a class="code" href="structviennacl_1_1result__of_1_1cl__type.html#a340db346857782e06f4eefb3934f28c9">viennacl::result_of::cl_type<T>::type</a>) * ksum.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>()),</div>
<div class="line"><a name="l00760"></a><span class="lineno"> 760</span>  result)</div>
<div class="line"><a name="l00761"></a><span class="lineno"> 761</span>  );</div>
<div class="line"><a name="l00762"></a><span class="lineno"> 762</span> }</div>
<div class="line"><a name="l00763"></a><span class="lineno"> 763</span> </div>
<div class="line"><a name="l00769"></a><span class="lineno"> 769</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div>
<div class="line"><a name="l00770"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1opencl.html#a61ed84aaf76cd26e36ef91598dc2f748"> 770</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#a61ed84aaf76cd26e36ef91598dc2f748">norm_1_cpu</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> <span class="keyword">const</span> & vec,</div>
<div class="line"><a name="l00771"></a><span class="lineno"> 771</span>  T & result)</div>
<div class="line"><a name="l00772"></a><span class="lineno"> 772</span> {</div>
<div class="line"><a name="l00773"></a><span class="lineno"> 773</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> work_groups = 128;</div>
<div class="line"><a name="l00774"></a><span class="lineno"> 774</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<T></a> temp(work_groups, <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(vec));</div>
<div class="line"><a name="l00775"></a><span class="lineno"> 775</span> </div>
<div class="line"><a name="l00776"></a><span class="lineno"> 776</span>  <span class="comment">// Step 1: Compute the partial work group results</span></div>
<div class="line"><a name="l00777"></a><span class="lineno"> 777</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#ad44f85d3504ba0dc38d734f14ec92de8">norm_reduction_impl</a>(vec, temp, 1);</div>
<div class="line"><a name="l00778"></a><span class="lineno"> 778</span> </div>
<div class="line"><a name="l00779"></a><span class="lineno"> 779</span>  <span class="comment">// Step 2: Now copy partial results from GPU back to CPU and run reduction there:</span></div>
<div class="line"><a name="l00780"></a><span class="lineno"> 780</span>  <span class="keyword">typedef</span> std::vector<typename viennacl::result_of::cl_type<T>::type> CPUVectorType;</div>
<div class="line"><a name="l00781"></a><span class="lineno"> 781</span> </div>
<div class="line"><a name="l00782"></a><span class="lineno"> 782</span>  CPUVectorType temp_cpu(work_groups);</div>
<div class="line"><a name="l00783"></a><span class="lineno"> 783</span>  <a class="code" href="namespaceviennacl.html#aaa5c8726b45bc89a523ca2fa8c42107a">viennacl::fast_copy</a>(temp.<a class="code" href="classviennacl_1_1vector__base.html#a762d98e2f912fc534951f25555b6077f">begin</a>(), temp.<a class="code" href="classviennacl_1_1vector__base.html#aba8a76bd4c96435ba68cf96b9e5132a6">end</a>(), temp_cpu.begin());</div>
<div class="line"><a name="l00784"></a><span class="lineno"> 784</span> </div>
<div class="line"><a name="l00785"></a><span class="lineno"> 785</span>  result = 0;</div>
<div class="line"><a name="l00786"></a><span class="lineno"> 786</span>  <span class="keywordflow">for</span> (<span class="keyword">typename</span> CPUVectorType::const_iterator it = temp_cpu.begin(); it != temp_cpu.end(); ++it)</div>
<div class="line"><a name="l00787"></a><span class="lineno"> 787</span>  result += static_cast<T>(*it);</div>
<div class="line"><a name="l00788"></a><span class="lineno"> 788</span> }</div>
<div class="line"><a name="l00789"></a><span class="lineno"> 789</span> </div>
<div class="line"><a name="l00790"></a><span class="lineno"> 790</span> </div>
<div class="line"><a name="l00791"></a><span class="lineno"> 791</span> </div>
<div class="line"><a name="l00793"></a><span class="lineno"> 793</span> </div>
<div class="line"><a name="l00794"></a><span class="lineno"> 794</span> </div>
<div class="line"><a name="l00800"></a><span class="lineno"> 800</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div>
<div class="line"><a name="l00801"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1opencl.html#a430b9424a974bdacda10b5a323976c0a"> 801</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#a430b9424a974bdacda10b5a323976c0a">norm_2_impl</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> <span class="keyword">const</span> & vec,</div>
<div class="line"><a name="l00802"></a><span class="lineno"> 802</span>  <a class="code" href="classviennacl_1_1scalar.html">scalar<T></a> & result)</div>
<div class="line"><a name="l00803"></a><span class="lineno"> 803</span> {</div>
<div class="line"><a name="l00804"></a><span class="lineno"> 804</span>  assert(viennacl::traits::opencl_handle(vec).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() == viennacl::traits::opencl_handle(result).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() && <span class="keywordtype">bool</span>(<span class="stringliteral">"Operands do not reside in the same OpenCL context. Automatic migration not yet supported!"</span>));</div>
<div class="line"><a name="l00805"></a><span class="lineno"> 805</span> </div>
<div class="line"><a name="l00806"></a><span class="lineno"> 806</span>  <a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> & ctx = <span class="keyword">const_cast<</span><a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> &<span class="keyword">></span>(viennacl::traits::opencl_handle(vec).context());</div>
<div class="line"><a name="l00807"></a><span class="lineno"> 807</span> </div>
<div class="line"><a name="l00808"></a><span class="lineno"> 808</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> work_groups = 128;</div>
<div class="line"><a name="l00809"></a><span class="lineno"> 809</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<T></a> temp(work_groups, <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(vec));</div>
<div class="line"><a name="l00810"></a><span class="lineno"> 810</span> </div>
<div class="line"><a name="l00811"></a><span class="lineno"> 811</span>  <span class="comment">// Step 1: Compute the partial work group results</span></div>
<div class="line"><a name="l00812"></a><span class="lineno"> 812</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#ad44f85d3504ba0dc38d734f14ec92de8">norm_reduction_impl</a>(vec, temp, 2);</div>
<div class="line"><a name="l00813"></a><span class="lineno"> 813</span> </div>
<div class="line"><a name="l00814"></a><span class="lineno"> 814</span>  <span class="comment">// Step 2: Reduction via OpenCL</span></div>
<div class="line"><a name="l00815"></a><span class="lineno"> 815</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a> & ksum = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html">viennacl::linalg::opencl::kernels::vector<T>::program_name</a>(), <span class="stringliteral">"sum"</span>);</div>
<div class="line"><a name="l00816"></a><span class="lineno"> 816</span> </div>
<div class="line"><a name="l00817"></a><span class="lineno"> 817</span>  ksum.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#a0144c18ae9f07722e5b5697335b7cff5">global_work_size</a>(0, ksum.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>(0));</div>
<div class="line"><a name="l00818"></a><span class="lineno"> 818</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>( ksum(viennacl::traits::opencl_handle(temp),</div>
<div class="line"><a name="l00819"></a><span class="lineno"> 819</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(temp)),</div>
<div class="line"><a name="l00820"></a><span class="lineno"> 820</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(temp)),</div>
<div class="line"><a name="l00821"></a><span class="lineno"> 821</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(temp)),</div>
<div class="line"><a name="l00822"></a><span class="lineno"> 822</span>  cl_uint(2),</div>
<div class="line"><a name="l00823"></a><span class="lineno"> 823</span>  <a class="code" href="classviennacl_1_1ocl_1_1local__mem.html">viennacl::ocl::local_mem</a>(<span class="keyword">sizeof</span>(<span class="keyword">typename</span> <a class="code" href="structviennacl_1_1result__of_1_1cl__type.html#a340db346857782e06f4eefb3934f28c9">viennacl::result_of::cl_type<T>::type</a>) * ksum.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>()),</div>
<div class="line"><a name="l00824"></a><span class="lineno"> 824</span>  result)</div>
<div class="line"><a name="l00825"></a><span class="lineno"> 825</span>  );</div>
<div class="line"><a name="l00826"></a><span class="lineno"> 826</span> }</div>
<div class="line"><a name="l00827"></a><span class="lineno"> 827</span> </div>
<div class="line"><a name="l00833"></a><span class="lineno"> 833</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div>
<div class="line"><a name="l00834"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1opencl.html#a500313611da0259aa03e288bac20eccb"> 834</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#a500313611da0259aa03e288bac20eccb">norm_2_cpu</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> <span class="keyword">const</span> & vec,</div>
<div class="line"><a name="l00835"></a><span class="lineno"> 835</span>  T & result)</div>
<div class="line"><a name="l00836"></a><span class="lineno"> 836</span> {</div>
<div class="line"><a name="l00837"></a><span class="lineno"> 837</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> work_groups = 128;</div>
<div class="line"><a name="l00838"></a><span class="lineno"> 838</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<T></a> temp(work_groups, <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(vec));</div>
<div class="line"><a name="l00839"></a><span class="lineno"> 839</span> </div>
<div class="line"><a name="l00840"></a><span class="lineno"> 840</span>  <span class="comment">// Step 1: Compute the partial work group results</span></div>
<div class="line"><a name="l00841"></a><span class="lineno"> 841</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#ad44f85d3504ba0dc38d734f14ec92de8">norm_reduction_impl</a>(vec, temp, 2);</div>
<div class="line"><a name="l00842"></a><span class="lineno"> 842</span> </div>
<div class="line"><a name="l00843"></a><span class="lineno"> 843</span>  <span class="comment">// Step 2: Now copy partial results from GPU back to CPU and run reduction there:</span></div>
<div class="line"><a name="l00844"></a><span class="lineno"> 844</span>  <span class="keyword">typedef</span> std::vector<typename viennacl::result_of::cl_type<T>::type> CPUVectorType;</div>
<div class="line"><a name="l00845"></a><span class="lineno"> 845</span> </div>
<div class="line"><a name="l00846"></a><span class="lineno"> 846</span>  CPUVectorType temp_cpu(work_groups);</div>
<div class="line"><a name="l00847"></a><span class="lineno"> 847</span>  <a class="code" href="namespaceviennacl.html#aaa5c8726b45bc89a523ca2fa8c42107a">viennacl::fast_copy</a>(temp.<a class="code" href="classviennacl_1_1vector__base.html#a762d98e2f912fc534951f25555b6077f">begin</a>(), temp.<a class="code" href="classviennacl_1_1vector__base.html#aba8a76bd4c96435ba68cf96b9e5132a6">end</a>(), temp_cpu.begin());</div>
<div class="line"><a name="l00848"></a><span class="lineno"> 848</span> </div>
<div class="line"><a name="l00849"></a><span class="lineno"> 849</span>  result = 0;</div>
<div class="line"><a name="l00850"></a><span class="lineno"> 850</span>  <span class="keywordflow">for</span> (<span class="keyword">typename</span> CPUVectorType::const_iterator it = temp_cpu.begin(); it != temp_cpu.end(); ++it)</div>
<div class="line"><a name="l00851"></a><span class="lineno"> 851</span>  result += static_cast<T>(*it);</div>
<div class="line"><a name="l00852"></a><span class="lineno"> 852</span>  result = std::sqrt(result);</div>
<div class="line"><a name="l00853"></a><span class="lineno"> 853</span> }</div>
<div class="line"><a name="l00854"></a><span class="lineno"> 854</span> </div>
<div class="line"><a name="l00855"></a><span class="lineno"> 855</span> </div>
<div class="line"><a name="l00856"></a><span class="lineno"> 856</span> </div>
<div class="line"><a name="l00858"></a><span class="lineno"> 858</span> </div>
<div class="line"><a name="l00864"></a><span class="lineno"> 864</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div>
<div class="line"><a name="l00865"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1opencl.html#a3448fa94672822135d5c8ca665543ad6"> 865</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#a3448fa94672822135d5c8ca665543ad6">norm_inf_impl</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> <span class="keyword">const</span> & vec,</div>
<div class="line"><a name="l00866"></a><span class="lineno"> 866</span>  <a class="code" href="classviennacl_1_1scalar.html">scalar<T></a> & result)</div>
<div class="line"><a name="l00867"></a><span class="lineno"> 867</span> {</div>
<div class="line"><a name="l00868"></a><span class="lineno"> 868</span>  assert(viennacl::traits::opencl_handle(vec).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() == viennacl::traits::opencl_handle(result).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() && <span class="keywordtype">bool</span>(<span class="stringliteral">"Operands do not reside in the same OpenCL context. Automatic migration not yet supported!"</span>));</div>
<div class="line"><a name="l00869"></a><span class="lineno"> 869</span> </div>
<div class="line"><a name="l00870"></a><span class="lineno"> 870</span>  <a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> & ctx = <span class="keyword">const_cast<</span><a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> &<span class="keyword">></span>(viennacl::traits::opencl_handle(vec).context());</div>
<div class="line"><a name="l00871"></a><span class="lineno"> 871</span> </div>
<div class="line"><a name="l00872"></a><span class="lineno"> 872</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> work_groups = 128;</div>
<div class="line"><a name="l00873"></a><span class="lineno"> 873</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<T></a> temp(work_groups, <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(vec));</div>
<div class="line"><a name="l00874"></a><span class="lineno"> 874</span> </div>
<div class="line"><a name="l00875"></a><span class="lineno"> 875</span>  <span class="comment">// Step 1: Compute the partial work group results</span></div>
<div class="line"><a name="l00876"></a><span class="lineno"> 876</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#ad44f85d3504ba0dc38d734f14ec92de8">norm_reduction_impl</a>(vec, temp, 0);</div>
<div class="line"><a name="l00877"></a><span class="lineno"> 877</span> </div>
<div class="line"><a name="l00878"></a><span class="lineno"> 878</span>  <span class="comment">//part 2: parallel reduction of reduced kernel:</span></div>
<div class="line"><a name="l00879"></a><span class="lineno"> 879</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a> & ksum = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html">viennacl::linalg::opencl::kernels::vector<T>::program_name</a>(), <span class="stringliteral">"sum"</span>);</div>
<div class="line"><a name="l00880"></a><span class="lineno"> 880</span> </div>
<div class="line"><a name="l00881"></a><span class="lineno"> 881</span>  ksum.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#a0144c18ae9f07722e5b5697335b7cff5">global_work_size</a>(0, ksum.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>(0));</div>
<div class="line"><a name="l00882"></a><span class="lineno"> 882</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>( ksum(viennacl::traits::opencl_handle(temp),</div>
<div class="line"><a name="l00883"></a><span class="lineno"> 883</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(temp)),</div>
<div class="line"><a name="l00884"></a><span class="lineno"> 884</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(temp)),</div>
<div class="line"><a name="l00885"></a><span class="lineno"> 885</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(temp)),</div>
<div class="line"><a name="l00886"></a><span class="lineno"> 886</span>  cl_uint(0),</div>
<div class="line"><a name="l00887"></a><span class="lineno"> 887</span>  <a class="code" href="classviennacl_1_1ocl_1_1local__mem.html">viennacl::ocl::local_mem</a>(<span class="keyword">sizeof</span>(<span class="keyword">typename</span> <a class="code" href="structviennacl_1_1result__of_1_1cl__type.html#a340db346857782e06f4eefb3934f28c9">viennacl::result_of::cl_type<T>::type</a>) * ksum.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>()),</div>
<div class="line"><a name="l00888"></a><span class="lineno"> 888</span>  result)</div>
<div class="line"><a name="l00889"></a><span class="lineno"> 889</span>  );</div>
<div class="line"><a name="l00890"></a><span class="lineno"> 890</span> }</div>
<div class="line"><a name="l00891"></a><span class="lineno"> 891</span> </div>
<div class="line"><a name="l00897"></a><span class="lineno"> 897</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div>
<div class="line"><a name="l00898"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1opencl.html#a4fad07ab525d7540817ecd9006a8bcc8"> 898</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#a4fad07ab525d7540817ecd9006a8bcc8">norm_inf_cpu</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> <span class="keyword">const</span> & vec,</div>
<div class="line"><a name="l00899"></a><span class="lineno"> 899</span>  T & result)</div>
<div class="line"><a name="l00900"></a><span class="lineno"> 900</span> {</div>
<div class="line"><a name="l00901"></a><span class="lineno"> 901</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> work_groups = 128;</div>
<div class="line"><a name="l00902"></a><span class="lineno"> 902</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<T></a> temp(work_groups, <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(vec));</div>
<div class="line"><a name="l00903"></a><span class="lineno"> 903</span> </div>
<div class="line"><a name="l00904"></a><span class="lineno"> 904</span>  <span class="comment">// Step 1: Compute the partial work group results</span></div>
<div class="line"><a name="l00905"></a><span class="lineno"> 905</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#ad44f85d3504ba0dc38d734f14ec92de8">norm_reduction_impl</a>(vec, temp, 0);</div>
<div class="line"><a name="l00906"></a><span class="lineno"> 906</span> </div>
<div class="line"><a name="l00907"></a><span class="lineno"> 907</span>  <span class="comment">// Step 2: Now copy partial results from GPU back to CPU and run reduction there:</span></div>
<div class="line"><a name="l00908"></a><span class="lineno"> 908</span>  <span class="keyword">typedef</span> std::vector<typename viennacl::result_of::cl_type<T>::type> CPUVectorType;</div>
<div class="line"><a name="l00909"></a><span class="lineno"> 909</span> </div>
<div class="line"><a name="l00910"></a><span class="lineno"> 910</span>  CPUVectorType temp_cpu(work_groups);</div>
<div class="line"><a name="l00911"></a><span class="lineno"> 911</span>  <a class="code" href="namespaceviennacl.html#aaa5c8726b45bc89a523ca2fa8c42107a">viennacl::fast_copy</a>(temp.<a class="code" href="classviennacl_1_1vector__base.html#a762d98e2f912fc534951f25555b6077f">begin</a>(), temp.<a class="code" href="classviennacl_1_1vector__base.html#aba8a76bd4c96435ba68cf96b9e5132a6">end</a>(), temp_cpu.begin());</div>
<div class="line"><a name="l00912"></a><span class="lineno"> 912</span> </div>
<div class="line"><a name="l00913"></a><span class="lineno"> 913</span>  result = 0;</div>
<div class="line"><a name="l00914"></a><span class="lineno"> 914</span>  <span class="keywordflow">for</span> (<span class="keyword">typename</span> CPUVectorType::const_iterator it = temp_cpu.begin(); it != temp_cpu.end(); ++it)</div>
<div class="line"><a name="l00915"></a><span class="lineno"> 915</span>  result = <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#a5d46fe9558b0e462f10fd44942ad4fc6">std::max</a>(result, static_cast<T>(*it));</div>
<div class="line"><a name="l00916"></a><span class="lineno"> 916</span> }</div>
<div class="line"><a name="l00917"></a><span class="lineno"> 917</span> </div>
<div class="line"><a name="l00918"></a><span class="lineno"> 918</span> </div>
<div class="line"><a name="l00920"></a><span class="lineno"> 920</span> </div>
<div class="line"><a name="l00921"></a><span class="lineno"> 921</span> <span class="comment">//This function should return a CPU scalar, otherwise statements like</span></div>
<div class="line"><a name="l00922"></a><span class="lineno"> 922</span> <span class="comment">// vcl_rhs[index_norm_inf(vcl_rhs)]</span></div>
<div class="line"><a name="l00923"></a><span class="lineno"> 923</span> <span class="comment">// are ambiguous</span></div>
<div class="line"><a name="l00929"></a><span class="lineno"> 929</span> <span class="comment"></span><span class="keyword">template</span> <<span class="keyword">typename</span> T></div>
<div class="line"><a name="l00930"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1opencl.html#ae19ed387707bd0b8721dd7acb150b2d8"> 930</a></span> cl_uint <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#ae19ed387707bd0b8721dd7acb150b2d8">index_norm_inf</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> <span class="keyword">const</span> & vec)</div>
<div class="line"><a name="l00931"></a><span class="lineno"> 931</span> {</div>
<div class="line"><a name="l00932"></a><span class="lineno"> 932</span>  <a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> & ctx = <span class="keyword">const_cast<</span><a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> &<span class="keyword">></span>(viennacl::traits::opencl_handle(vec).context());</div>
<div class="line"><a name="l00933"></a><span class="lineno"> 933</span>  <a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html#a803233f6aed07b9ef954c30257d7a75f">viennacl::linalg::opencl::kernels::vector<T>::init</a>(ctx);</div>
<div class="line"><a name="l00934"></a><span class="lineno"> 934</span> </div>
<div class="line"><a name="l00935"></a><span class="lineno"> 935</span>  <a class="code" href="classviennacl_1_1ocl_1_1handle.html">viennacl::ocl::handle<cl_mem></a> h = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#ac70d01bc7f8bd1f36c10eae811672d79">create_memory</a>(CL_MEM_READ_WRITE, <span class="keyword">sizeof</span>(cl_uint));</div>
<div class="line"><a name="l00936"></a><span class="lineno"> 936</span> </div>
<div class="line"><a name="l00937"></a><span class="lineno"> 937</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a> & k = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html">viennacl::linalg::opencl::kernels::vector<T>::program_name</a>(), <span class="stringliteral">"index_norm_inf"</span>);</div>
<div class="line"><a name="l00938"></a><span class="lineno"> 938</span>  <span class="comment">//cl_uint size = static_cast<cl_uint>(vcl_vec.internal_size());</span></div>
<div class="line"><a name="l00939"></a><span class="lineno"> 939</span> </div>
<div class="line"><a name="l00940"></a><span class="lineno"> 940</span>  <span class="comment">//TODO: Use multi-group kernel for large vector sizes</span></div>
<div class="line"><a name="l00941"></a><span class="lineno"> 941</span> </div>
<div class="line"><a name="l00942"></a><span class="lineno"> 942</span>  k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#a0144c18ae9f07722e5b5697335b7cff5">global_work_size</a>(0, k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>());</div>
<div class="line"><a name="l00943"></a><span class="lineno"> 943</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(k(viennacl::traits::opencl_handle(vec),</div>
<div class="line"><a name="l00944"></a><span class="lineno"> 944</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec)),</div>
<div class="line"><a name="l00945"></a><span class="lineno"> 945</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec)),</div>
<div class="line"><a name="l00946"></a><span class="lineno"> 946</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec)),</div>
<div class="line"><a name="l00947"></a><span class="lineno"> 947</span>  <a class="code" href="classviennacl_1_1ocl_1_1local__mem.html">viennacl::ocl::local_mem</a>(<span class="keyword">sizeof</span>(<span class="keyword">typename</span> <a class="code" href="structviennacl_1_1result__of_1_1cl__type.html#a340db346857782e06f4eefb3934f28c9">viennacl::result_of::cl_type<T>::type</a>) * k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>()),</div>
<div class="line"><a name="l00948"></a><span class="lineno"> 948</span>  <a class="code" href="classviennacl_1_1ocl_1_1local__mem.html">viennacl::ocl::local_mem</a>(<span class="keyword">sizeof</span>(cl_uint) * k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>()), h));</div>
<div class="line"><a name="l00949"></a><span class="lineno"> 949</span> </div>
<div class="line"><a name="l00950"></a><span class="lineno"> 950</span>  <span class="comment">//read value:</span></div>
<div class="line"><a name="l00951"></a><span class="lineno"> 951</span>  cl_uint result;</div>
<div class="line"><a name="l00952"></a><span class="lineno"> 952</span>  cl_int err = clEnqueueReadBuffer(ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#af4f7f70a51d069f7796bd9b4bb2a852a">get_queue</a>().<a class="code" href="classviennacl_1_1ocl_1_1command__queue.html#a670f2d080528e50d64d3912567708754">handle</a>().<a class="code" href="classviennacl_1_1ocl_1_1handle.html#a5074caaee700015fc2d3b03540b01673">get</a>(), h.<a class="code" href="classviennacl_1_1ocl_1_1handle.html#a5074caaee700015fc2d3b03540b01673">get</a>(), CL_TRUE, 0, <span class="keyword">sizeof</span>(cl_uint), &result, 0, NULL, NULL);</div>
<div class="line"><a name="l00953"></a><span class="lineno"> 953</span>  <a class="code" href="error_8hpp.html#a44f070f54255e72eb40c75ebd72ea602">VIENNACL_ERR_CHECK</a>(err);</div>
<div class="line"><a name="l00954"></a><span class="lineno"> 954</span>  <span class="keywordflow">return</span> result;</div>
<div class="line"><a name="l00955"></a><span class="lineno"> 955</span> }</div>
<div class="line"><a name="l00956"></a><span class="lineno"> 956</span> </div>
<div class="line"><a name="l00957"></a><span class="lineno"> 957</span> </div>
<div class="line"><a name="l00959"></a><span class="lineno"> 959</span> </div>
<div class="line"><a name="l00965"></a><span class="lineno"> 965</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00966"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1opencl.html#ac170765011d5fabf045d6adae0916f95"> 966</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#ac170765011d5fabf045d6adae0916f95">max_impl</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & x,</div>
<div class="line"><a name="l00967"></a><span class="lineno"> 967</span>  <a class="code" href="classviennacl_1_1scalar.html">scalar<NumericT></a> & result)</div>
<div class="line"><a name="l00968"></a><span class="lineno"> 968</span> {</div>
<div class="line"><a name="l00969"></a><span class="lineno"> 969</span>  assert(viennacl::traits::opencl_handle(x).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() == viennacl::traits::opencl_handle(result).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() && <span class="keywordtype">bool</span>(<span class="stringliteral">"Operands do not reside in the same OpenCL context. Automatic migration not yet supported!"</span>));</div>
<div class="line"><a name="l00970"></a><span class="lineno"> 970</span> </div>
<div class="line"><a name="l00971"></a><span class="lineno"> 971</span>  <a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> & ctx = <span class="keyword">const_cast<</span><a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> &<span class="keyword">></span>(viennacl::traits::opencl_handle(x).context());</div>
<div class="line"><a name="l00972"></a><span class="lineno"> 972</span>  <a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html#a803233f6aed07b9ef954c30257d7a75f">viennacl::linalg::opencl::kernels::vector<NumericT>::init</a>(ctx);</div>
<div class="line"><a name="l00973"></a><span class="lineno"> 973</span> </div>
<div class="line"><a name="l00974"></a><span class="lineno"> 974</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> work_groups = 128;</div>
<div class="line"><a name="l00975"></a><span class="lineno"> 975</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<NumericT></a> temp(work_groups, <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(x));</div>
<div class="line"><a name="l00976"></a><span class="lineno"> 976</span> </div>
<div class="line"><a name="l00977"></a><span class="lineno"> 977</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a> & k = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html">viennacl::linalg::opencl::kernels::vector<NumericT>::program_name</a>(), <span class="stringliteral">"max_kernel"</span>);</div>
<div class="line"><a name="l00978"></a><span class="lineno"> 978</span> </div>
<div class="line"><a name="l00979"></a><span class="lineno"> 979</span>  k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#a0144c18ae9f07722e5b5697335b7cff5">global_work_size</a>(0, work_groups * k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>(0));</div>
<div class="line"><a name="l00980"></a><span class="lineno"> 980</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(k(viennacl::traits::opencl_handle(x),</div>
<div class="line"><a name="l00981"></a><span class="lineno"> 981</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(x)),</div>
<div class="line"><a name="l00982"></a><span class="lineno"> 982</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(x)),</div>
<div class="line"><a name="l00983"></a><span class="lineno"> 983</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(x)),</div>
<div class="line"><a name="l00984"></a><span class="lineno"> 984</span>  <a class="code" href="classviennacl_1_1ocl_1_1local__mem.html">viennacl::ocl::local_mem</a>(<span class="keyword">sizeof</span>(<span class="keyword">typename</span> <a class="code" href="structviennacl_1_1result__of_1_1cl__type.html#a340db346857782e06f4eefb3934f28c9">viennacl::result_of::cl_type<NumericT>::type</a>) * k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>()),</div>
<div class="line"><a name="l00985"></a><span class="lineno"> 985</span>  viennacl::traits::opencl_handle(temp)</div>
<div class="line"><a name="l00986"></a><span class="lineno"> 986</span>  ));</div>
<div class="line"><a name="l00987"></a><span class="lineno"> 987</span> </div>
<div class="line"><a name="l00988"></a><span class="lineno"> 988</span>  k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#a0144c18ae9f07722e5b5697335b7cff5">global_work_size</a>(0, k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>());</div>
<div class="line"><a name="l00989"></a><span class="lineno"> 989</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(k(viennacl::traits::opencl_handle(temp),</div>
<div class="line"><a name="l00990"></a><span class="lineno"> 990</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(temp)),</div>
<div class="line"><a name="l00991"></a><span class="lineno"> 991</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(temp)),</div>
<div class="line"><a name="l00992"></a><span class="lineno"> 992</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(temp)),</div>
<div class="line"><a name="l00993"></a><span class="lineno"> 993</span>  <a class="code" href="classviennacl_1_1ocl_1_1local__mem.html">viennacl::ocl::local_mem</a>(<span class="keyword">sizeof</span>(<span class="keyword">typename</span> <a class="code" href="structviennacl_1_1result__of_1_1cl__type.html#a340db346857782e06f4eefb3934f28c9">viennacl::result_of::cl_type<NumericT>::type</a>) * k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>()),</div>
<div class="line"><a name="l00994"></a><span class="lineno"> 994</span>  viennacl::traits::opencl_handle(result)</div>
<div class="line"><a name="l00995"></a><span class="lineno"> 995</span>  ));</div>
<div class="line"><a name="l00996"></a><span class="lineno"> 996</span> }</div>
<div class="line"><a name="l00997"></a><span class="lineno"> 997</span> </div>
<div class="line"><a name="l01003"></a><span class="lineno"> 1003</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l01004"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1opencl.html#ac79bc14c508a0830434970c2cee89641"> 1004</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#ac79bc14c508a0830434970c2cee89641">max_cpu</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & x,</div>
<div class="line"><a name="l01005"></a><span class="lineno"> 1005</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> & result)</div>
<div class="line"><a name="l01006"></a><span class="lineno"> 1006</span> {</div>
<div class="line"><a name="l01007"></a><span class="lineno"> 1007</span>  <a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> & ctx = <span class="keyword">const_cast<</span><a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> &<span class="keyword">></span>(viennacl::traits::opencl_handle(x).context());</div>
<div class="line"><a name="l01008"></a><span class="lineno"> 1008</span>  <a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html#a803233f6aed07b9ef954c30257d7a75f">viennacl::linalg::opencl::kernels::vector<NumericT>::init</a>(ctx);</div>
<div class="line"><a name="l01009"></a><span class="lineno"> 1009</span> </div>
<div class="line"><a name="l01010"></a><span class="lineno"> 1010</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> work_groups = 128;</div>
<div class="line"><a name="l01011"></a><span class="lineno"> 1011</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<NumericT></a> temp(work_groups, <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(x));</div>
<div class="line"><a name="l01012"></a><span class="lineno"> 1012</span> </div>
<div class="line"><a name="l01013"></a><span class="lineno"> 1013</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a> & k = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html">viennacl::linalg::opencl::kernels::vector<NumericT>::program_name</a>(), <span class="stringliteral">"max_kernel"</span>);</div>
<div class="line"><a name="l01014"></a><span class="lineno"> 1014</span> </div>
<div class="line"><a name="l01015"></a><span class="lineno"> 1015</span>  k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#a0144c18ae9f07722e5b5697335b7cff5">global_work_size</a>(0, work_groups * k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>(0));</div>
<div class="line"><a name="l01016"></a><span class="lineno"> 1016</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(k(viennacl::traits::opencl_handle(x),</div>
<div class="line"><a name="l01017"></a><span class="lineno"> 1017</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(x)),</div>
<div class="line"><a name="l01018"></a><span class="lineno"> 1018</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(x)),</div>
<div class="line"><a name="l01019"></a><span class="lineno"> 1019</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(x)),</div>
<div class="line"><a name="l01020"></a><span class="lineno"> 1020</span>  <a class="code" href="classviennacl_1_1ocl_1_1local__mem.html">viennacl::ocl::local_mem</a>(<span class="keyword">sizeof</span>(<span class="keyword">typename</span> <a class="code" href="structviennacl_1_1result__of_1_1cl__type.html#a340db346857782e06f4eefb3934f28c9">viennacl::result_of::cl_type<NumericT>::type</a>) * k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>()),</div>
<div class="line"><a name="l01021"></a><span class="lineno"> 1021</span>  viennacl::traits::opencl_handle(temp)</div>
<div class="line"><a name="l01022"></a><span class="lineno"> 1022</span>  ));</div>
<div class="line"><a name="l01023"></a><span class="lineno"> 1023</span> </div>
<div class="line"><a name="l01024"></a><span class="lineno"> 1024</span>  <span class="comment">// Step 2: Now copy partial results from GPU back to CPU and run reduction there:</span></div>
<div class="line"><a name="l01025"></a><span class="lineno"> 1025</span>  <span class="keyword">typedef</span> std::vector<typename viennacl::result_of::cl_type<NumericT>::type> CPUVectorType;</div>
<div class="line"><a name="l01026"></a><span class="lineno"> 1026</span> </div>
<div class="line"><a name="l01027"></a><span class="lineno"> 1027</span>  CPUVectorType temp_cpu(work_groups);</div>
<div class="line"><a name="l01028"></a><span class="lineno"> 1028</span>  <a class="code" href="namespaceviennacl.html#aaa5c8726b45bc89a523ca2fa8c42107a">viennacl::fast_copy</a>(temp.<a class="code" href="classviennacl_1_1vector__base.html#a762d98e2f912fc534951f25555b6077f">begin</a>(), temp.<a class="code" href="classviennacl_1_1vector__base.html#aba8a76bd4c96435ba68cf96b9e5132a6">end</a>(), temp_cpu.begin());</div>
<div class="line"><a name="l01029"></a><span class="lineno"> 1029</span> </div>
<div class="line"><a name="l01030"></a><span class="lineno"> 1030</span>  result = <span class="keyword">static_cast<</span><a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a><span class="keyword">></span>(temp_cpu[0]);</div>
<div class="line"><a name="l01031"></a><span class="lineno"> 1031</span>  <span class="keywordflow">for</span> (<span class="keyword">typename</span> CPUVectorType::const_iterator it = temp_cpu.begin(); it != temp_cpu.end(); ++it)</div>
<div class="line"><a name="l01032"></a><span class="lineno"> 1032</span>  result = <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#a5d46fe9558b0e462f10fd44942ad4fc6">std::max</a>(result, static_cast<NumericT>(*it));</div>
<div class="line"><a name="l01033"></a><span class="lineno"> 1033</span> </div>
<div class="line"><a name="l01034"></a><span class="lineno"> 1034</span> }</div>
<div class="line"><a name="l01035"></a><span class="lineno"> 1035</span> </div>
<div class="line"><a name="l01036"></a><span class="lineno"> 1036</span> </div>
<div class="line"><a name="l01038"></a><span class="lineno"> 1038</span> </div>
<div class="line"><a name="l01044"></a><span class="lineno"> 1044</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l01045"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1opencl.html#a71a1b9f38905691db366f206dfea4bd5"> 1045</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#a71a1b9f38905691db366f206dfea4bd5">min_impl</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & x,</div>
<div class="line"><a name="l01046"></a><span class="lineno"> 1046</span>  <a class="code" href="classviennacl_1_1scalar.html">scalar<NumericT></a> & result)</div>
<div class="line"><a name="l01047"></a><span class="lineno"> 1047</span> {</div>
<div class="line"><a name="l01048"></a><span class="lineno"> 1048</span>  assert(viennacl::traits::opencl_handle(x).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() == viennacl::traits::opencl_handle(result).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() && <span class="keywordtype">bool</span>(<span class="stringliteral">"Operands do not reside in the same OpenCL context. Automatic migration not yet supported!"</span>));</div>
<div class="line"><a name="l01049"></a><span class="lineno"> 1049</span> </div>
<div class="line"><a name="l01050"></a><span class="lineno"> 1050</span>  <a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> & ctx = <span class="keyword">const_cast<</span><a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> &<span class="keyword">></span>(viennacl::traits::opencl_handle(x).context());</div>
<div class="line"><a name="l01051"></a><span class="lineno"> 1051</span>  <a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html#a803233f6aed07b9ef954c30257d7a75f">viennacl::linalg::opencl::kernels::vector<NumericT>::init</a>(ctx);</div>
<div class="line"><a name="l01052"></a><span class="lineno"> 1052</span> </div>
<div class="line"><a name="l01053"></a><span class="lineno"> 1053</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> work_groups = 128;</div>
<div class="line"><a name="l01054"></a><span class="lineno"> 1054</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<NumericT></a> temp(work_groups, <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(x));</div>
<div class="line"><a name="l01055"></a><span class="lineno"> 1055</span> </div>
<div class="line"><a name="l01056"></a><span class="lineno"> 1056</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a> & k = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html">viennacl::linalg::opencl::kernels::vector<NumericT>::program_name</a>(), <span class="stringliteral">"min_kernel"</span>);</div>
<div class="line"><a name="l01057"></a><span class="lineno"> 1057</span> </div>
<div class="line"><a name="l01058"></a><span class="lineno"> 1058</span>  k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#a0144c18ae9f07722e5b5697335b7cff5">global_work_size</a>(0, work_groups * k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>(0));</div>
<div class="line"><a name="l01059"></a><span class="lineno"> 1059</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(k(viennacl::traits::opencl_handle(x),</div>
<div class="line"><a name="l01060"></a><span class="lineno"> 1060</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(x)),</div>
<div class="line"><a name="l01061"></a><span class="lineno"> 1061</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(x)),</div>
<div class="line"><a name="l01062"></a><span class="lineno"> 1062</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(x)),</div>
<div class="line"><a name="l01063"></a><span class="lineno"> 1063</span>  <a class="code" href="classviennacl_1_1ocl_1_1local__mem.html">viennacl::ocl::local_mem</a>(<span class="keyword">sizeof</span>(<span class="keyword">typename</span> <a class="code" href="structviennacl_1_1result__of_1_1cl__type.html#a340db346857782e06f4eefb3934f28c9">viennacl::result_of::cl_type<NumericT>::type</a>) * k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>()),</div>
<div class="line"><a name="l01064"></a><span class="lineno"> 1064</span>  viennacl::traits::opencl_handle(temp)</div>
<div class="line"><a name="l01065"></a><span class="lineno"> 1065</span>  ));</div>
<div class="line"><a name="l01066"></a><span class="lineno"> 1066</span> </div>
<div class="line"><a name="l01067"></a><span class="lineno"> 1067</span>  k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#a0144c18ae9f07722e5b5697335b7cff5">global_work_size</a>(0, k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>());</div>
<div class="line"><a name="l01068"></a><span class="lineno"> 1068</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(k(viennacl::traits::opencl_handle(temp),</div>
<div class="line"><a name="l01069"></a><span class="lineno"> 1069</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(temp)),</div>
<div class="line"><a name="l01070"></a><span class="lineno"> 1070</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(temp)),</div>
<div class="line"><a name="l01071"></a><span class="lineno"> 1071</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(temp)),</div>
<div class="line"><a name="l01072"></a><span class="lineno"> 1072</span>  <a class="code" href="classviennacl_1_1ocl_1_1local__mem.html">viennacl::ocl::local_mem</a>(<span class="keyword">sizeof</span>(<span class="keyword">typename</span> <a class="code" href="structviennacl_1_1result__of_1_1cl__type.html#a340db346857782e06f4eefb3934f28c9">viennacl::result_of::cl_type<NumericT>::type</a>) * k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>()),</div>
<div class="line"><a name="l01073"></a><span class="lineno"> 1073</span>  viennacl::traits::opencl_handle(result)</div>
<div class="line"><a name="l01074"></a><span class="lineno"> 1074</span>  ));</div>
<div class="line"><a name="l01075"></a><span class="lineno"> 1075</span> }</div>
<div class="line"><a name="l01076"></a><span class="lineno"> 1076</span> </div>
<div class="line"><a name="l01082"></a><span class="lineno"> 1082</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l01083"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1opencl.html#a96c7c34e9ab708abe647c5d1eb7f6b07"> 1083</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#a96c7c34e9ab708abe647c5d1eb7f6b07">min_cpu</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & x,</div>
<div class="line"><a name="l01084"></a><span class="lineno"> 1084</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> & result)</div>
<div class="line"><a name="l01085"></a><span class="lineno"> 1085</span> {</div>
<div class="line"><a name="l01086"></a><span class="lineno"> 1086</span>  <a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> & ctx = <span class="keyword">const_cast<</span><a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> &<span class="keyword">></span>(viennacl::traits::opencl_handle(x).context());</div>
<div class="line"><a name="l01087"></a><span class="lineno"> 1087</span>  <a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html#a803233f6aed07b9ef954c30257d7a75f">viennacl::linalg::opencl::kernels::vector<NumericT>::init</a>(ctx);</div>
<div class="line"><a name="l01088"></a><span class="lineno"> 1088</span> </div>
<div class="line"><a name="l01089"></a><span class="lineno"> 1089</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> work_groups = 128;</div>
<div class="line"><a name="l01090"></a><span class="lineno"> 1090</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<NumericT></a> temp(work_groups, <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(x));</div>
<div class="line"><a name="l01091"></a><span class="lineno"> 1091</span> </div>
<div class="line"><a name="l01092"></a><span class="lineno"> 1092</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a> & k = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html">viennacl::linalg::opencl::kernels::vector<NumericT>::program_name</a>(), <span class="stringliteral">"min_kernel"</span>);</div>
<div class="line"><a name="l01093"></a><span class="lineno"> 1093</span> </div>
<div class="line"><a name="l01094"></a><span class="lineno"> 1094</span>  k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#a0144c18ae9f07722e5b5697335b7cff5">global_work_size</a>(0, work_groups * k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>(0));</div>
<div class="line"><a name="l01095"></a><span class="lineno"> 1095</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(k(viennacl::traits::opencl_handle(x),</div>
<div class="line"><a name="l01096"></a><span class="lineno"> 1096</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(x)),</div>
<div class="line"><a name="l01097"></a><span class="lineno"> 1097</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(x)),</div>
<div class="line"><a name="l01098"></a><span class="lineno"> 1098</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(x)),</div>
<div class="line"><a name="l01099"></a><span class="lineno"> 1099</span>  <a class="code" href="classviennacl_1_1ocl_1_1local__mem.html">viennacl::ocl::local_mem</a>(<span class="keyword">sizeof</span>(<span class="keyword">typename</span> <a class="code" href="structviennacl_1_1result__of_1_1cl__type.html#a340db346857782e06f4eefb3934f28c9">viennacl::result_of::cl_type<NumericT>::type</a>) * k.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>()),</div>
<div class="line"><a name="l01100"></a><span class="lineno"> 1100</span>  viennacl::traits::opencl_handle(temp)</div>
<div class="line"><a name="l01101"></a><span class="lineno"> 1101</span>  ));</div>
<div class="line"><a name="l01102"></a><span class="lineno"> 1102</span> </div>
<div class="line"><a name="l01103"></a><span class="lineno"> 1103</span>  <span class="comment">// Step 2: Now copy partial results from GPU back to CPU and run reduction there:</span></div>
<div class="line"><a name="l01104"></a><span class="lineno"> 1104</span>  <span class="keyword">typedef</span> std::vector<typename viennacl::result_of::cl_type<NumericT>::type> CPUVectorType;</div>
<div class="line"><a name="l01105"></a><span class="lineno"> 1105</span> </div>
<div class="line"><a name="l01106"></a><span class="lineno"> 1106</span>  CPUVectorType temp_cpu(work_groups);</div>
<div class="line"><a name="l01107"></a><span class="lineno"> 1107</span>  <a class="code" href="namespaceviennacl.html#aaa5c8726b45bc89a523ca2fa8c42107a">viennacl::fast_copy</a>(temp.<a class="code" href="classviennacl_1_1vector__base.html#a762d98e2f912fc534951f25555b6077f">begin</a>(), temp.<a class="code" href="classviennacl_1_1vector__base.html#aba8a76bd4c96435ba68cf96b9e5132a6">end</a>(), temp_cpu.begin());</div>
<div class="line"><a name="l01108"></a><span class="lineno"> 1108</span> </div>
<div class="line"><a name="l01109"></a><span class="lineno"> 1109</span>  result = <span class="keyword">static_cast<</span><a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a><span class="keyword">></span>(temp_cpu[0]);</div>
<div class="line"><a name="l01110"></a><span class="lineno"> 1110</span>  <span class="keywordflow">for</span> (<span class="keyword">typename</span> CPUVectorType::const_iterator it = temp_cpu.begin(); it != temp_cpu.end(); ++it)</div>
<div class="line"><a name="l01111"></a><span class="lineno"> 1111</span>  result = <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#aef015779a92be597e546c3491cebf6c1">std::min</a>(result, static_cast<NumericT>(*it));</div>
<div class="line"><a name="l01112"></a><span class="lineno"> 1112</span> }</div>
<div class="line"><a name="l01113"></a><span class="lineno"> 1113</span> </div>
<div class="line"><a name="l01115"></a><span class="lineno"> 1115</span> </div>
<div class="line"><a name="l01121"></a><span class="lineno"> 1121</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l01122"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1opencl.html#a73f87509090aaf15968741d501bdc260"> 1122</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#a73f87509090aaf15968741d501bdc260">sum_impl</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & x,</div>
<div class="line"><a name="l01123"></a><span class="lineno"> 1123</span>  <a class="code" href="classviennacl_1_1scalar.html">scalar<NumericT></a> & result)</div>
<div class="line"><a name="l01124"></a><span class="lineno"> 1124</span> {</div>
<div class="line"><a name="l01125"></a><span class="lineno"> 1125</span>  assert(viennacl::traits::opencl_handle(x).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() == viennacl::traits::opencl_handle(result).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() && <span class="keywordtype">bool</span>(<span class="stringliteral">"Operands do not reside in the same OpenCL context. Automatic migration not yet supported!"</span>));</div>
<div class="line"><a name="l01126"></a><span class="lineno"> 1126</span> </div>
<div class="line"><a name="l01127"></a><span class="lineno"> 1127</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<NumericT></a> all_ones = <a class="code" href="structviennacl_1_1scalar__vector.html">viennacl::scalar_vector<NumericT></a>(x.<a class="code" href="classviennacl_1_1vector__base.html#a15c47ae4326098aeaa4ed6b91fc6df9b">size</a>(), <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a>(1), <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(x));</div>
<div class="line"><a name="l01128"></a><span class="lineno"> 1128</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#a1adcbf3b6d428fc941484c35ce7e083a">viennacl::linalg::opencl::inner_prod_impl</a>(x, all_ones, result);</div>
<div class="line"><a name="l01129"></a><span class="lineno"> 1129</span> }</div>
<div class="line"><a name="l01130"></a><span class="lineno"> 1130</span> </div>
<div class="line"><a name="l01136"></a><span class="lineno"> 1136</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l01137"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1opencl.html#a07a0a89b0e9f73cd9f2b799e6778679b"> 1137</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#a07a0a89b0e9f73cd9f2b799e6778679b">sum_cpu</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & x, <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> & result)</div>
<div class="line"><a name="l01138"></a><span class="lineno"> 1138</span> {</div>
<div class="line"><a name="l01139"></a><span class="lineno"> 1139</span>  <a class="code" href="classviennacl_1_1scalar.html">scalar<NumericT></a> tmp(0, <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(x));</div>
<div class="line"><a name="l01140"></a><span class="lineno"> 1140</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#a73f87509090aaf15968741d501bdc260">sum_impl</a>(x, tmp);</div>
<div class="line"><a name="l01141"></a><span class="lineno"> 1141</span>  result = tmp;</div>
<div class="line"><a name="l01142"></a><span class="lineno"> 1142</span> }</div>
<div class="line"><a name="l01143"></a><span class="lineno"> 1143</span> </div>
<div class="line"><a name="l01144"></a><span class="lineno"> 1144</span> </div>
<div class="line"><a name="l01145"></a><span class="lineno"> 1145</span> <span class="comment">//TODO: Special case vec1 == vec2 allows improvement!!</span></div>
<div class="line"><a name="l01155"></a><span class="lineno"> 1155</span> <span class="comment"></span><span class="keyword">template</span> <<span class="keyword">typename</span> T></div>
<div class="line"><a name="l01156"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1opencl.html#a7cf8faf72604a859321348b7fb549420"> 1156</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#a7cf8faf72604a859321348b7fb549420">plane_rotation</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> & vec1,</div>
<div class="line"><a name="l01157"></a><span class="lineno"> 1157</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> & vec2,</div>
<div class="line"><a name="l01158"></a><span class="lineno"> 1158</span>  T alpha, T beta)</div>
<div class="line"><a name="l01159"></a><span class="lineno"> 1159</span> {</div>
<div class="line"><a name="l01160"></a><span class="lineno"> 1160</span>  assert(viennacl::traits::opencl_handle(vec1).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() == viennacl::traits::opencl_handle(vec2).<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">context</a>() && <span class="keywordtype">bool</span>(<span class="stringliteral">"Operands do not reside in the same OpenCL context. Automatic migration not yet supported!"</span>));</div>
<div class="line"><a name="l01161"></a><span class="lineno"> 1161</span> </div>
<div class="line"><a name="l01162"></a><span class="lineno"> 1162</span>  <a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> & ctx = <span class="keyword">const_cast<</span><a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> &<span class="keyword">></span>(viennacl::traits::opencl_handle(vec1).context());</div>
<div class="line"><a name="l01163"></a><span class="lineno"> 1163</span>  <a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html#a803233f6aed07b9ef954c30257d7a75f">viennacl::linalg::opencl::kernels::vector<T>::init</a>(ctx);</div>
<div class="line"><a name="l01164"></a><span class="lineno"> 1164</span> </div>
<div class="line"><a name="l01165"></a><span class="lineno"> 1165</span>  assert(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec1) == <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec2));</div>
<div class="line"><a name="l01166"></a><span class="lineno"> 1166</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a> & k = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html">viennacl::linalg::opencl::kernels::vector<T>::program_name</a>(), <span class="stringliteral">"plane_rotation"</span>);</div>
<div class="line"><a name="l01167"></a><span class="lineno"> 1167</span> </div>
<div class="line"><a name="l01168"></a><span class="lineno"> 1168</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(k(viennacl::traits::opencl_handle(vec1),</div>
<div class="line"><a name="l01169"></a><span class="lineno"> 1169</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec1)),</div>
<div class="line"><a name="l01170"></a><span class="lineno"> 1170</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec1)),</div>
<div class="line"><a name="l01171"></a><span class="lineno"> 1171</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec1)),</div>
<div class="line"><a name="l01172"></a><span class="lineno"> 1172</span>  viennacl::traits::opencl_handle(vec2),</div>
<div class="line"><a name="l01173"></a><span class="lineno"> 1173</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec2)),</div>
<div class="line"><a name="l01174"></a><span class="lineno"> 1174</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec2)),</div>
<div class="line"><a name="l01175"></a><span class="lineno"> 1175</span>  cl_uint(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec2)),</div>
<div class="line"><a name="l01176"></a><span class="lineno"> 1176</span>  viennacl::traits::opencl_handle(alpha),</div>
<div class="line"><a name="l01177"></a><span class="lineno"> 1177</span>  viennacl::traits::opencl_handle(beta))</div>
<div class="line"><a name="l01178"></a><span class="lineno"> 1178</span>  );</div>
<div class="line"><a name="l01179"></a><span class="lineno"> 1179</span> }</div>
<div class="line"><a name="l01180"></a><span class="lineno"> 1180</span> </div>
<div class="line"><a name="l01181"></a><span class="lineno"> 1181</span> </div>
<div class="line"><a name="l01183"></a><span class="lineno"> 1183</span> </div>
<div class="line"><a name="l01184"></a><span class="lineno"> 1184</span> </div>
<div class="line"><a name="l01185"></a><span class="lineno"> 1185</span> <span class="keyword">namespace </span>detail</div>
<div class="line"><a name="l01186"></a><span class="lineno"> 1186</span> {</div>
<div class="line"><a name="l01192"></a><span class="lineno"> 1192</span>  <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l01193"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a9900a6b53663c061cac19d0e125fe461"> 1193</a></span>  <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a9900a6b53663c061cac19d0e125fe461">scan_impl</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & input,</div>
<div class="line"><a name="l01194"></a><span class="lineno"> 1194</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & output,</div>
<div class="line"><a name="l01195"></a><span class="lineno"> 1195</span>  <span class="keywordtype">bool</span> is_inclusive)</div>
<div class="line"><a name="l01196"></a><span class="lineno"> 1196</span>  {</div>
<div class="line"><a name="l01197"></a><span class="lineno"> 1197</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> local_worksize = 128;</div>
<div class="line"><a name="l01198"></a><span class="lineno"> 1198</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> workgroups = 128;</div>
<div class="line"><a name="l01199"></a><span class="lineno"> 1199</span> </div>
<div class="line"><a name="l01200"></a><span class="lineno"> 1200</span>  <a class="code" href="classviennacl_1_1backend_1_1mem__handle.html">viennacl::backend::mem_handle</a> opencl_carries;</div>
<div class="line"><a name="l01201"></a><span class="lineno"> 1201</span>  <a class="code" href="namespaceviennacl_1_1backend.html#a1499f19634964e2c7c8aeeefc6206126">viennacl::backend::memory_create</a>(opencl_carries, <span class="keyword">sizeof</span>(<a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a>)*workgroups, <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(input));</div>
<div class="line"><a name="l01202"></a><span class="lineno"> 1202</span> </div>
<div class="line"><a name="l01203"></a><span class="lineno"> 1203</span>  <a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> & ctx = <span class="keyword">const_cast<</span><a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> &<span class="keyword">></span>(viennacl::traits::opencl_handle(input).context());</div>
<div class="line"><a name="l01204"></a><span class="lineno"> 1204</span>  <a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1scan.html#a6e3e5e19bedf8150c466ba799960d6bb">viennacl::linalg::opencl::kernels::scan<NumericT>::init</a>(ctx);</div>
<div class="line"><a name="l01205"></a><span class="lineno"> 1205</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a>& k1 = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1scan.html">viennacl::linalg::opencl::kernels::scan<NumericT>::program_name</a>(), <span class="stringliteral">"scan_1"</span>);</div>
<div class="line"><a name="l01206"></a><span class="lineno"> 1206</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a>& k2 = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1scan.html">viennacl::linalg::opencl::kernels::scan<NumericT>::program_name</a>(), <span class="stringliteral">"scan_2"</span>);</div>
<div class="line"><a name="l01207"></a><span class="lineno"> 1207</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a>& k3 = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1scan.html">viennacl::linalg::opencl::kernels::scan<NumericT>::program_name</a>(), <span class="stringliteral">"scan_3"</span>);</div>
<div class="line"><a name="l01208"></a><span class="lineno"> 1208</span> </div>
<div class="line"><a name="l01209"></a><span class="lineno"> 1209</span>  <span class="comment">// First step: Scan within each thread group and write carries</span></div>
<div class="line"><a name="l01210"></a><span class="lineno"> 1210</span>  k1.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>(0, local_worksize);</div>
<div class="line"><a name="l01211"></a><span class="lineno"> 1211</span>  k1.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#a0144c18ae9f07722e5b5697335b7cff5">global_work_size</a>(0, workgroups * local_worksize);</div>
<div class="line"><a name="l01212"></a><span class="lineno"> 1212</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(k1( input, cl_uint( input.<a class="code" href="classviennacl_1_1vector__base.html#aaabd2cd126b77ee09b80b4c447bcbd3e">start</a>()), cl_uint( input.<a class="code" href="classviennacl_1_1vector__base.html#af1e0bd20ec7254908f6d49df07785cf4">stride</a>()), cl_uint(input.<a class="code" href="classviennacl_1_1vector__base.html#a15c47ae4326098aeaa4ed6b91fc6df9b">size</a>()),</div>
<div class="line"><a name="l01213"></a><span class="lineno"> 1213</span>  output, cl_uint(output.<a class="code" href="classviennacl_1_1vector__base.html#aaabd2cd126b77ee09b80b4c447bcbd3e">start</a>()), cl_uint(output.<a class="code" href="classviennacl_1_1vector__base.html#af1e0bd20ec7254908f6d49df07785cf4">stride</a>()),</div>
<div class="line"><a name="l01214"></a><span class="lineno"> 1214</span>  cl_uint(is_inclusive ? 0 : 1), opencl_carries.opencl_handle())</div>
<div class="line"><a name="l01215"></a><span class="lineno"> 1215</span>  );</div>
<div class="line"><a name="l01216"></a><span class="lineno"> 1216</span> </div>
<div class="line"><a name="l01217"></a><span class="lineno"> 1217</span>  <span class="comment">// Second step: Compute offset for each thread group (exclusive scan for each thread group)</span></div>
<div class="line"><a name="l01218"></a><span class="lineno"> 1218</span>  k2.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>(0, workgroups);</div>
<div class="line"><a name="l01219"></a><span class="lineno"> 1219</span>  k2.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#a0144c18ae9f07722e5b5697335b7cff5">global_work_size</a>(0, workgroups);</div>
<div class="line"><a name="l01220"></a><span class="lineno"> 1220</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(k2(opencl_carries.opencl_handle()));</div>
<div class="line"><a name="l01221"></a><span class="lineno"> 1221</span> </div>
<div class="line"><a name="l01222"></a><span class="lineno"> 1222</span>  <span class="comment">// Third step: Offset each thread group accordingly</span></div>
<div class="line"><a name="l01223"></a><span class="lineno"> 1223</span>  k3.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>(0, local_worksize);</div>
<div class="line"><a name="l01224"></a><span class="lineno"> 1224</span>  k3.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#a0144c18ae9f07722e5b5697335b7cff5">global_work_size</a>(0, workgroups * local_worksize);</div>
<div class="line"><a name="l01225"></a><span class="lineno"> 1225</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(k3(output, cl_uint(output.<a class="code" href="classviennacl_1_1vector__base.html#aaabd2cd126b77ee09b80b4c447bcbd3e">start</a>()), cl_uint(output.<a class="code" href="classviennacl_1_1vector__base.html#af1e0bd20ec7254908f6d49df07785cf4">stride</a>()), cl_uint(output.<a class="code" href="classviennacl_1_1vector__base.html#a15c47ae4326098aeaa4ed6b91fc6df9b">size</a>()),</div>
<div class="line"><a name="l01226"></a><span class="lineno"> 1226</span>  opencl_carries.opencl_handle())</div>
<div class="line"><a name="l01227"></a><span class="lineno"> 1227</span>  );</div>
<div class="line"><a name="l01228"></a><span class="lineno"> 1228</span>  }</div>
<div class="line"><a name="l01229"></a><span class="lineno"> 1229</span> }</div>
<div class="line"><a name="l01230"></a><span class="lineno"> 1230</span> </div>
<div class="line"><a name="l01231"></a><span class="lineno"> 1231</span> </div>
<div class="line"><a name="l01237"></a><span class="lineno"> 1237</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l01238"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1opencl.html#a89a844a138804369fef44a01653e85b3"> 1238</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#a89a844a138804369fef44a01653e85b3">inclusive_scan</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & input,</div>
<div class="line"><a name="l01239"></a><span class="lineno"> 1239</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & output)</div>
<div class="line"><a name="l01240"></a><span class="lineno"> 1240</span> {</div>
<div class="line"><a name="l01241"></a><span class="lineno"> 1241</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a9900a6b53663c061cac19d0e125fe461">detail::scan_impl</a>(input, output, <span class="keyword">true</span>);</div>
<div class="line"><a name="l01242"></a><span class="lineno"> 1242</span> }</div>
<div class="line"><a name="l01243"></a><span class="lineno"> 1243</span> </div>
<div class="line"><a name="l01244"></a><span class="lineno"> 1244</span> </div>
<div class="line"><a name="l01250"></a><span class="lineno"> 1250</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l01251"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1opencl.html#a2ab3c5aa6788fe5dce609753f8c038f7"> 1251</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#a2ab3c5aa6788fe5dce609753f8c038f7">exclusive_scan</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & input,</div>
<div class="line"><a name="l01252"></a><span class="lineno"> 1252</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & output)</div>
<div class="line"><a name="l01253"></a><span class="lineno"> 1253</span> {</div>
<div class="line"><a name="l01254"></a><span class="lineno"> 1254</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a9900a6b53663c061cac19d0e125fe461">detail::scan_impl</a>(input, output, <span class="keyword">false</span>);</div>
<div class="line"><a name="l01255"></a><span class="lineno"> 1255</span> }</div>
<div class="line"><a name="l01256"></a><span class="lineno"> 1256</span> </div>
<div class="line"><a name="l01257"></a><span class="lineno"> 1257</span> </div>
<div class="line"><a name="l01258"></a><span class="lineno"> 1258</span> } <span class="comment">//namespace opencl</span></div>
<div class="line"><a name="l01259"></a><span class="lineno"> 1259</span> } <span class="comment">//namespace linalg</span></div>
<div class="line"><a name="l01260"></a><span class="lineno"> 1260</span> } <span class="comment">//namespace viennacl</span></div>
<div class="line"><a name="l01261"></a><span class="lineno"> 1261</span> </div>
<div class="line"><a name="l01262"></a><span class="lineno"> 1262</span> </div>
<div class="line"><a name="l01263"></a><span class="lineno"> 1263</span> <span class="preprocessor">#endif</span></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1opencl_html_a96c7c34e9ab708abe647c5d1eb7f6b07"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1opencl.html#a96c7c34e9ab708abe647c5d1eb7f6b07">viennacl::linalg::opencl::min_cpu</a></div><div class="ttdeci">void min_cpu(vector_base< NumericT > const &x, NumericT &result)</div><div class="ttdoc">Computes the minimum of a vector, where the result is stored on a CPU scalar. </div><div class="ttdef"><b>Definition:</b> <a href="opencl_2vector__operations_8hpp_source.html#l01083">vector_operations.hpp:1083</a></div></div>
<div class="ttc" id="structviennacl_1_1ocl_1_1packed__cl__uint_html_a457e1f554ae439501613c843b6dad189"><div class="ttname"><a href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a457e1f554ae439501613c843b6dad189">viennacl::ocl::packed_cl_uint::stride</a></div><div class="ttdeci">cl_uint stride</div><div class="ttdoc">Increment between integers. </div><div class="ttdef"><b>Definition:</b> <a href="kernel_8hpp_source.html#l00050">kernel.hpp:50</a></div></div>
<div class="ttc" id="classviennacl_1_1vector__tuple_html_a9f2fc8200f0199e396eaeca310f8e9f4"><div class="ttname"><a href="classviennacl_1_1vector__tuple.html#a9f2fc8200f0199e396eaeca310f8e9f4">viennacl::vector_tuple::const_size</a></div><div class="ttdeci">vcl_size_t const_size() const </div><div class="ttdef"><b>Definition:</b> <a href="vector_8hpp_source.html#l01143">vector.hpp:1143</a></div></div>
<div class="ttc" id="structviennacl_1_1ocl_1_1packed__cl__uint_html"><div class="ttname"><a href="structviennacl_1_1ocl_1_1packed__cl__uint.html">viennacl::ocl::packed_cl_uint</a></div><div class="ttdoc">Helper class for packing four cl_uint numbers into a uint4 type for access inside an OpenCL kernel...</div><div class="ttdef"><b>Definition:</b> <a href="kernel_8hpp_source.html#l00045">kernel.hpp:45</a></div></div>
<div class="ttc" id="classviennacl_1_1scalar_html"><div class="ttname"><a href="classviennacl_1_1scalar.html">viennacl::scalar</a></div><div class="ttdoc">This class represents a single scalar value on the GPU and behaves mostly like a built-in scalar type...</div><div class="ttdef"><b>Definition:</b> <a href="forwards_8h_source.html#l00227">forwards.h:227</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1opencl_html_ad22775c47f41c305da21168d1cb92236"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1opencl.html#ad22775c47f41c305da21168d1cb92236">viennacl::linalg::opencl::avbv</a></div><div class="ttdeci">void avbv(vector_base< T > &vec1, vector_base< T > const &vec2, ScalarType1 const &alpha, vcl_size_t len_alpha, bool reciprocal_alpha, bool flip_sign_alpha, vector_base< T > const &vec3, ScalarType2 const &beta, vcl_size_t len_beta, bool reciprocal_beta, bool flip_sign_beta)</div><div class="ttdef"><b>Definition:</b> <a href="opencl_2vector__operations_8hpp_source.html#l00116">vector_operations.hpp:116</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1opencl_html_a430b9424a974bdacda10b5a323976c0a"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1opencl.html#a430b9424a974bdacda10b5a323976c0a">viennacl::linalg::opencl::norm_2_impl</a></div><div class="ttdeci">void norm_2_impl(vector_base< T > const &vec, scalar< T > &result)</div><div class="ttdoc">Computes the l^2-norm of a vector - implementation using OpenCL summation at second step...</div><div class="ttdef"><b>Definition:</b> <a href="opencl_2vector__operations_8hpp_source.html#l00801">vector_operations.hpp:801</a></div></div>
<div class="ttc" id="device_8hpp_html"><div class="ttname"><a href="device_8hpp.html">device.hpp</a></div><div class="ttdoc">Represents an OpenCL device within ViennaCL. </div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1opencl_html_a61ed84aaf76cd26e36ef91598dc2f748"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1opencl.html#a61ed84aaf76cd26e36ef91598dc2f748">viennacl::linalg::opencl::norm_1_cpu</a></div><div class="ttdeci">void norm_1_cpu(vector_base< T > const &vec, T &result)</div><div class="ttdoc">Computes the l^1-norm of a vector with final reduction on CPU. </div><div class="ttdef"><b>Definition:</b> <a href="opencl_2vector__operations_8hpp_source.html#l00770">vector_operations.hpp:770</a></div></div>
<div class="ttc" id="size_8hpp_html"><div class="ttname"><a href="size_8hpp.html">size.hpp</a></div><div class="ttdoc">Generic size and resize functionality for different vector and matrix types. </div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1opencl_html_a7cf8faf72604a859321348b7fb549420"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1opencl.html#a7cf8faf72604a859321348b7fb549420">viennacl::linalg::opencl::plane_rotation</a></div><div class="ttdeci">void plane_rotation(vector_base< T > &vec1, vector_base< T > &vec2, T alpha, T beta)</div><div class="ttdoc">Computes a plane rotation of two vectors. </div><div class="ttdef"><b>Definition:</b> <a href="opencl_2vector__operations_8hpp_source.html#l01156">vector_operations.hpp:1156</a></div></div>
<div class="ttc" id="classviennacl_1_1ocl_1_1context_html_af4f7f70a51d069f7796bd9b4bb2a852a"><div class="ttname"><a href="classviennacl_1_1ocl_1_1context.html#af4f7f70a51d069f7796bd9b4bb2a852a">viennacl::ocl::context::get_queue</a></div><div class="ttdeci">viennacl::ocl::command_queue & get_queue()</div><div class="ttdef"><b>Definition:</b> <a href="ocl_2context_8hpp_source.html#l00266">context.hpp:266</a></div></div>
<div class="ttc" id="classviennacl_1_1ocl_1_1kernel_html"><div class="ttname"><a href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a></div><div class="ttdoc">Represents an OpenCL kernel within ViennaCL. </div><div class="ttdef"><b>Definition:</b> <a href="kernel_8hpp_source.html#l00058">kernel.hpp:58</a></div></div>
<div class="ttc" id="start_8hpp_html"><div class="ttname"><a href="start_8hpp.html">start.hpp</a></div><div class="ttdoc">Extracts the underlying OpenCL start index handle from a vector, a matrix, an expression etc...</div></div>
<div class="ttc" id="structviennacl_1_1ocl_1_1packed__cl__uint_html_a7991987e7676fabb8d1cbc54eaa0ba01"><div class="ttname"><a href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a7991987e7676fabb8d1cbc54eaa0ba01">viennacl::ocl::packed_cl_uint::start</a></div><div class="ttdeci">cl_uint start</div><div class="ttdoc">Starting value of the integer stride. </div><div class="ttdef"><b>Definition:</b> <a href="kernel_8hpp_source.html#l00048">kernel.hpp:48</a></div></div>
<div class="ttc" id="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector__convert_html_aa9b325a3e08a54c231d0aaa17f9162f4"><div class="ttname"><a href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector__convert.html#aa9b325a3e08a54c231d0aaa17f9162f4">viennacl::linalg::opencl::kernels::vector_convert::program_name</a></div><div class="ttdeci">static std::string program_name()</div><div class="ttdef"><b>Definition:</b> <a href="linalg_2opencl_2kernels_2vector_8hpp_source.html#l00784">vector.hpp:784</a></div></div>
<div class="ttc" id="tools_8hpp_html"><div class="ttname"><a href="tools_8hpp.html">tools.hpp</a></div><div class="ttdoc">Various little tools used here and there in ViennaCL. </div></div>
<div class="ttc" id="classviennacl_1_1ocl_1_1kernel_html_ae2b841c487f9ddbfcfb6297d648e2d7f"><div class="ttname"><a href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">viennacl::ocl::kernel::local_work_size</a></div><div class="ttdeci">size_type local_work_size(int index=0) const </div><div class="ttdoc">Returns the local work size at the respective dimension. </div><div class="ttdef"><b>Definition:</b> <a href="kernel_8hpp_source.html#l00742">kernel.hpp:742</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1opencl_html_ad44f85d3504ba0dc38d734f14ec92de8"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1opencl.html#ad44f85d3504ba0dc38d734f14ec92de8">viennacl::linalg::opencl::norm_reduction_impl</a></div><div class="ttdeci">void norm_reduction_impl(vector_base< T > const &vec, vector_base< T > &partial_result, cl_uint norm_id)</div><div class="ttdoc">Computes the partial work group results for vector norms. </div><div class="ttdef"><b>Definition:</b> <a href="opencl_2vector__operations_8hpp_source.html#l00705">vector_operations.hpp:705</a></div></div>
<div class="ttc" id="classviennacl_1_1ocl_1_1context_html"><div class="ttname"><a href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a></div><div class="ttdoc">Manages an OpenCL context and provides the respective convenience functions for creating buffers...</div><div class="ttdef"><b>Definition:</b> <a href="ocl_2context_8hpp_source.html#l00055">context.hpp:55</a></div></div>
<div class="ttc" id="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector__multi__inner__prod_html"><div class="ttname"><a href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector__multi__inner__prod.html">viennacl::linalg::opencl::kernels::vector_multi_inner_prod</a></div><div class="ttdoc">Main kernel class for generating OpenCL kernels for multiple inner products on/with viennacl::vector<...</div><div class="ttdef"><b>Definition:</b> <a href="linalg_2opencl_2kernels_2vector_8hpp_source.html#l00727">vector.hpp:727</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1opencl_html_a3448fa94672822135d5c8ca665543ad6"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1opencl.html#a3448fa94672822135d5c8ca665543ad6">viennacl::linalg::opencl::norm_inf_impl</a></div><div class="ttdeci">void norm_inf_impl(vector_base< T > const &vec, scalar< T > &result)</div><div class="ttdoc">Computes the supremum-norm of a vector. </div><div class="ttdef"><b>Definition:</b> <a href="opencl_2vector__operations_8hpp_source.html#l00865">vector_operations.hpp:865</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1traits_html_a09997870f4802fa5d4ac2c43cf4020d1"><div class="ttname"><a href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a></div><div class="ttdeci">result_of::size_type< viennacl::vector_base< T > >::type stride(viennacl::vector_base< T > const &s)</div><div class="ttdef"><b>Definition:</b> <a href="stride_8hpp_source.html#l00045">stride.hpp:45</a></div></div>
<div class="ttc" id="forwards_8h_html"><div class="ttname"><a href="forwards_8h.html">forwards.h</a></div><div class="ttdoc">This file provides the forward declarations for the main types used within ViennaCL. </div></div>
<div class="ttc" id="stride_8hpp_html"><div class="ttname"><a href="stride_8hpp.html">stride.hpp</a></div><div class="ttdoc">Determines row and column increments for matrices and matrix proxies. </div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1opencl_html_a71a1b9f38905691db366f206dfea4bd5"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1opencl.html#a71a1b9f38905691db366f206dfea4bd5">viennacl::linalg::opencl::min_impl</a></div><div class="ttdeci">void min_impl(vector_base< NumericT > const &x, scalar< NumericT > &result)</div><div class="ttdoc">Computes the minimum of a vector, where the result is stored in an OpenCL buffer. ...</div><div class="ttdef"><b>Definition:</b> <a href="opencl_2vector__operations_8hpp_source.html#l01045">vector_operations.hpp:1045</a></div></div>
<div class="ttc" id="structviennacl_1_1result__of_1_1cl__type_html_a340db346857782e06f4eefb3934f28c9"><div class="ttname"><a href="structviennacl_1_1result__of_1_1cl__type.html#a340db346857782e06f4eefb3934f28c9">viennacl::result_of::cl_type::type</a></div><div class="ttdeci">T type</div><div class="ttdef"><b>Definition:</b> <a href="result__of_8hpp_source.html#l00590">result_of.hpp:590</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1traits_html_a0cd530f8a76a5fb3d60a9230bea30bca"><div class="ttname"><a href="namespaceviennacl_1_1traits.html#a0cd530f8a76a5fb3d60a9230bea30bca">viennacl::traits::internal_size</a></div><div class="ttdeci">vcl_size_t internal_size(vector_base< NumericT > const &vec)</div><div class="ttdoc">Helper routine for obtaining the buffer length of a ViennaCL vector. </div><div class="ttdef"><b>Definition:</b> <a href="size_8hpp_source.html#l00375">size.hpp:375</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1detail_html_a5d46fe9558b0e462f10fd44942ad4fc6"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1detail.html#a5d46fe9558b0e462f10fd44942ad4fc6">viennacl::linalg::detail::max</a></div><div class="ttdeci">T max(const T &lhs, const T &rhs)</div><div class="ttdoc">Maximum. </div><div class="ttdef"><b>Definition:</b> <a href="linalg_2detail_2bisect_2util_8hpp_source.html#l00059">util.hpp:59</a></div></div>
<div class="ttc" id="classviennacl_1_1vector__expression_html"><div class="ttname"><a href="classviennacl_1_1vector__expression.html">viennacl::vector_expression</a></div><div class="ttdoc">An expression template class that represents a binary operation that yields a vector. </div><div class="ttdef"><b>Definition:</b> <a href="forwards_8h_source.html#l00239">forwards.h:239</a></div></div>
<div class="ttc" id="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1scan_html_a6e3e5e19bedf8150c466ba799960d6bb"><div class="ttname"><a href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1scan.html#a6e3e5e19bedf8150c466ba799960d6bb">viennacl::linalg::opencl::kernels::scan::init</a></div><div class="ttdeci">static void init(viennacl::ocl::context &ctx)</div><div class="ttdef"><b>Definition:</b> <a href="scan_8hpp_source.html#l00162">scan.hpp:162</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1opencl_html_a3acee3fef422c2c2abee2f4e1d67c350"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1opencl.html#a3acee3fef422c2c2abee2f4e1d67c350">viennacl::linalg::opencl::avbv_v</a></div><div class="ttdeci">void avbv_v(vector_base< T > &vec1, vector_base< T > const &vec2, ScalarType1 const &alpha, vcl_size_t len_alpha, bool reciprocal_alpha, bool flip_sign_alpha, vector_base< T > const &vec3, ScalarType2 const &beta, vcl_size_t len_beta, bool reciprocal_beta, bool flip_sign_beta)</div><div class="ttdef"><b>Definition:</b> <a href="opencl_2vector__operations_8hpp_source.html#l00178">vector_operations.hpp:178</a></div></div>
<div class="ttc" id="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1scan_html"><div class="ttname"><a href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1scan.html">viennacl::linalg::opencl::kernels::scan</a></div><div class="ttdoc">Main kernel class for generating OpenCL kernels for singular value decomposition of dense matrices...</div><div class="ttdef"><b>Definition:</b> <a href="scan_8hpp_source.html#l00155">scan.hpp:155</a></div></div>
<div class="ttc" id="structviennacl_1_1ocl_1_1packed__cl__uint_html_ab4fed39d6fdda2db5bcb5ec29c2537d0"><div class="ttname"><a href="structviennacl_1_1ocl_1_1packed__cl__uint.html#ab4fed39d6fdda2db5bcb5ec29c2537d0">viennacl::ocl::packed_cl_uint::internal_size</a></div><div class="ttdeci">cl_uint internal_size</div><div class="ttdoc">Internal length of the buffer. Might be larger than 'size' due to padding. </div><div class="ttdef"><b>Definition:</b> <a href="kernel_8hpp_source.html#l00054">kernel.hpp:54</a></div></div>
<div class="ttc" id="linalg_2opencl_2common_8hpp_html"><div class="ttname"><a href="linalg_2opencl_2common_8hpp.html">common.hpp</a></div><div class="ttdoc">Common implementations shared by OpenCL-based operations. </div></div>
<div class="ttc" id="classviennacl_1_1ocl_1_1command__queue_html_a670f2d080528e50d64d3912567708754"><div class="ttname"><a href="classviennacl_1_1ocl_1_1command__queue.html#a670f2d080528e50d64d3912567708754">viennacl::ocl::command_queue::handle</a></div><div class="ttdeci">viennacl::ocl::handle< cl_command_queue > const & handle() const </div><div class="ttdef"><b>Definition:</b> <a href="command__queue_8hpp_source.html#l00081">command_queue.hpp:81</a></div></div>
<div class="ttc" id="tests_2src_2bisect_8cpp_html_a52b5d30a2d7b064678644a3bf49b7f6c"><div class="ttname"><a href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a></div><div class="ttdeci">float NumericT</div><div class="ttdef"><b>Definition:</b> <a href="tests_2src_2bisect_8cpp_source.html#l00040">bisect.cpp:40</a></div></div>
<div class="ttc" id="classviennacl_1_1vector__base_html_af1e0bd20ec7254908f6d49df07785cf4"><div class="ttname"><a href="classviennacl_1_1vector__base.html#af1e0bd20ec7254908f6d49df07785cf4">viennacl::vector_base::stride</a></div><div class="ttdeci">size_type stride() const </div><div class="ttdoc">Returns the stride within the buffer (in multiples of sizeof(NumericT)) </div><div class="ttdef"><b>Definition:</b> <a href="vector__def_8hpp_source.html#l00124">vector_def.hpp:124</a></div></div>
<div class="ttc" id="error_8hpp_html_a44f070f54255e72eb40c75ebd72ea602"><div class="ttname"><a href="error_8hpp.html#a44f070f54255e72eb40c75ebd72ea602">VIENNACL_ERR_CHECK</a></div><div class="ttdeci">#define VIENNACL_ERR_CHECK(err)</div><div class="ttdef"><b>Definition:</b> <a href="error_8hpp_source.html#l00681">error.hpp:681</a></div></div>
<div class="ttc" id="classviennacl_1_1ocl_1_1handle_html_a5074caaee700015fc2d3b03540b01673"><div class="ttname"><a href="classviennacl_1_1ocl_1_1handle.html#a5074caaee700015fc2d3b03540b01673">viennacl::ocl::handle::get</a></div><div class="ttdeci">const OCL_TYPE & get() const </div><div class="ttdef"><b>Definition:</b> <a href="ocl_2handle_8hpp_source.html#l00191">handle.hpp:191</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1opencl_html_a1adcbf3b6d428fc941484c35ce7e083a"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1opencl.html#a1adcbf3b6d428fc941484c35ce7e083a">viennacl::linalg::opencl::inner_prod_impl</a></div><div class="ttdeci">void inner_prod_impl(vector_base< T > const &vec1, vector_base< T > const &vec2, vector_base< T > &partial_result)</div><div class="ttdoc">Computes the partial inner product of two vectors - implementation. Library users should call inner_p...</div><div class="ttdef"><b>Definition:</b> <a href="opencl_2vector__operations_8hpp_source.html#l00388">vector_operations.hpp:388</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1traits_html_aa2344ea20469f55fbc15a8e9526494d0"><div class="ttname"><a href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a></div><div class="ttdeci">vcl_size_t size(VectorType const &vec)</div><div class="ttdoc">Generic routine for obtaining the size of a vector (ViennaCL, uBLAS, etc.) </div><div class="ttdef"><b>Definition:</b> <a href="size_8hpp_source.html#l00239">size.hpp:239</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1opencl_html_a73f87509090aaf15968741d501bdc260"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1opencl.html#a73f87509090aaf15968741d501bdc260">viennacl::linalg::opencl::sum_impl</a></div><div class="ttdeci">void sum_impl(vector_base< NumericT > const &x, scalar< NumericT > &result)</div><div class="ttdoc">Computes the sum over all entries of a vector. </div><div class="ttdef"><b>Definition:</b> <a href="opencl_2vector__operations_8hpp_source.html#l01122">vector_operations.hpp:1122</a></div></div>
<div class="ttc" id="classviennacl_1_1ocl_1_1local__mem_html"><div class="ttname"><a href="classviennacl_1_1ocl_1_1local__mem.html">viennacl::ocl::local_mem</a></div><div class="ttdoc">A class representing local (shared) OpenCL memory. Typically used as kernel argument. </div><div class="ttdef"><b>Definition:</b> <a href="local__mem_8hpp_source.html#l00033">local_mem.hpp:33</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1opencl_html_ac170765011d5fabf045d6adae0916f95"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1opencl.html#ac170765011d5fabf045d6adae0916f95">viennacl::linalg::opencl::max_impl</a></div><div class="ttdeci">void max_impl(vector_base< NumericT > const &x, scalar< NumericT > &result)</div><div class="ttdoc">Computes the maximum value of a vector, where the result is stored in an OpenCL buffer. </div><div class="ttdef"><b>Definition:</b> <a href="opencl_2vector__operations_8hpp_source.html#l00966">vector_operations.hpp:966</a></div></div>
<div class="ttc" id="structviennacl_1_1is__cpu__scalar_html"><div class="ttname"><a href="structviennacl_1_1is__cpu__scalar.html">viennacl::is_cpu_scalar</a></div><div class="ttdoc">Helper struct for checking whether a type is a host scalar type (e.g. float, double) ...</div><div class="ttdef"><b>Definition:</b> <a href="forwards_8h_source.html#l00448">forwards.h:448</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1opencl_html_ac79bc14c508a0830434970c2cee89641"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1opencl.html#ac79bc14c508a0830434970c2cee89641">viennacl::linalg::opencl::max_cpu</a></div><div class="ttdeci">void max_cpu(vector_base< NumericT > const &x, NumericT &result)</div><div class="ttdoc">Computes the maximum value of a vector, where the value is stored in a host value. </div><div class="ttdef"><b>Definition:</b> <a href="opencl_2vector__operations_8hpp_source.html#l01004">vector_operations.hpp:1004</a></div></div>
<div class="ttc" id="classviennacl_1_1ocl_1_1context_html_afe68ad8c2df449f40f45db6605038946"><div class="ttname"><a href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">viennacl::ocl::context::get_kernel</a></div><div class="ttdeci">viennacl::ocl::kernel & get_kernel(std::string const &program_name, std::string const &kernel_name)</div><div class="ttdoc">Convenience function for retrieving the kernel of a program directly from the context. </div><div class="ttdef"><b>Definition:</b> <a href="ocl_2context_8hpp_source.html#l00605">context.hpp:605</a></div></div>
<div class="ttc" id="classviennacl_1_1vector__base_html_a762d98e2f912fc534951f25555b6077f"><div class="ttname"><a href="classviennacl_1_1vector__base.html#a762d98e2f912fc534951f25555b6077f">viennacl::vector_base< NumericT >::begin</a></div><div class="ttdeci">iterator begin()</div><div class="ttdoc">Returns an iterator pointing to the beginning of the vector (STL like) </div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1opencl_html_a500313611da0259aa03e288bac20eccb"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1opencl.html#a500313611da0259aa03e288bac20eccb">viennacl::linalg::opencl::norm_2_cpu</a></div><div class="ttdeci">void norm_2_cpu(vector_base< T > const &vec, T &result)</div><div class="ttdoc">Computes the l^1-norm of a vector with final reduction on CPU. </div><div class="ttdef"><b>Definition:</b> <a href="opencl_2vector__operations_8hpp_source.html#l00834">vector_operations.hpp:834</a></div></div>
<div class="ttc" id="classviennacl_1_1vector__tuple_html"><div class="ttname"><a href="classviennacl_1_1vector__tuple.html">viennacl::vector_tuple</a></div><div class="ttdoc">Tuple class holding pointers to multiple vectors. Mainly used as a temporary object returned from vie...</div><div class="ttdef"><b>Definition:</b> <a href="forwards_8h_source.html#l00269">forwards.h:269</a></div></div>
<div class="ttc" id="linalg_2opencl_2kernels_2vector_8hpp_html"><div class="ttname"><a href="linalg_2opencl_2kernels_2vector_8hpp.html">vector.hpp</a></div><div class="ttdoc">OpenCL kernel file for vector operations. </div></div>
<div class="ttc" id="ocl_2handle_8hpp_html"><div class="ttname"><a href="ocl_2handle_8hpp.html">handle.hpp</a></div><div class="ttdoc">Implementation of a smart-pointer-like class for handling OpenCL handles. </div></div>
<div class="ttc" id="namespaceviennacl_1_1traits_html_a68603a1e1ca1bfb6d107831ba5096786"><div class="ttname"><a href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a></div><div class="ttdeci">result_of::size_type< T >::type start(T const &obj)</div><div class="ttdef"><b>Definition:</b> <a href="start_8hpp_source.html#l00044">start.hpp:44</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1opencl_html_a0501c423f35eb16759db2c3028ae4857"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1opencl.html#a0501c423f35eb16759db2c3028ae4857">viennacl::linalg::opencl::av</a></div><div class="ttdeci">void av(vector_base< T > &vec1, vector_base< T > const &vec2, ScalarType1 const &alpha, vcl_size_t len_alpha, bool reciprocal_alpha, bool flip_sign_alpha)</div><div class="ttdef"><b>Definition:</b> <a href="opencl_2vector__operations_8hpp_source.html#l00076">vector_operations.hpp:76</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1opencl_1_1detail_html_a685282399bcfb05ee912c02fed7f922f"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a685282399bcfb05ee912c02fed7f922f">viennacl::linalg::opencl::detail::make_options</a></div><div class="ttdeci">cl_uint make_options(vcl_size_t length, bool reciprocal, bool flip_sign)</div><div class="ttdef"><b>Definition:</b> <a href="linalg_2opencl_2common_8hpp_source.html#l00042">common.hpp:42</a></div></div>
<div class="ttc" id="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector_html_a803233f6aed07b9ef954c30257d7a75f"><div class="ttname"><a href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html#a803233f6aed07b9ef954c30257d7a75f">viennacl::linalg::opencl::kernels::vector::init</a></div><div class="ttdeci">static void init(viennacl::ocl::context &ctx)</div><div class="ttdef"><b>Definition:</b> <a href="linalg_2opencl_2kernels_2vector_8hpp_source.html#l00686">vector.hpp:686</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1opencl_html_a1ec36a29b89412455b3392fbca312a24"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1opencl.html#a1ec36a29b89412455b3392fbca312a24">viennacl::linalg::opencl::norm_1_impl</a></div><div class="ttdeci">void norm_1_impl(vector_base< T > const &vec, scalar< T > &result)</div><div class="ttdoc">Computes the l^1-norm of a vector. </div><div class="ttdef"><b>Definition:</b> <a href="opencl_2vector__operations_8hpp_source.html#l00737">vector_operations.hpp:737</a></div></div>
<div class="ttc" id="classviennacl_1_1vector_html_a1b73aadf0c7b6c0028fd237ebb30c767"><div class="ttname"><a href="classviennacl_1_1vector.html#a1b73aadf0c7b6c0028fd237ebb30c767">viennacl::vector::resize</a></div><div class="ttdeci">void resize(size_type new_size, bool preserve=true)</div><div class="ttdoc">Resizes the allocated memory for the vector. Pads the memory to be a multiple of 'AlignmentV'. </div><div class="ttdef"><b>Definition:</b> <a href="vector_8hpp_source.html#l01046">vector.hpp:1046</a></div></div>
<div class="ttc" id="classviennacl_1_1vector__base_html"><div class="ttname"><a href="classviennacl_1_1vector__base.html">viennacl::vector_base</a></div><div class="ttdoc">Common base class for dense vectors, vector ranges, and vector slices. </div><div class="ttdef"><b>Definition:</b> <a href="vector__def_8hpp_source.html#l00104">vector_def.hpp:104</a></div></div>
<div class="ttc" id="namespaceviennacl_html_a98a0afcc513111ffa0bd138f891930df"><div class="ttname"><a href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">viennacl::vcl_size_t</a></div><div class="ttdeci">std::size_t vcl_size_t</div><div class="ttdef"><b>Definition:</b> <a href="forwards_8h_source.html#l00075">forwards.h:75</a></div></div>
<div class="ttc" id="classviennacl_1_1vector_html"><div class="ttname"><a href="classviennacl_1_1vector.html">viennacl::vector</a></div><div class="ttdef"><b>Definition:</b> <a href="forwards_8h_source.html#l00266">forwards.h:266</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1opencl_html_a89a844a138804369fef44a01653e85b3"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1opencl.html#a89a844a138804369fef44a01653e85b3">viennacl::linalg::opencl::inclusive_scan</a></div><div class="ttdeci">void inclusive_scan(vector_base< NumericT > const &input, vector_base< NumericT > &output)</div><div class="ttdoc">This function implements an inclusive scan using CUDA. </div><div class="ttdef"><b>Definition:</b> <a href="opencl_2vector__operations_8hpp_source.html#l01238">vector_operations.hpp:1238</a></div></div>
<div class="ttc" id="structviennacl_1_1is__division_html"><div class="ttname"><a href="structviennacl_1_1is__division.html">viennacl::is_division</a></div><div class="ttdoc">Helper metafunction for checking whether the provided type is viennacl::op_div (for division) ...</div><div class="ttdef"><b>Definition:</b> <a href="predicate_8hpp_source.html#l00466">predicate.hpp:466</a></div></div>
<div class="ttc" id="scan_8hpp_html"><div class="ttname"><a href="scan_8hpp.html">scan.hpp</a></div><div class="ttdoc">OpenCL kernel file for scan operations. To be merged back to vector operations. </div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1opencl_html_a8dd7386eb70a19d9d818b5ba57512d57"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1opencl.html#a8dd7386eb70a19d9d818b5ba57512d57">viennacl::linalg::opencl::element_op</a></div><div class="ttdeci">void element_op(matrix_base< T > &A, matrix_expression< const matrix_base< T >, const matrix_base< T >, op_element_binary< OP > > const &proxy)</div><div class="ttdoc">Implementation of binary element-wise operations A = OP(B,C) </div><div class="ttdef"><b>Definition:</b> <a href="opencl_2matrix__operations_8hpp_source.html#l00540">matrix_operations.hpp:540</a></div></div>
<div class="ttc" id="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector__multi__inner__prod_html_abb6e0bf18d527d2a9d075b28e0b89d93"><div class="ttname"><a href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector__multi__inner__prod.html#abb6e0bf18d527d2a9d075b28e0b89d93">viennacl::linalg::opencl::kernels::vector_multi_inner_prod::init</a></div><div class="ttdeci">static void init(viennacl::ocl::context &ctx)</div><div class="ttdef"><b>Definition:</b> <a href="linalg_2opencl_2kernels_2vector_8hpp_source.html#l00734">vector.hpp:734</a></div></div>
<div class="ttc" id="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector__element_html"><div class="ttname"><a href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector__element.html">viennacl::linalg::opencl::kernels::vector_element</a></div><div class="ttdoc">Main kernel class for generating OpenCL kernels for elementwise operations other than addition and su...</div><div class="ttdef"><b>Definition:</b> <a href="vector__element_8hpp_source.html#l00097">vector_element.hpp:97</a></div></div>
<div class="ttc" id="predicate_8hpp_html"><div class="ttname"><a href="predicate_8hpp.html">predicate.hpp</a></div><div class="ttdoc">All the predicates used within ViennaCL. Checks for expressions to be vectors, etc. </div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1opencl_html_a4e7dbe07ee5433438da8435cdb1a08ee"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1opencl.html#a4e7dbe07ee5433438da8435cdb1a08ee">viennacl::linalg::opencl::convert</a></div><div class="ttdeci">void convert(matrix_base< DestNumericT > &dest, matrix_base< SrcNumericT > const &src)</div><div class="ttdef"><b>Definition:</b> <a href="opencl_2matrix__operations_8hpp_source.html#l00134">matrix_operations.hpp:134</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1traits_html_a6707f5dab8f482170d2046a605f46ef8"><div class="ttname"><a href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a></div><div class="ttdeci">viennacl::context context(T const &t)</div><div class="ttdoc">Returns an ID for the currently active memory domain of an object. </div><div class="ttdef"><b>Definition:</b> <a href="traits_2context_8hpp_source.html#l00040">context.hpp:40</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1ocl_html_a5f2022f653ea1cf364d20e3ff84dcada"><div class="ttname"><a href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a></div><div class="ttdeci">void enqueue(KernelType &k, viennacl::ocl::command_queue const &queue)</div><div class="ttdoc">Enqueues a kernel in the provided queue. </div><div class="ttdef"><b>Definition:</b> <a href="enqueue_8hpp_source.html#l00050">enqueue.hpp:50</a></div></div>
<div class="ttc" id="kernel_8hpp_html"><div class="ttname"><a href="kernel_8hpp.html">kernel.hpp</a></div><div class="ttdoc">Representation of an OpenCL kernel in ViennaCL. </div></div>
<div class="ttc" id="structviennacl_1_1scalar__vector_html"><div class="ttname"><a href="structviennacl_1_1scalar__vector.html">viennacl::scalar_vector</a></div><div class="ttdoc">Represents a vector consisting of scalars 's' only, i.e. v[i] = s for all i. To be used as an initial...</div><div class="ttdef"><b>Definition:</b> <a href="vector__def_8hpp_source.html#l00087">vector_def.hpp:87</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1opencl_html_a2ab3c5aa6788fe5dce609753f8c038f7"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1opencl.html#a2ab3c5aa6788fe5dce609753f8c038f7">viennacl::linalg::opencl::exclusive_scan</a></div><div class="ttdeci">void exclusive_scan(vector_base< NumericT > const &input, vector_base< NumericT > &output)</div><div class="ttdoc">This function implements an exclusive scan using CUDA. </div><div class="ttdef"><b>Definition:</b> <a href="opencl_2vector__operations_8hpp_source.html#l01251">vector_operations.hpp:1251</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1opencl_html_ae19ed387707bd0b8721dd7acb150b2d8"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1opencl.html#ae19ed387707bd0b8721dd7acb150b2d8">viennacl::linalg::opencl::index_norm_inf</a></div><div class="ttdeci">cl_uint index_norm_inf(vector_base< T > const &vec)</div><div class="ttdoc">Computes the index of the first entry that is equal to the supremum-norm in modulus. </div><div class="ttdef"><b>Definition:</b> <a href="opencl_2vector__operations_8hpp_source.html#l00930">vector_operations.hpp:930</a></div></div>
<div class="ttc" id="classviennacl_1_1vector__base_html_a15c47ae4326098aeaa4ed6b91fc6df9b"><div class="ttname"><a href="classviennacl_1_1vector__base.html#a15c47ae4326098aeaa4ed6b91fc6df9b">viennacl::vector_base::size</a></div><div class="ttdeci">size_type size() const </div><div class="ttdoc">Returns the length of the vector (cf. std::vector) </div><div class="ttdef"><b>Definition:</b> <a href="vector__def_8hpp_source.html#l00118">vector_def.hpp:118</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1opencl_html_a4fad07ab525d7540817ecd9006a8bcc8"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1opencl.html#a4fad07ab525d7540817ecd9006a8bcc8">viennacl::linalg::opencl::norm_inf_cpu</a></div><div class="ttdeci">void norm_inf_cpu(vector_base< T > const &vec, T &result)</div><div class="ttdoc">Computes the supremum-norm of a vector. </div><div class="ttdef"><b>Definition:</b> <a href="opencl_2vector__operations_8hpp_source.html#l00898">vector_operations.hpp:898</a></div></div>
<div class="ttc" id="classviennacl_1_1ocl_1_1kernel_html_a0144c18ae9f07722e5b5697335b7cff5"><div class="ttname"><a href="classviennacl_1_1ocl_1_1kernel.html#a0144c18ae9f07722e5b5697335b7cff5">viennacl::ocl::kernel::global_work_size</a></div><div class="ttdeci">size_type global_work_size(int index=0) const </div><div class="ttdoc">Returns the global work size at the respective dimension. </div><div class="ttdef"><b>Definition:</b> <a href="kernel_8hpp_source.html#l00751">kernel.hpp:751</a></div></div>
<div class="ttc" id="classviennacl_1_1backend_1_1mem__handle_html"><div class="ttname"><a href="classviennacl_1_1backend_1_1mem__handle.html">viennacl::backend::mem_handle</a></div><div class="ttdoc">Main abstraction class for multiple memory domains. Represents a buffer in either main RAM...</div><div class="ttdef"><b>Definition:</b> <a href="mem__handle_8hpp_source.html#l00089">mem_handle.hpp:89</a></div></div>
<div class="ttc" id="classviennacl_1_1vector__tuple_html_a9e4b9367232f8937dfaddeaeca64e0e0"><div class="ttname"><a href="classviennacl_1_1vector__tuple.html#a9e4b9367232f8937dfaddeaeca64e0e0">viennacl::vector_tuple::const_at</a></div><div class="ttdeci">VectorType const & const_at(vcl_size_t i) const </div><div class="ttdef"><b>Definition:</b> <a href="vector_8hpp_source.html#l01146">vector.hpp:1146</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1opencl_1_1detail_html_a66ecf8efa0b41147e85710db81cc9e37"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a66ecf8efa0b41147e85710db81cc9e37">viennacl::linalg::opencl::detail::make_layout</a></div><div class="ttdeci">viennacl::ocl::packed_cl_uint make_layout(vector_base< NumericT > const &vec)</div><div class="ttdef"><b>Definition:</b> <a href="opencl_2vector__operations_8hpp_source.html#l00470">vector_operations.hpp:470</a></div></div>
<div class="ttc" id="structviennacl_1_1op__element__binary_html"><div class="ttname"><a href="structviennacl_1_1op__element__binary.html">viennacl::op_element_binary</a></div><div class="ttdoc">A tag class representing element-wise binary operations (like multiplication) on vectors or matrices...</div><div class="ttdef"><b>Definition:</b> <a href="forwards_8h_source.html#l00130">forwards.h:130</a></div></div>
<div class="ttc" id="vector__element_8hpp_html"><div class="ttname"><a href="vector__element_8hpp.html">vector_element.hpp</a></div><div class="ttdoc">OpenCL kernel file for element-wise vector operations. </div></div>
<div class="ttc" id="namespaceviennacl_1_1backend_html_a1499f19634964e2c7c8aeeefc6206126"><div class="ttname"><a href="namespaceviennacl_1_1backend.html#a1499f19634964e2c7c8aeeefc6206126">viennacl::backend::memory_create</a></div><div class="ttdeci">void memory_create(mem_handle &handle, vcl_size_t size_in_bytes, viennacl::context const &ctx, const void *host_ptr=NULL)</div><div class="ttdoc">Creates an array of the specified size. If the second argument is provided, the buffer is initialized...</div><div class="ttdef"><b>Definition:</b> <a href="memory_8hpp_source.html#l00087">memory.hpp:87</a></div></div>
<div class="ttc" id="vector__def_8hpp_html"><div class="ttname"><a href="vector__def_8hpp.html">vector_def.hpp</a></div><div class="ttdoc">Forward declarations of the implicit_vector_base, vector_base class. </div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1detail_html_aef015779a92be597e546c3491cebf6c1"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1detail.html#aef015779a92be597e546c3491cebf6c1">viennacl::linalg::detail::min</a></div><div class="ttdeci">T min(const T &lhs, const T &rhs)</div><div class="ttdoc">Minimum. </div><div class="ttdef"><b>Definition:</b> <a href="linalg_2detail_2bisect_2util_8hpp_source.html#l00045">util.hpp:45</a></div></div>
<div class="ttc" id="traits_2handle_8hpp_html"><div class="ttname"><a href="traits_2handle_8hpp.html">handle.hpp</a></div><div class="ttdoc">Extracts the underlying OpenCL handle from a vector, a matrix, an expression etc. ...</div></div>
<div class="ttc" id="classviennacl_1_1vector__base_html_a47350ccdc4b0a24eaea0e8d5f9fe7fec"><div class="ttname"><a href="classviennacl_1_1vector__base.html#a47350ccdc4b0a24eaea0e8d5f9fe7fec">viennacl::vector_base::internal_size</a></div><div class="ttdeci">size_type internal_size() const </div><div class="ttdoc">Returns the internal length of the vector, which is given by size() plus the extra memory due to padd...</div><div class="ttdef"><b>Definition:</b> <a href="vector__def_8hpp_source.html#l00120">vector_def.hpp:120</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1opencl_html_a964528bcf7fca1f0e63be4b81d9a1a4b"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1opencl.html#a964528bcf7fca1f0e63be4b81d9a1a4b">viennacl::linalg::opencl::vector_assign</a></div><div class="ttdeci">void vector_assign(vector_base< T > &vec1, const T &alpha, bool up_to_internal_size=false)</div><div class="ttdoc">Assign a constant value to a vector (-range/-slice) </div><div class="ttdef"><b>Definition:</b> <a href="opencl_2vector__operations_8hpp_source.html#l00246">vector_operations.hpp:246</a></div></div>
<div class="ttc" id="classviennacl_1_1vector__base_html_aba8a76bd4c96435ba68cf96b9e5132a6"><div class="ttname"><a href="classviennacl_1_1vector__base.html#aba8a76bd4c96435ba68cf96b9e5132a6">viennacl::vector_base< NumericT >::end</a></div><div class="ttdeci">iterator end()</div><div class="ttdoc">Returns an iterator pointing to the end of the vector (STL like) </div></div>
<div class="ttc" id="structviennacl_1_1is__product_html"><div class="ttname"><a href="structviennacl_1_1is__product.html">viennacl::is_product</a></div><div class="ttdoc">Helper metafunction for checking whether the provided type is viennacl::op_prod (for products/multipl...</div><div class="ttdef"><b>Definition:</b> <a href="predicate_8hpp_source.html#l00436">predicate.hpp:436</a></div></div>
<div class="ttc" id="classviennacl_1_1vector__base_html_aaabd2cd126b77ee09b80b4c447bcbd3e"><div class="ttname"><a href="classviennacl_1_1vector__base.html#aaabd2cd126b77ee09b80b4c447bcbd3e">viennacl::vector_base::start</a></div><div class="ttdeci">size_type start() const </div><div class="ttdoc">Returns the offset within the buffer. </div><div class="ttdef"><b>Definition:</b> <a href="vector__def_8hpp_source.html#l00122">vector_def.hpp:122</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1opencl_1_1detail_html_aaeb876e922457f997cd0e7f2a51c4e1d"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#aaeb876e922457f997cd0e7f2a51c4e1d">viennacl::linalg::opencl::detail::op_to_string</a></div><div class="ttdeci">std::string op_to_string(op_abs)</div><div class="ttdef"><b>Definition:</b> <a href="linalg_2opencl_2common_8hpp_source.html#l00078">common.hpp:78</a></div></div>
<div class="ttc" id="structviennacl_1_1ocl_1_1type__to__string_html"><div class="ttname"><a href="structviennacl_1_1ocl_1_1type__to__string.html">viennacl::ocl::type_to_string</a></div><div class="ttdoc">Helper class for converting a type to its string representation. </div><div class="ttdef"><b>Definition:</b> <a href="ocl_2utils_8hpp_source.html#l00057">utils.hpp:57</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1opencl_1_1detail_html_a9900a6b53663c061cac19d0e125fe461"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1opencl_1_1detail.html#a9900a6b53663c061cac19d0e125fe461">viennacl::linalg::opencl::detail::scan_impl</a></div><div class="ttdeci">void scan_impl(vector_base< NumericT > const &input, vector_base< NumericT > &output, bool is_inclusive)</div><div class="ttdoc">Worker routine for scan routines using OpenCL. </div><div class="ttdef"><b>Definition:</b> <a href="opencl_2vector__operations_8hpp_source.html#l01193">vector_operations.hpp:1193</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1opencl_html_a8d0663f2f9916ed1ec639bcd1d240a7d"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1opencl.html#a8d0663f2f9916ed1ec639bcd1d240a7d">viennacl::linalg::opencl::vector_swap</a></div><div class="ttdeci">void vector_swap(vector_base< T > &vec1, vector_base< T > &vec2)</div><div class="ttdoc">Swaps the contents of two vectors, data is copied. </div><div class="ttdef"><b>Definition:</b> <a href="opencl_2vector__operations_8hpp_source.html#l00272">vector_operations.hpp:272</a></div></div>
<div class="ttc" id="structviennacl_1_1op__element__unary_html"><div class="ttname"><a href="structviennacl_1_1op__element__unary.html">viennacl::op_element_unary</a></div><div class="ttdoc">A tag class representing element-wise unary operations (like sin()) on vectors or matrices...</div><div class="ttdef"><b>Definition:</b> <a href="forwards_8h_source.html#l00134">forwards.h:134</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1opencl_html_aa3db821922ad772f03e524d7dabc022d"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1opencl.html#aa3db821922ad772f03e524d7dabc022d">viennacl::linalg::opencl::inner_prod_cpu</a></div><div class="ttdeci">void inner_prod_cpu(vector_base< T > const &vec1, vector_base< T > const &vec2, T &result)</div><div class="ttdoc">Computes the inner product of two vectors - implementation. Library users should call inner_prod(vec1...</div><div class="ttdef"><b>Definition:</b> <a href="opencl_2vector__operations_8hpp_source.html#l00669">vector_operations.hpp:669</a></div></div>
<div class="ttc" id="scalar_8hpp_html"><div class="ttname"><a href="scalar_8hpp.html">scalar.hpp</a></div><div class="ttdoc">Implementation of the ViennaCL scalar class. </div></div>
<div class="ttc" id="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector__convert_html_a5b181b269925c10d0a7ed4e258393566"><div class="ttname"><a href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector__convert.html#a5b181b269925c10d0a7ed4e258393566">viennacl::linalg::opencl::kernels::vector_convert::init</a></div><div class="ttdeci">static void init(viennacl::ocl::context &ctx)</div><div class="ttdef"><b>Definition:</b> <a href="linalg_2opencl_2kernels_2vector_8hpp_source.html#l00789">vector.hpp:789</a></div></div>
<div class="ttc" id="classviennacl_1_1ocl_1_1handle_html"><div class="ttname"><a href="classviennacl_1_1ocl_1_1handle.html">viennacl::ocl::handle< cl_mem ></a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1opencl_html_a07a0a89b0e9f73cd9f2b799e6778679b"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1opencl.html#a07a0a89b0e9f73cd9f2b799e6778679b">viennacl::linalg::opencl::sum_cpu</a></div><div class="ttdeci">void sum_cpu(vector_base< NumericT > const &x, NumericT &result)</div><div class="ttdoc">Computes the sum over all entries of a vector. </div><div class="ttdef"><b>Definition:</b> <a href="opencl_2vector__operations_8hpp_source.html#l01137">vector_operations.hpp:1137</a></div></div>
<div class="ttc" id="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector_html"><div class="ttname"><a href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector.html">viennacl::linalg::opencl::kernels::vector</a></div><div class="ttdoc">Main kernel class for generating OpenCL kernels for operations on/with viennacl::vector<> without inv...</div><div class="ttdef"><b>Definition:</b> <a href="linalg_2opencl_2kernels_2vector_8hpp_source.html#l00679">vector.hpp:679</a></div></div>
<div class="ttc" id="enable__if_8hpp_html"><div class="ttname"><a href="enable__if_8hpp.html">enable_if.hpp</a></div><div class="ttdoc">Simple enable-if variant that uses the SFINAE pattern. </div></div>
<div class="ttc" id="structviennacl_1_1ocl_1_1packed__cl__uint_html_a5f4dcdfd54664fb7859b27f3dec641c0"><div class="ttname"><a href="structviennacl_1_1ocl_1_1packed__cl__uint.html#a5f4dcdfd54664fb7859b27f3dec641c0">viennacl::ocl::packed_cl_uint::size</a></div><div class="ttdeci">cl_uint size</div><div class="ttdoc">Number of values in the stride. </div><div class="ttdef"><b>Definition:</b> <a href="kernel_8hpp_source.html#l00052">kernel.hpp:52</a></div></div>
<div class="ttc" id="namespaceviennacl_html_aaa5c8726b45bc89a523ca2fa8c42107a"><div class="ttname"><a href="namespaceviennacl.html#aaa5c8726b45bc89a523ca2fa8c42107a">viennacl::fast_copy</a></div><div class="ttdeci">void fast_copy(const const_vector_iterator< SCALARTYPE, ALIGNMENT > &gpu_begin, const const_vector_iterator< SCALARTYPE, ALIGNMENT > &gpu_end, CPU_ITERATOR cpu_begin)</div></div>
<div class="ttc" id="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector__element_html_a18d9e0cc1f4e6235008503386f584414"><div class="ttname"><a href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1vector__element.html#a18d9e0cc1f4e6235008503386f584414">viennacl::linalg::opencl::kernels::vector_element::init</a></div><div class="ttdeci">static void init(viennacl::ocl::context &ctx)</div><div class="ttdef"><b>Definition:</b> <a href="vector__element_8hpp_source.html#l00104">vector_element.hpp:104</a></div></div>
<div class="ttc" id="classviennacl_1_1ocl_1_1context_html_ac70d01bc7f8bd1f36c10eae811672d79"><div class="ttname"><a href="classviennacl_1_1ocl_1_1context.html#ac70d01bc7f8bd1f36c10eae811672d79">viennacl::ocl::context::create_memory</a></div><div class="ttdeci">viennacl::ocl::handle< cl_mem > create_memory(cl_mem_flags flags, unsigned int size, void *ptr=NULL) const </div><div class="ttdoc">Creates a memory buffer within the context. </div><div class="ttdef"><b>Definition:</b> <a href="ocl_2context_8hpp_source.html#l00216">context.hpp:216</a></div></div>
</div><!-- fragment --></div><!-- contents -->
</div><!-- doc-content -->
<!-- start footer part -->
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
<ul>
<li class="navelem"><a class="el" href="dir_c82e3d11dd171600f4a6e0cab1ec1e0d.html">viennacl</a></li><li class="navelem"><a class="el" href="dir_63cde087767c4ed65c7901ffc6e293fe.html">linalg</a></li><li class="navelem"><a class="el" href="dir_9df590563da805a074404567c6e27abf.html">opencl</a></li><li class="navelem"><a class="el" href="opencl_2vector__operations_8hpp.html">vector_operations.hpp</a></li>
<li class="footer">Generated on Wed Jan 20 2016 22:32:41 for ViennaCL - The Vienna Computing Library by
<a href="http://www.doxygen.org/index.html">
<img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.6 </li>
</ul>
</div>
</body>
</html>
|
