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<div class="title">sliced_ell_matrix.hpp</div> </div>
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<a href="sliced__ell__matrix_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_SLICED_ELL_MATRIX_HPP_</span></div>
<div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="preprocessor">#define VIENNACL_SLICED_ELL_MATRIX_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="l00028"></a><span class="lineno"> 28</span> <span class="preprocessor">#include "<a class="code" href="forwards_8h.html">viennacl/forwards.h</a>"</span></div>
<div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="preprocessor">#include "<a class="code" href="vector_8hpp.html">viennacl/vector.hpp</a>"</span></div>
<div class="line"><a name="l00030"></a><span class="lineno"> 30</span> </div>
<div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="preprocessor">#include "<a class="code" href="tools_8hpp.html">viennacl/tools/tools.hpp</a>"</span></div>
<div class="line"><a name="l00032"></a><span class="lineno"> 32</span> </div>
<div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="preprocessor">#include "<a class="code" href="sparse__matrix__operations_8hpp.html">viennacl/linalg/sparse_matrix_operations.hpp</a>"</span></div>
<div class="line"><a name="l00034"></a><span class="lineno"> 34</span> </div>
<div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="keyword">namespace </span>viennacl</div>
<div class="line"><a name="l00036"></a><span class="lineno"> 36</span> {</div>
<div class="line"><a name="l00045"></a><span class="lineno"> 45</span> <span class="keyword">template</span><<span class="keyword">typename</span> ScalarT, <span class="keyword">typename</span> IndexT <span class="comment">/* see forwards.h = unsigned int */</span>></div>
<div class="line"><a name="l00046"></a><span class="lineno"> 46</span> <span class="keyword">class </span>sliced_ell_matrix</div>
<div class="line"><a name="l00047"></a><span class="lineno"> 47</span> {</div>
<div class="line"><a name="l00048"></a><span class="lineno"> 48</span> <span class="keyword">public</span>:</div>
<div class="line"><a name="l00049"></a><span class="lineno"><a class="line" href="classviennacl_1_1sliced__ell__matrix.html#a2cdf3aeccfe9a10b89c48b3430cb4c93"> 49</a></span>  <span class="keyword">typedef</span> <a class="code" href="classviennacl_1_1backend_1_1mem__handle.html">viennacl::backend::mem_handle</a> <a class="code" href="classviennacl_1_1sliced__ell__matrix.html#a2cdf3aeccfe9a10b89c48b3430cb4c93">handle_type</a>;</div>
<div class="line"><a name="l00050"></a><span class="lineno"><a class="line" href="classviennacl_1_1sliced__ell__matrix.html#af0672b686ad27ddcf948116bae059329"> 50</a></span>  <span class="keyword">typedef</span> <a class="code" href="classviennacl_1_1scalar.html">scalar<typename viennacl::tools::CHECK_SCALAR_TEMPLATE_ARGUMENT<ScalarT>::ResultType</a>> <a class="code" href="classviennacl_1_1sliced__ell__matrix.html#af0672b686ad27ddcf948116bae059329">value_type</a>;</div>
<div class="line"><a name="l00051"></a><span class="lineno"><a class="line" href="classviennacl_1_1sliced__ell__matrix.html#adf0fb80bb38ab0256a622960c0c18699"> 51</a></span>  <span class="keyword">typedef</span> <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="classviennacl_1_1sliced__ell__matrix.html#adf0fb80bb38ab0256a622960c0c18699">size_type</a>;</div>
<div class="line"><a name="l00052"></a><span class="lineno"> 52</span> </div>
<div class="line"><a name="l00053"></a><span class="lineno"><a class="line" href="classviennacl_1_1sliced__ell__matrix.html#a362dc0c5f0d644cbcf6514f3b3ee6529"> 53</a></span>  <span class="keyword">explicit</span> <a class="code" href="classviennacl_1_1sliced__ell__matrix.html#a362dc0c5f0d644cbcf6514f3b3ee6529">sliced_ell_matrix</a>() : rows_(0), cols_(0), rows_per_block_(0) {}</div>
<div class="line"><a name="l00054"></a><span class="lineno"> 54</span> </div>
<div class="line"><a name="l00059"></a><span class="lineno"><a class="line" href="classviennacl_1_1sliced__ell__matrix.html#a9f244082eff24e93495d3b4abec735b0"> 59</a></span>  <a class="code" href="classviennacl_1_1sliced__ell__matrix.html#a9f244082eff24e93495d3b4abec735b0">sliced_ell_matrix</a>(<a class="code" href="classviennacl_1_1sliced__ell__matrix.html#adf0fb80bb38ab0256a622960c0c18699">size_type</a> num_rows,</div>
<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <a class="code" href="classviennacl_1_1sliced__ell__matrix.html#adf0fb80bb38ab0256a622960c0c18699">size_type</a> num_cols,</div>
<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <a class="code" href="classviennacl_1_1sliced__ell__matrix.html#adf0fb80bb38ab0256a622960c0c18699">size_type</a> num_rows_per_block_ = 0)</div>
<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  : rows_(num_rows),</div>
<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  cols_(num_cols),</div>
<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  rows_per_block_(num_rows_per_block_) {}</div>
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span> </div>
<div class="line"><a name="l00066"></a><span class="lineno"><a class="line" href="classviennacl_1_1sliced__ell__matrix.html#aa725bf2d5b213f119bd4b9fe9258c201"> 66</a></span>  <span class="keyword">explicit</span> <a class="code" href="classviennacl_1_1sliced__ell__matrix.html#aa725bf2d5b213f119bd4b9fe9258c201">sliced_ell_matrix</a>(<a class="code" href="classviennacl_1_1context.html">viennacl::context</a> ctx) : rows_(0), cols_(0), rows_per_block_(0)</div>
<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  {</div>
<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  columns_per_block_.<a class="code" href="classviennacl_1_1backend_1_1mem__handle.html#ac13e99f562746d6682116dec1e13a7da">switch_active_handle_id</a>(ctx.<a class="code" href="classviennacl_1_1context.html#aadf575d49ed144e8fa4707cdad69c349">memory_type</a>());</div>
<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  column_indices_.<a class="code" href="classviennacl_1_1backend_1_1mem__handle.html#ac13e99f562746d6682116dec1e13a7da">switch_active_handle_id</a>(ctx.<a class="code" href="classviennacl_1_1context.html#aadf575d49ed144e8fa4707cdad69c349">memory_type</a>());</div>
<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  block_start_.<a class="code" href="classviennacl_1_1backend_1_1mem__handle.html#ac13e99f562746d6682116dec1e13a7da">switch_active_handle_id</a>(ctx.<a class="code" href="classviennacl_1_1context.html#aadf575d49ed144e8fa4707cdad69c349">memory_type</a>());</div>
<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  elements_.<a class="code" href="classviennacl_1_1backend_1_1mem__handle.html#ac13e99f562746d6682116dec1e13a7da">switch_active_handle_id</a>(ctx.<a class="code" href="classviennacl_1_1context.html#aadf575d49ed144e8fa4707cdad69c349">memory_type</a>());</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> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENCL</span></div>
<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="keywordflow">if</span> (ctx.<a class="code" href="classviennacl_1_1context.html#aadf575d49ed144e8fa4707cdad69c349">memory_type</a>() == <a class="code" href="namespaceviennacl.html#a00b40450b6b2fd87aad3527d9b2084b8adb37af613f34867568e4f6cf720c68b1">OPENCL_MEMORY</a>)</div>
<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  {</div>
<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  columns_per_block_.opencl_handle().context(ctx.opencl_context());</div>
<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  column_indices_.opencl_handle().context(ctx.opencl_context());</div>
<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  block_start_.opencl_handle().context(ctx.opencl_context());</div>
<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  elements_.opencl_handle().context(ctx.opencl_context());</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> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  }</div>
<div class="line"><a name="l00083"></a><span class="lineno"> 83</span> </div>
<div class="line"><a name="l00085"></a><span class="lineno"><a class="line" href="classviennacl_1_1sliced__ell__matrix.html#ac681e3c8d41b686282711644cbdcadfb"> 85</a></span>  <span class="keywordtype">void</span> <a class="code" href="classviennacl_1_1sliced__ell__matrix.html#ac681e3c8d41b686282711644cbdcadfb">clear</a>()</div>
<div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  {</div>
<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  <a class="code" href="classviennacl_1_1backend_1_1typesafe__host__array.html">viennacl::backend::typesafe_host_array<IndexT></a> host_columns_per_block_buffer(columns_per_block_, rows_ / rows_per_block_ + 1);</div>
<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <a class="code" href="classviennacl_1_1backend_1_1typesafe__host__array.html">viennacl::backend::typesafe_host_array<IndexT></a> host_column_buffer(column_indices_, <a class="code" href="classviennacl_1_1sliced__ell__matrix.html#ab8a2233384ac8dcdb85b5385706548a1">internal_size1</a>());</div>
<div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <a class="code" href="classviennacl_1_1backend_1_1typesafe__host__array.html">viennacl::backend::typesafe_host_array<IndexT></a> host_block_start_buffer(block_start_, (rows_ - 1) / rows_per_block_ + 1);</div>
<div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  std::vector<ScalarT> host_elements(1);</div>
<div class="line"><a name="l00091"></a><span class="lineno"> 91</span> </div>
<div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <a class="code" href="namespaceviennacl_1_1backend.html#a1499f19634964e2c7c8aeeefc6206126">viennacl::backend::memory_create</a>(columns_per_block_, host_columns_per_block_buffer.<a class="code" href="classviennacl_1_1backend_1_1typesafe__host__array.html#ac8646f4841c47048a1d2e004b9536af8">element_size</a>() * (rows_ / rows_per_block_ + 1), <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(columns_per_block_), host_columns_per_block_buffer.<a class="code" href="classviennacl_1_1backend_1_1typesafe__host__array.html#a1727eeb845f50cf5bd51ef54c5938b8c">get</a>());</div>
<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <a class="code" href="namespaceviennacl_1_1backend.html#a1499f19634964e2c7c8aeeefc6206126">viennacl::backend::memory_create</a>(column_indices_, host_column_buffer.<a class="code" href="classviennacl_1_1backend_1_1typesafe__host__array.html#ac8646f4841c47048a1d2e004b9536af8">element_size</a>() * <a class="code" href="classviennacl_1_1sliced__ell__matrix.html#ab8a2233384ac8dcdb85b5385706548a1">internal_size1</a>(), <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(column_indices_), host_column_buffer.<a class="code" href="classviennacl_1_1backend_1_1typesafe__host__array.html#a1727eeb845f50cf5bd51ef54c5938b8c">get</a>());</div>
<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <a class="code" href="namespaceviennacl_1_1backend.html#a1499f19634964e2c7c8aeeefc6206126">viennacl::backend::memory_create</a>(block_start_, host_block_start_buffer.<a class="code" href="classviennacl_1_1backend_1_1typesafe__host__array.html#ac8646f4841c47048a1d2e004b9536af8">element_size</a>() * ((rows_ - 1) / rows_per_block_ + 1), <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(block_start_), host_block_start_buffer.<a class="code" href="classviennacl_1_1backend_1_1typesafe__host__array.html#a1727eeb845f50cf5bd51ef54c5938b8c">get</a>());</div>
<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <a class="code" href="namespaceviennacl_1_1backend.html#a1499f19634964e2c7c8aeeefc6206126">viennacl::backend::memory_create</a>(elements_, <span class="keyword">sizeof</span>(ScalarT) * 1, <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(elements_), &(host_elements[0]));</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> </div>
<div class="line"><a name="l00098"></a><span class="lineno"><a class="line" href="classviennacl_1_1sliced__ell__matrix.html#ab8a2233384ac8dcdb85b5385706548a1"> 98</a></span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="classviennacl_1_1sliced__ell__matrix.html#ab8a2233384ac8dcdb85b5385706548a1">internal_size1</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> viennacl::tools::align_to_multiple<vcl_size_t>(rows_, rows_per_block_); }</div>
<div class="line"><a name="l00099"></a><span class="lineno"><a class="line" href="classviennacl_1_1sliced__ell__matrix.html#ad4fd3359611ca475b85d2041bdec1377"> 99</a></span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="classviennacl_1_1sliced__ell__matrix.html#ad4fd3359611ca475b85d2041bdec1377">internal_size2</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> cols_; }</div>
<div class="line"><a name="l00100"></a><span class="lineno"> 100</span> </div>
<div class="line"><a name="l00101"></a><span class="lineno"><a class="line" href="classviennacl_1_1sliced__ell__matrix.html#a16cd8194ca5b263de32f131362498d77"> 101</a></span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="classviennacl_1_1sliced__ell__matrix.html#a16cd8194ca5b263de32f131362498d77">size1</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> rows_; }</div>
<div class="line"><a name="l00102"></a><span class="lineno"><a class="line" href="classviennacl_1_1sliced__ell__matrix.html#ae0afefc19f6dc7692a87cd8a16b51d30"> 102</a></span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="classviennacl_1_1sliced__ell__matrix.html#ae0afefc19f6dc7692a87cd8a16b51d30">size2</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> cols_; }</div>
<div class="line"><a name="l00103"></a><span class="lineno"> 103</span> </div>
<div class="line"><a name="l00104"></a><span class="lineno"><a class="line" href="classviennacl_1_1sliced__ell__matrix.html#aa9a7f4003687cae9a2af97f9fa328db5"> 104</a></span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="classviennacl_1_1sliced__ell__matrix.html#aa9a7f4003687cae9a2af97f9fa328db5">rows_per_block</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> rows_per_block_; }</div>
<div class="line"><a name="l00105"></a><span class="lineno"> 105</span> </div>
<div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <span class="comment">//vcl_size_t nnz() const { return rows_ * maxnnz_; }</span></div>
<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  <span class="comment">//vcl_size_t internal_nnz() const { return internal_size1() * internal_maxnnz(); }</span></div>
<div class="line"><a name="l00108"></a><span class="lineno"> 108</span> </div>
<div class="line"><a name="l00109"></a><span class="lineno"><a class="line" href="classviennacl_1_1sliced__ell__matrix.html#a94043424c01974b2db8062f74f625825"> 109</a></span>  <a class="code" href="classviennacl_1_1backend_1_1mem__handle.html">handle_type</a> & <a class="code" href="classviennacl_1_1sliced__ell__matrix.html#a94043424c01974b2db8062f74f625825">handle1</a>() { <span class="keywordflow">return</span> columns_per_block_; }</div>
<div class="line"><a name="l00110"></a><span class="lineno"><a class="line" href="classviennacl_1_1sliced__ell__matrix.html#a727fd3a25232545c59204885ff3e32d4"> 110</a></span>  <span class="keyword">const</span> <a class="code" href="classviennacl_1_1backend_1_1mem__handle.html">handle_type</a> & <a class="code" href="classviennacl_1_1sliced__ell__matrix.html#a727fd3a25232545c59204885ff3e32d4">handle1</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> columns_per_block_; }</div>
<div class="line"><a name="l00111"></a><span class="lineno"> 111</span> </div>
<div class="line"><a name="l00112"></a><span class="lineno"><a class="line" href="classviennacl_1_1sliced__ell__matrix.html#a31d5fa9ec25dcfeb260f7e11c4db6571"> 112</a></span>  <a class="code" href="classviennacl_1_1backend_1_1mem__handle.html">handle_type</a> & <a class="code" href="classviennacl_1_1sliced__ell__matrix.html#a31d5fa9ec25dcfeb260f7e11c4db6571">handle2</a>() { <span class="keywordflow">return</span> column_indices_; }</div>
<div class="line"><a name="l00113"></a><span class="lineno"><a class="line" href="classviennacl_1_1sliced__ell__matrix.html#a45249ad5b44d0f506adc27e1e18aecdf"> 113</a></span>  <span class="keyword">const</span> <a class="code" href="classviennacl_1_1backend_1_1mem__handle.html">handle_type</a> & <a class="code" href="classviennacl_1_1sliced__ell__matrix.html#a45249ad5b44d0f506adc27e1e18aecdf">handle2</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> column_indices_; }</div>
<div class="line"><a name="l00114"></a><span class="lineno"> 114</span> </div>
<div class="line"><a name="l00115"></a><span class="lineno"><a class="line" href="classviennacl_1_1sliced__ell__matrix.html#aa59ae796d592a679a4c6036ba84f61b0"> 115</a></span>  <a class="code" href="classviennacl_1_1backend_1_1mem__handle.html">handle_type</a> & <a class="code" href="classviennacl_1_1sliced__ell__matrix.html#aa59ae796d592a679a4c6036ba84f61b0">handle3</a>() { <span class="keywordflow">return</span> block_start_; }</div>
<div class="line"><a name="l00116"></a><span class="lineno"><a class="line" href="classviennacl_1_1sliced__ell__matrix.html#aec497ed037ef674d36729bda4db7e93f"> 116</a></span>  <span class="keyword">const</span> <a class="code" href="classviennacl_1_1backend_1_1mem__handle.html">handle_type</a> & <a class="code" href="classviennacl_1_1sliced__ell__matrix.html#aec497ed037ef674d36729bda4db7e93f">handle3</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> block_start_; }</div>
<div class="line"><a name="l00117"></a><span class="lineno"> 117</span> </div>
<div class="line"><a name="l00118"></a><span class="lineno"><a class="line" href="classviennacl_1_1sliced__ell__matrix.html#abbc671358c44037b7c2b22a01f17c3a7"> 118</a></span>  <a class="code" href="classviennacl_1_1backend_1_1mem__handle.html">handle_type</a> & <a class="code" href="classviennacl_1_1sliced__ell__matrix.html#abbc671358c44037b7c2b22a01f17c3a7">handle</a>() { <span class="keywordflow">return</span> elements_; }</div>
<div class="line"><a name="l00119"></a><span class="lineno"><a class="line" href="classviennacl_1_1sliced__ell__matrix.html#a1b9a6e9229a8694123562166eb2d4e32"> 119</a></span>  <span class="keyword">const</span> <a class="code" href="classviennacl_1_1backend_1_1mem__handle.html">handle_type</a> & <a class="code" href="classviennacl_1_1sliced__ell__matrix.html#a1b9a6e9229a8694123562166eb2d4e32">handle</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> elements_; }</div>
<div class="line"><a name="l00120"></a><span class="lineno"> 120</span> </div>
<div class="line"><a name="l00121"></a><span class="lineno"> 121</span> <span class="preprocessor">#if defined(_MSC_VER) && _MSC_VER < 1500 //Visual Studio 2005 needs special treatment</span></div>
<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  <span class="keyword">template</span><<span class="keyword">typename</span> CPUMatrixT></div>
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <span class="keyword">friend</span> <span class="keywordtype">void</span> <a class="code" href="classviennacl_1_1sliced__ell__matrix.html#a40c479e880ef7e7f50ed67cda91bb8e7">copy</a>(CPUMatrixT <span class="keyword">const</span> & cpu_matrix, <a class="code" href="classviennacl_1_1sliced__ell__matrix.html">sliced_ell_matrix</a> & gpu_matrix );</div>
<div class="line"><a name="l00124"></a><span class="lineno"> 124</span> <span class="preprocessor">#else</span></div>
<div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  <span class="keyword">template</span><<span class="keyword">typename</span> CPUMatrixT, <span class="keyword">typename</span> ScalarT2, <span class="keyword">typename</span> IndexT2></div>
<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  <span class="keyword">friend</span> <span class="keywordtype">void</span> <a class="code" href="classviennacl_1_1sliced__ell__matrix.html#a40c479e880ef7e7f50ed67cda91bb8e7">copy</a>(CPUMatrixT <span class="keyword">const</span> & cpu_matrix, <a class="code" href="classviennacl_1_1sliced__ell__matrix.html">sliced_ell_matrix<ScalarT2, IndexT2></a> & gpu_matrix );</div>
<div class="line"><a name="l00127"></a><span class="lineno"> 127</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00128"></a><span class="lineno"> 128</span> </div>
<div class="line"><a name="l00129"></a><span class="lineno"> 129</span> <span class="keyword">private</span>:</div>
<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> rows_;</div>
<div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> cols_;</div>
<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> rows_per_block_; <span class="comment">//parameter C in the paper by Kreutzer et al.</span></div>
<div class="line"><a name="l00133"></a><span class="lineno"> 133</span> </div>
<div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  <a class="code" href="classviennacl_1_1sliced__ell__matrix.html#a2cdf3aeccfe9a10b89c48b3430cb4c93">handle_type</a> columns_per_block_;</div>
<div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  <a class="code" href="classviennacl_1_1sliced__ell__matrix.html#a2cdf3aeccfe9a10b89c48b3430cb4c93">handle_type</a> column_indices_;</div>
<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  <a class="code" href="classviennacl_1_1sliced__ell__matrix.html#a2cdf3aeccfe9a10b89c48b3430cb4c93">handle_type</a> block_start_;</div>
<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  <a class="code" href="classviennacl_1_1sliced__ell__matrix.html#a2cdf3aeccfe9a10b89c48b3430cb4c93">handle_type</a> elements_;</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> </div>
<div class="line"><a name="l00140"></a><span class="lineno"> 140</span> <span class="keyword">template</span><<span class="keyword">typename</span> CPUMatrixT, <span class="keyword">typename</span> ScalarT, <span class="keyword">typename</span> IndexT></div>
<div class="line"><a name="l00141"></a><span class="lineno"><a class="line" href="namespaceviennacl.html#a40fb810a020b6bd780ee1e12e6d02763"> 141</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl.html#a10b7f8cf6b8864a7aa196d670481a453">copy</a>(CPUMatrixT <span class="keyword">const</span> & cpu_matrix, <a class="code" href="classviennacl_1_1sliced__ell__matrix.html">sliced_ell_matrix<ScalarT, IndexT></a> & gpu_matrix )</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>  assert( (gpu_matrix.size1() == 0 || <a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">viennacl::traits::size1</a>(cpu_matrix) == gpu_matrix.size1()) && <span class="keywordtype">bool</span>(<span class="stringliteral">"Size mismatch"</span>) );</div>
<div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  assert( (gpu_matrix.size2() == 0 || <a class="code" href="namespaceviennacl_1_1traits.html#a3658e7c29ac0f60a20cb5871f5b5fd98">viennacl::traits::size2</a>(cpu_matrix) == gpu_matrix.size2()) && <span class="keywordtype">bool</span>(<span class="stringliteral">"Size mismatch"</span>) );</div>
<div class="line"><a name="l00145"></a><span class="lineno"> 145</span> </div>
<div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  <span class="keywordflow">if</span> (gpu_matrix.rows_per_block() == 0) <span class="comment">// not yet initialized by user. Set default: 32 is perfect for NVIDIA GPUs and older AMD GPUs. Still okay for newer AMD GPUs.</span></div>
<div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  gpu_matrix.rows_per_block_ = 32;</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>  if (<a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">viennacl::traits::size1</a>(cpu_matrix) > 0 && <a class="code" href="namespaceviennacl_1_1traits.html#a3658e7c29ac0f60a20cb5871f5b5fd98">viennacl::traits::size2</a>(cpu_matrix) > 0)</div>
<div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  {</div>
<div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  <span class="comment">//determine max capacity for row</span></div>
<div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  IndexT columns_in_current_block = 0;</div>
<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> total_element_buffer_size = 0;</div>
<div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <a class="code" href="classviennacl_1_1backend_1_1typesafe__host__array.html">viennacl::backend::typesafe_host_array<IndexT></a> columns_in_block_buffer(gpu_matrix.handle1(), (<a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">viennacl::traits::size1</a>(cpu_matrix) - 1) / gpu_matrix.rows_per_block() + 1);</div>
<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <span class="keywordflow">for</span> (<span class="keyword">typename</span> CPUMatrixT::const_iterator1 row_it = cpu_matrix.begin1(); row_it != cpu_matrix.end1(); ++row_it)</div>
<div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  {</div>
<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> entries_in_row = 0;</div>
<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <span class="keywordflow">for</span> (<span class="keyword">typename</span> CPUMatrixT::const_iterator2 col_it = row_it.begin(); col_it != row_it.end(); ++col_it)</div>
<div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  ++entries_in_row;</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>  columns_in_current_block = <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#a5d46fe9558b0e462f10fd44942ad4fc6">std::max</a>(columns_in_current_block, static_cast<IndexT>(entries_in_row));</div>
<div class="line"><a name="l00162"></a><span class="lineno"> 162</span> </div>
<div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  <span class="comment">// check for end of block</span></div>
<div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  <span class="keywordflow">if</span> ( (row_it.index1() % gpu_matrix.rows_per_block() == gpu_matrix.rows_per_block() - 1)</div>
<div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  || row_it.index1() == <a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">viennacl::traits::size1</a>(cpu_matrix) - 1)</div>
<div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  {</div>
<div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  total_element_buffer_size += columns_in_current_block * gpu_matrix.rows_per_block();</div>
<div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  columns_in_block_buffer.set(row_it.index1() / gpu_matrix.rows_per_block(), columns_in_current_block);</div>
<div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  columns_in_current_block = 0;</div>
<div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  }</div>
<div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  }</div>
<div class="line"><a name="l00172"></a><span class="lineno"> 172</span> </div>
<div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  <span class="comment">//setup GPU matrix</span></div>
<div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  gpu_matrix.rows_ = cpu_matrix.size1();</div>
<div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  gpu_matrix.cols_ = cpu_matrix.size2();</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>  <a class="code" href="classviennacl_1_1backend_1_1typesafe__host__array.html">viennacl::backend::typesafe_host_array<IndexT></a> coords(gpu_matrix.handle2(), total_element_buffer_size);</div>
<div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  <a class="code" href="classviennacl_1_1backend_1_1typesafe__host__array.html">viennacl::backend::typesafe_host_array<IndexT></a> block_start(gpu_matrix.handle3(), (<a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">viennacl::traits::size1</a>(cpu_matrix) - 1) / gpu_matrix.rows_per_block() + 1);</div>
<div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  std::vector<ScalarT> elements(total_element_buffer_size, 0);</div>
<div class="line"><a name="l00180"></a><span class="lineno"> 180</span> </div>
<div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> block_offset = 0;</div>
<div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> block_index = 0;</div>
<div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> row_in_block = 0;</div>
<div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <span class="keywordflow">for</span> (<span class="keyword">typename</span> CPUMatrixT::const_iterator1 row_it = cpu_matrix.begin1(); row_it != cpu_matrix.end1(); ++row_it)</div>
<div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  {</div>
<div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> entry_in_row = 0;</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>  <span class="keywordflow">for</span> (<span class="keyword">typename</span> CPUMatrixT::const_iterator2 col_it = row_it.begin(); col_it != row_it.end(); ++col_it)</div>
<div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  {</div>
<div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> buffer_index = block_offset + entry_in_row * gpu_matrix.rows_per_block() + row_in_block;</div>
<div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  coords.set(buffer_index, col_it.index2());</div>
<div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  elements[buffer_index] = *col_it;</div>
<div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  entry_in_row++;</div>
<div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  }</div>
<div class="line"><a name="l00195"></a><span class="lineno"> 195</span> </div>
<div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  ++row_in_block;</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>  <span class="comment">// check for end of block:</span></div>
<div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  <span class="keywordflow">if</span> ( (row_it.index1() % gpu_matrix.rows_per_block() == gpu_matrix.rows_per_block() - 1)</div>
<div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  || row_it.index1() == <a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">viennacl::traits::size1</a>(cpu_matrix) - 1)</div>
<div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  {</div>
<div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  block_start.<a class="code" href="classviennacl_1_1backend_1_1typesafe__host__array.html#ac31bfde381eb40e0349678252c444af9">set</a>(block_index, static_cast<IndexT>(block_offset));</div>
<div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  block_offset += columns_in_block_buffer[block_index] * gpu_matrix.rows_per_block();</div>
<div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  ++block_index;</div>
<div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  row_in_block = 0;</div>
<div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  }</div>
<div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  }</div>
<div class="line"><a name="l00208"></a><span class="lineno"> 208</span> </div>
<div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  <a class="code" href="namespaceviennacl_1_1backend.html#a1499f19634964e2c7c8aeeefc6206126">viennacl::backend::memory_create</a>(gpu_matrix.handle1(), columns_in_block_buffer.raw_size(), <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">traits::context</a>(gpu_matrix.handle1()), columns_in_block_buffer.get());</div>
<div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  <a class="code" href="namespaceviennacl_1_1backend.html#a1499f19634964e2c7c8aeeefc6206126">viennacl::backend::memory_create</a>(gpu_matrix.handle2(), coords.raw_size(), <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">traits::context</a>(gpu_matrix.handle2()), coords.get());</div>
<div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  <a class="code" href="namespaceviennacl_1_1backend.html#a1499f19634964e2c7c8aeeefc6206126">viennacl::backend::memory_create</a>(gpu_matrix.handle3(), block_start.raw_size(), <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">traits::context</a>(gpu_matrix.handle3()), block_start.get());</div>
<div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  <a class="code" href="namespaceviennacl_1_1backend.html#a1499f19634964e2c7c8aeeefc6206126">viennacl::backend::memory_create</a>(gpu_matrix.handle(), <span class="keyword">sizeof</span>(ScalarT) * elements.<a class="code" href="classviennacl_1_1backend_1_1typesafe__host__array.html#a3943ea09faa2df9b7bee130d3a2d5f20">size</a>(), <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">traits::context</a>(gpu_matrix.handle()), &(elements[0]));</div>
<div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  }</div>
<div class="line"><a name="l00214"></a><span class="lineno"> 214</span> }</div>
<div class="line"><a name="l00215"></a><span class="lineno"> 215</span> </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> </div>
<div class="line"><a name="l00223"></a><span class="lineno"> 223</span> <span class="keyword">template</span><<span class="keyword">typename</span> IndexT, <span class="keyword">typename</span> NumericT, <span class="keyword">typename</span> IndexT2></div>
<div class="line"><a name="l00224"></a><span class="lineno"><a class="line" href="namespaceviennacl.html#ab1bf9bf2d8e0714db63fc999000c1510"> 224</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl.html#a10b7f8cf6b8864a7aa196d670481a453">copy</a>(std::vector< std::map<IndexT, NumericT> > <span class="keyword">const</span> & cpu_matrix,</div>
<div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  <a class="code" href="classviennacl_1_1sliced__ell__matrix.html">sliced_ell_matrix<NumericT, IndexT2></a> & gpu_matrix)</div>
<div class="line"><a name="l00226"></a><span class="lineno"> 226</span> {</div>
<div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> max_col = 0;</div>
<div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> i=0; i<cpu_matrix.size(); ++i)</div>
<div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  {</div>
<div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  <span class="keywordflow">if</span> (cpu_matrix[i].<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a>() > 0)</div>
<div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  max_col = std::max<vcl_size_t>(max_col, (cpu_matrix[i].rbegin())->first);</div>
<div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  }</div>
<div class="line"><a name="l00233"></a><span class="lineno"> 233</span> </div>
<div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  <a class="code" href="namespaceviennacl.html#a10b7f8cf6b8864a7aa196d670481a453">viennacl::copy</a>(<a class="code" href="classviennacl_1_1tools_1_1const__sparse__matrix__adapter.html">tools::const_sparse_matrix_adapter<NumericT, IndexT></a>(cpu_matrix, cpu_matrix.size(), max_col + 1), gpu_matrix);</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> <span class="comment">/*</span></div>
<div class="line"><a name="l00239"></a><span class="lineno"> 239</span> <span class="comment">template<typename CPUMatrixT, typename ScalarT, typename IndexT></span></div>
<div class="line"><a name="l00240"></a><span class="lineno"> 240</span> <span class="comment">void copy(sliced_ell_matrix<ScalarT, IndexT> const & gpu_matrix, CPUMatrixT & cpu_matrix )</span></div>
<div class="line"><a name="l00241"></a><span class="lineno"> 241</span> <span class="comment">{</span></div>
<div class="line"><a name="l00242"></a><span class="lineno"> 242</span> <span class="comment"> assert( (viennacl::traits::size1(cpu_matrix) == gpu_matrix.size1()) && bool("Size mismatch") );</span></div>
<div class="line"><a name="l00243"></a><span class="lineno"> 243</span> <span class="comment"> assert( (viennacl::traits::size2(cpu_matrix) == gpu_matrix.size2()) && bool("Size mismatch") );</span></div>
<div class="line"><a name="l00244"></a><span class="lineno"> 244</span> <span class="comment"></span></div>
<div class="line"><a name="l00245"></a><span class="lineno"> 245</span> <span class="comment"> if (gpu_matrix.size1() > 0 && gpu_matrix.size2() > 0)</span></div>
<div class="line"><a name="l00246"></a><span class="lineno"> 246</span> <span class="comment"> {</span></div>
<div class="line"><a name="l00247"></a><span class="lineno"> 247</span> <span class="comment"> std::vector<NumericT> elements(gpu_matrix.internal_nnz());</span></div>
<div class="line"><a name="l00248"></a><span class="lineno"> 248</span> <span class="comment"> viennacl::backend::typesafe_host_array<unsigned int> coords(gpu_matrix.handle2(), gpu_matrix.internal_nnz());</span></div>
<div class="line"><a name="l00249"></a><span class="lineno"> 249</span> <span class="comment"></span></div>
<div class="line"><a name="l00250"></a><span class="lineno"> 250</span> <span class="comment"> viennacl::backend::memory_read(gpu_matrix.handle(), 0, sizeof(NumericT) * elements.size(), &(elements[0]));</span></div>
<div class="line"><a name="l00251"></a><span class="lineno"> 251</span> <span class="comment"> viennacl::backend::memory_read(gpu_matrix.handle2(), 0, coords.raw_size(), coords.get());</span></div>
<div class="line"><a name="l00252"></a><span class="lineno"> 252</span> <span class="comment"></span></div>
<div class="line"><a name="l00253"></a><span class="lineno"> 253</span> <span class="comment"> for (vcl_size_t row = 0; row < gpu_matrix.size1(); row++)</span></div>
<div class="line"><a name="l00254"></a><span class="lineno"> 254</span> <span class="comment"> {</span></div>
<div class="line"><a name="l00255"></a><span class="lineno"> 255</span> <span class="comment"> for (vcl_size_t ind = 0; ind < gpu_matrix.internal_maxnnz(); ind++)</span></div>
<div class="line"><a name="l00256"></a><span class="lineno"> 256</span> <span class="comment"> {</span></div>
<div class="line"><a name="l00257"></a><span class="lineno"> 257</span> <span class="comment"> vcl_size_t offset = gpu_matrix.internal_size1() * ind + row;</span></div>
<div class="line"><a name="l00258"></a><span class="lineno"> 258</span> <span class="comment"></span></div>
<div class="line"><a name="l00259"></a><span class="lineno"> 259</span> <span class="comment"> if (elements[offset] == static_cast<NumericT>(0.0))</span></div>
<div class="line"><a name="l00260"></a><span class="lineno"> 260</span> <span class="comment"> continue;</span></div>
<div class="line"><a name="l00261"></a><span class="lineno"> 261</span> <span class="comment"></span></div>
<div class="line"><a name="l00262"></a><span class="lineno"> 262</span> <span class="comment"> if (coords[offset] >= gpu_matrix.size2())</span></div>
<div class="line"><a name="l00263"></a><span class="lineno"> 263</span> <span class="comment"> {</span></div>
<div class="line"><a name="l00264"></a><span class="lineno"> 264</span> <span class="comment"> std::cerr << "ViennaCL encountered invalid data " << offset << " " << ind << " " << row << " " << coords[offset] << " " << gpu_matrix.size2() << std::endl;</span></div>
<div class="line"><a name="l00265"></a><span class="lineno"> 265</span> <span class="comment"> return;</span></div>
<div class="line"><a name="l00266"></a><span class="lineno"> 266</span> <span class="comment"> }</span></div>
<div class="line"><a name="l00267"></a><span class="lineno"> 267</span> <span class="comment"></span></div>
<div class="line"><a name="l00268"></a><span class="lineno"> 268</span> <span class="comment"> cpu_matrix(row, coords[offset]) = elements[offset];</span></div>
<div class="line"><a name="l00269"></a><span class="lineno"> 269</span> <span class="comment"> }</span></div>
<div class="line"><a name="l00270"></a><span class="lineno"> 270</span> <span class="comment"> }</span></div>
<div class="line"><a name="l00271"></a><span class="lineno"> 271</span> <span class="comment"> }</span></div>
<div class="line"><a name="l00272"></a><span class="lineno"> 272</span> <span class="comment">} */</span></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> </div>
<div class="line"><a name="l00275"></a><span class="lineno"> 275</span> <span class="comment">//</span></div>
<div class="line"><a name="l00276"></a><span class="lineno"> 276</span> <span class="comment">// Specify available operations:</span></div>
<div class="line"><a name="l00277"></a><span class="lineno"> 277</span> <span class="comment">//</span></div>
<div class="line"><a name="l00278"></a><span class="lineno"> 278</span> </div>
<div class="line"><a name="l00281"></a><span class="lineno"> 281</span> <span class="keyword">namespace </span>linalg</div>
<div class="line"><a name="l00282"></a><span class="lineno"> 282</span> {</div>
<div class="line"><a name="l00283"></a><span class="lineno"> 283</span> <span class="keyword">namespace </span>detail</div>
<div class="line"><a name="l00284"></a><span class="lineno"> 284</span> {</div>
<div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  <span class="comment">// x = A * y</span></div>
<div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  <span class="keyword">template</span><<span class="keyword">typename</span> ScalarT, <span class="keyword">typename</span> IndexT></div>
<div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  <span class="keyword">struct </span>op_executor<vector_base<ScalarT>, <a class="code" href="structop__assign.html">op_assign</a>, vector_expression<const sliced_ell_matrix<ScalarT, IndexT>, const vector_base<ScalarT>, op_prod> ></div>
<div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  {</div>
<div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  <span class="keyword">static</span> <span class="keywordtype">void</span> apply(vector_base<ScalarT> & lhs, vector_expression<<span class="keyword">const</span> sliced_ell_matrix<ScalarT, IndexT>, <span class="keyword">const</span> vector_base<ScalarT>, op_prod> <span class="keyword">const</span> & rhs)</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>  <span class="comment">// check for the special case x = A * x</span></div>
<div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  <span class="keywordflow">if</span> (<a class="code" href="namespaceviennacl_1_1traits.html#ae39853b7f291a697e119a139439178fb">viennacl::traits::handle</a>(lhs) == <a class="code" href="namespaceviennacl_1_1traits.html#ae39853b7f291a697e119a139439178fb">viennacl::traits::handle</a>(rhs.rhs()))</div>
<div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  {</div>
<div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<ScalarT></a> temp(lhs);</div>
<div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  <a class="code" href="namespaceviennacl_1_1linalg.html#aafc6db8d806f67c24f93eaaded84b853">viennacl::linalg::prod_impl</a>(rhs.lhs(), rhs.rhs(), ScalarT(1), temp, ScalarT(0));</div>
<div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  lhs = temp;</div>
<div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  }</div>
<div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  <a class="code" href="namespaceviennacl_1_1linalg.html#aafc6db8d806f67c24f93eaaded84b853">viennacl::linalg::prod_impl</a>(rhs.lhs(), rhs.rhs(), ScalarT(1), lhs, ScalarT(0));</div>
<div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  }</div>
<div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  };</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>  <span class="keyword">template</span><<span class="keyword">typename</span> ScalarT, <span class="keyword">typename</span> IndexT></div>
<div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  <span class="keyword">struct </span>op_executor<vector_base<ScalarT>, op_inplace_add, vector_expression<const sliced_ell_matrix<ScalarT, IndexT>, const vector_base<ScalarT>, op_prod> ></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>  <span class="keyword">static</span> <span class="keywordtype">void</span> apply(vector_base<ScalarT> & lhs, vector_expression<<span class="keyword">const</span> sliced_ell_matrix<ScalarT, IndexT>, <span class="keyword">const</span> vector_base<ScalarT>, op_prod> <span class="keyword">const</span> & rhs)</div>
<div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  {</div>
<div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  <span class="comment">// check for the special case x += A * x</span></div>
<div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  <span class="keywordflow">if</span> (<a class="code" href="namespaceviennacl_1_1traits.html#ae39853b7f291a697e119a139439178fb">viennacl::traits::handle</a>(lhs) == <a class="code" href="namespaceviennacl_1_1traits.html#ae39853b7f291a697e119a139439178fb">viennacl::traits::handle</a>(rhs.rhs()))</div>
<div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  {</div>
<div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<ScalarT></a> temp(lhs);</div>
<div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  <a class="code" href="namespaceviennacl_1_1linalg.html#aafc6db8d806f67c24f93eaaded84b853">viennacl::linalg::prod_impl</a>(rhs.lhs(), rhs.rhs(), ScalarT(1), temp, ScalarT(0));</div>
<div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  lhs += temp;</div>
<div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  }</div>
<div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  <a class="code" href="namespaceviennacl_1_1linalg.html#aafc6db8d806f67c24f93eaaded84b853">viennacl::linalg::prod_impl</a>(rhs.lhs(), rhs.rhs(), ScalarT(1), lhs, ScalarT(1));</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>  };</div>
<div class="line"><a name="l00319"></a><span class="lineno"> 319</span> </div>
<div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  <span class="keyword">template</span><<span class="keyword">typename</span> ScalarT, <span class="keyword">typename</span> IndexT></div>
<div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  <span class="keyword">struct </span>op_executor<vector_base<ScalarT>, op_inplace_sub, vector_expression<const sliced_ell_matrix<ScalarT, IndexT>, const vector_base<ScalarT>, op_prod> ></div>
<div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  {</div>
<div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  <span class="keyword">static</span> <span class="keywordtype">void</span> apply(vector_base<ScalarT> & lhs, vector_expression<<span class="keyword">const</span> sliced_ell_matrix<ScalarT, IndexT>, <span class="keyword">const</span> vector_base<ScalarT>, op_prod> <span class="keyword">const</span> & rhs)</div>
<div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  {</div>
<div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  <span class="comment">// check for the special case x -= A * x</span></div>
<div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  <span class="keywordflow">if</span> (<a class="code" href="namespaceviennacl_1_1traits.html#ae39853b7f291a697e119a139439178fb">viennacl::traits::handle</a>(lhs) == <a class="code" href="namespaceviennacl_1_1traits.html#ae39853b7f291a697e119a139439178fb">viennacl::traits::handle</a>(rhs.rhs()))</div>
<div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  {</div>
<div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<ScalarT></a> temp(lhs);</div>
<div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  <a class="code" href="namespaceviennacl_1_1linalg.html#aafc6db8d806f67c24f93eaaded84b853">viennacl::linalg::prod_impl</a>(rhs.lhs(), rhs.rhs(), ScalarT(1), temp, ScalarT(0));</div>
<div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  lhs -= temp;</div>
<div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  }</div>
<div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  <a class="code" href="namespaceviennacl_1_1linalg.html#aafc6db8d806f67c24f93eaaded84b853">viennacl::linalg::prod_impl</a>(rhs.lhs(), rhs.rhs(), ScalarT(-1), lhs, ScalarT(1));</div>
<div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  }</div>
<div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  };</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> </div>
<div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  <span class="comment">// x = A * vec_op</span></div>
<div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  <span class="keyword">template</span><<span class="keyword">typename</span> ScalarT, <span class="keyword">typename</span> IndexT, <span class="keyword">typename</span> LHS, <span class="keyword">typename</span> RHS, <span class="keyword">typename</span> OP></div>
<div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  <span class="keyword">struct </span>op_executor<vector_base<ScalarT>, <a class="code" href="structop__assign.html">op_assign</a>, vector_expression<const sliced_ell_matrix<ScalarT, IndexT>, const vector_expression<const LHS, const RHS, OP>, op_prod> ></div>
<div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  {</div>
<div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  <span class="keyword">static</span> <span class="keywordtype">void</span> apply(vector_base<ScalarT> & lhs, vector_expression<<span class="keyword">const</span> sliced_ell_matrix<ScalarT, IndexT>, <span class="keyword">const</span> vector_expression<const LHS, const RHS, OP>, op_prod> <span class="keyword">const</span> & rhs)</div>
<div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  {</div>
<div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<ScalarT></a> temp(rhs.rhs(), <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(rhs));</div>
<div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  <a class="code" href="namespaceviennacl_1_1linalg.html#aafc6db8d806f67c24f93eaaded84b853">viennacl::linalg::prod_impl</a>(rhs.lhs(), temp, lhs);</div>
<div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  }</div>
<div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  };</div>
<div class="line"><a name="l00348"></a><span class="lineno"> 348</span> </div>
<div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  <span class="comment">// x = A * vec_op</span></div>
<div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  <span class="keyword">template</span><<span class="keyword">typename</span> ScalarT, <span class="keyword">typename</span> IndexT, <span class="keyword">typename</span> LHS, <span class="keyword">typename</span> RHS, <span class="keyword">typename</span> OP></div>
<div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  <span class="keyword">struct </span>op_executor<vector_base<ScalarT>, op_inplace_add, vector_expression<const sliced_ell_matrix<ScalarT, IndexT>, const vector_expression<const LHS, const RHS, OP>, op_prod> ></div>
<div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  {</div>
<div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  <span class="keyword">static</span> <span class="keywordtype">void</span> apply(vector_base<ScalarT> & lhs, vector_expression<<span class="keyword">const</span> sliced_ell_matrix<ScalarT, IndexT>, <span class="keyword">const</span> vector_expression<const LHS, const RHS, OP>, op_prod> <span class="keyword">const</span> & rhs)</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_1vector.html">viennacl::vector<ScalarT></a> temp(rhs.rhs(), <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(rhs));</div>
<div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<ScalarT></a> temp_result(lhs);</div>
<div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  <a class="code" href="namespaceviennacl_1_1linalg.html#aafc6db8d806f67c24f93eaaded84b853">viennacl::linalg::prod_impl</a>(rhs.lhs(), temp, temp_result);</div>
<div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  lhs += temp_result;</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>  };</div>
<div class="line"><a name="l00361"></a><span class="lineno"> 361</span> </div>
<div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  <span class="comment">// x = A * vec_op</span></div>
<div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  <span class="keyword">template</span><<span class="keyword">typename</span> ScalarT, <span class="keyword">typename</span> IndexT, <span class="keyword">typename</span> LHS, <span class="keyword">typename</span> RHS, <span class="keyword">typename</span> OP></div>
<div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  <span class="keyword">struct </span>op_executor<vector_base<ScalarT>, op_inplace_sub, vector_expression<const sliced_ell_matrix<ScalarT, IndexT>, const vector_expression<const LHS, const RHS, OP>, op_prod> ></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>  <span class="keyword">static</span> <span class="keywordtype">void</span> apply(vector_base<ScalarT> & lhs, vector_expression<<span class="keyword">const</span> sliced_ell_matrix<ScalarT, IndexT>, <span class="keyword">const</span> vector_expression<const LHS, const RHS, OP>, op_prod> <span class="keyword">const</span> & rhs)</div>
<div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  {</div>
<div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<ScalarT></a> temp(rhs.rhs(), <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(rhs));</div>
<div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<ScalarT></a> temp_result(lhs);</div>
<div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  <a class="code" href="namespaceviennacl_1_1linalg.html#aafc6db8d806f67c24f93eaaded84b853">viennacl::linalg::prod_impl</a>(rhs.lhs(), temp, temp_result);</div>
<div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  lhs -= temp_result;</div>
<div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  }</div>
<div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  };</div>
<div class="line"><a name="l00374"></a><span class="lineno"> 374</span> </div>
<div class="line"><a name="l00375"></a><span class="lineno"> 375</span> } <span class="comment">// namespace detail</span></div>
<div class="line"><a name="l00376"></a><span class="lineno"> 376</span> } <span class="comment">// namespace linalg</span></div>
<div class="line"><a name="l00377"></a><span class="lineno"> 377</span> </div>
<div class="line"><a name="l00379"></a><span class="lineno"> 379</span> }</div>
<div class="line"><a name="l00380"></a><span class="lineno"> 380</span> </div>
<div class="line"><a name="l00381"></a><span class="lineno"> 381</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00382"></a><span class="lineno"> 382</span> </div>
<div class="line"><a name="l00383"></a><span class="lineno"> 383</span> </div>
<div class="ttc" id="classviennacl_1_1sliced__ell__matrix_html_a31d5fa9ec25dcfeb260f7e11c4db6571"><div class="ttname"><a href="classviennacl_1_1sliced__ell__matrix.html#a31d5fa9ec25dcfeb260f7e11c4db6571">viennacl::sliced_ell_matrix::handle2</a></div><div class="ttdeci">handle_type & handle2()</div><div class="ttdef"><b>Definition:</b> <a href="sliced__ell__matrix_8hpp_source.html#l00112">sliced_ell_matrix.hpp:112</a></div></div>
<div class="ttc" id="classviennacl_1_1sliced__ell__matrix_html_ac681e3c8d41b686282711644cbdcadfb"><div class="ttname"><a href="classviennacl_1_1sliced__ell__matrix.html#ac681e3c8d41b686282711644cbdcadfb">viennacl::sliced_ell_matrix::clear</a></div><div class="ttdeci">void clear()</div><div class="ttdoc">Resets all entries in the matrix back to zero without changing the matrix size. Resets the sparsity p...</div><div class="ttdef"><b>Definition:</b> <a href="sliced__ell__matrix_8hpp_source.html#l00085">sliced_ell_matrix.hpp:85</a></div></div>
<div class="ttc" id="classviennacl_1_1sliced__ell__matrix_html_aec497ed037ef674d36729bda4db7e93f"><div class="ttname"><a href="classviennacl_1_1sliced__ell__matrix.html#aec497ed037ef674d36729bda4db7e93f">viennacl::sliced_ell_matrix::handle3</a></div><div class="ttdeci">const handle_type & handle3() const </div><div class="ttdef"><b>Definition:</b> <a href="sliced__ell__matrix_8hpp_source.html#l00116">sliced_ell_matrix.hpp:116</a></div></div>
<div class="ttc" id="classviennacl_1_1backend_1_1typesafe__host__array_html"><div class="ttname"><a href="classviennacl_1_1backend_1_1typesafe__host__array.html">viennacl::backend::typesafe_host_array</a></div><div class="ttdoc">Helper class implementing an array on the host. Default case: No conversion necessary. </div><div class="ttdef"><b>Definition:</b> <a href="backend_2util_8hpp_source.html#l00092">util.hpp:92</a></div></div>
<div class="ttc" id="classviennacl_1_1backend_1_1typesafe__host__array_html_ac8646f4841c47048a1d2e004b9536af8"><div class="ttname"><a href="classviennacl_1_1backend_1_1typesafe__host__array.html#ac8646f4841c47048a1d2e004b9536af8">viennacl::backend::typesafe_host_array::element_size</a></div><div class="ttdeci">vcl_size_t element_size() const </div><div class="ttdef"><b>Definition:</b> <a href="backend_2util_8hpp_source.html#l00112">util.hpp:112</a></div></div>
<div class="ttc" id="classviennacl_1_1sliced__ell__matrix_html_a362dc0c5f0d644cbcf6514f3b3ee6529"><div class="ttname"><a href="classviennacl_1_1sliced__ell__matrix.html#a362dc0c5f0d644cbcf6514f3b3ee6529">viennacl::sliced_ell_matrix::sliced_ell_matrix</a></div><div class="ttdeci">sliced_ell_matrix()</div><div class="ttdef"><b>Definition:</b> <a href="sliced__ell__matrix_8hpp_source.html#l00053">sliced_ell_matrix.hpp:53</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="classviennacl_1_1sliced__ell__matrix_html_adf0fb80bb38ab0256a622960c0c18699"><div class="ttname"><a href="classviennacl_1_1sliced__ell__matrix.html#adf0fb80bb38ab0256a622960c0c18699">viennacl::sliced_ell_matrix::size_type</a></div><div class="ttdeci">vcl_size_t size_type</div><div class="ttdef"><b>Definition:</b> <a href="sliced__ell__matrix_8hpp_source.html#l00051">sliced_ell_matrix.hpp:51</a></div></div>
<div class="ttc" id="classviennacl_1_1backend_1_1typesafe__host__array_html_a3943ea09faa2df9b7bee130d3a2d5f20"><div class="ttname"><a href="classviennacl_1_1backend_1_1typesafe__host__array.html#a3943ea09faa2df9b7bee130d3a2d5f20">viennacl::backend::typesafe_host_array::size</a></div><div class="ttdeci">vcl_size_t size() const </div><div class="ttdef"><b>Definition:</b> <a href="backend_2util_8hpp_source.html#l00113">util.hpp:113</a></div></div>
<div class="ttc" id="classviennacl_1_1sliced__ell__matrix_html_a727fd3a25232545c59204885ff3e32d4"><div class="ttname"><a href="classviennacl_1_1sliced__ell__matrix.html#a727fd3a25232545c59204885ff3e32d4">viennacl::sliced_ell_matrix::handle1</a></div><div class="ttdeci">const handle_type & handle1() const </div><div class="ttdef"><b>Definition:</b> <a href="sliced__ell__matrix_8hpp_source.html#l00110">sliced_ell_matrix.hpp:110</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="namespaceviennacl_1_1traits_html_aa756f5d6820722094cae0d8b9bb6d5e2"><div class="ttname"><a href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">viennacl::traits::size1</a></div><div class="ttdeci">vcl_size_t size1(MatrixType const &mat)</div><div class="ttdoc">Generic routine for obtaining the number of rows of a matrix (ViennaCL, uBLAS, etc.) </div><div class="ttdef"><b>Definition:</b> <a href="size_8hpp_source.html#l00163">size.hpp:163</a></div></div>
<div class="ttc" id="namespaceviennacl_html_a00b40450b6b2fd87aad3527d9b2084b8adb37af613f34867568e4f6cf720c68b1"><div class="ttname"><a href="namespaceviennacl.html#a00b40450b6b2fd87aad3527d9b2084b8adb37af613f34867568e4f6cf720c68b1">viennacl::OPENCL_MEMORY</a></div><div class="ttdef"><b>Definition:</b> <a href="forwards_8h_source.html#l00349">forwards.h:349</a></div></div>
<div class="ttc" id="classviennacl_1_1sliced__ell__matrix_html_a45249ad5b44d0f506adc27e1e18aecdf"><div class="ttname"><a href="classviennacl_1_1sliced__ell__matrix.html#a45249ad5b44d0f506adc27e1e18aecdf">viennacl::sliced_ell_matrix::handle2</a></div><div class="ttdeci">const handle_type & handle2() const </div><div class="ttdef"><b>Definition:</b> <a href="sliced__ell__matrix_8hpp_source.html#l00113">sliced_ell_matrix.hpp:113</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="classviennacl_1_1backend_1_1typesafe__host__array_html_a1727eeb845f50cf5bd51ef54c5938b8c"><div class="ttname"><a href="classviennacl_1_1backend_1_1typesafe__host__array.html#a1727eeb845f50cf5bd51ef54c5938b8c">viennacl::backend::typesafe_host_array::get</a></div><div class="ttdeci">void * get()</div><div class="ttdef"><b>Definition:</b> <a href="backend_2util_8hpp_source.html#l00110">util.hpp:110</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_1sliced__ell__matrix_html_aa9a7f4003687cae9a2af97f9fa328db5"><div class="ttname"><a href="classviennacl_1_1sliced__ell__matrix.html#aa9a7f4003687cae9a2af97f9fa328db5">viennacl::sliced_ell_matrix::rows_per_block</a></div><div class="ttdeci">vcl_size_t rows_per_block() const </div><div class="ttdef"><b>Definition:</b> <a href="sliced__ell__matrix_8hpp_source.html#l00104">sliced_ell_matrix.hpp:104</a></div></div>
<div class="ttc" id="classviennacl_1_1sliced__ell__matrix_html_a40c479e880ef7e7f50ed67cda91bb8e7"><div class="ttname"><a href="classviennacl_1_1sliced__ell__matrix.html#a40c479e880ef7e7f50ed67cda91bb8e7">viennacl::sliced_ell_matrix::copy</a></div><div class="ttdeci">friend void copy(CPUMatrixT const &cpu_matrix, sliced_ell_matrix< ScalarT2, IndexT2 > &gpu_matrix)</div></div>
<div class="ttc" id="classviennacl_1_1sliced__ell__matrix_html_af0672b686ad27ddcf948116bae059329"><div class="ttname"><a href="classviennacl_1_1sliced__ell__matrix.html#af0672b686ad27ddcf948116bae059329">viennacl::sliced_ell_matrix::value_type</a></div><div class="ttdeci">scalar< typename viennacl::tools::CHECK_SCALAR_TEMPLATE_ARGUMENT< ScalarT >::ResultType > value_type</div><div class="ttdef"><b>Definition:</b> <a href="sliced__ell__matrix_8hpp_source.html#l00050">sliced_ell_matrix.hpp:50</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1traits_html_a3658e7c29ac0f60a20cb5871f5b5fd98"><div class="ttname"><a href="namespaceviennacl_1_1traits.html#a3658e7c29ac0f60a20cb5871f5b5fd98">viennacl::traits::size2</a></div><div class="ttdeci">result_of::size_type< MatrixType >::type size2(MatrixType const &mat)</div><div class="ttdoc">Generic routine for obtaining the number of columns of a matrix (ViennaCL, uBLAS, etc...</div><div class="ttdef"><b>Definition:</b> <a href="size_8hpp_source.html#l00201">size.hpp:201</a></div></div>
<div class="ttc" id="classviennacl_1_1sliced__ell__matrix_html_abbc671358c44037b7c2b22a01f17c3a7"><div class="ttname"><a href="classviennacl_1_1sliced__ell__matrix.html#abbc671358c44037b7c2b22a01f17c3a7">viennacl::sliced_ell_matrix::handle</a></div><div class="ttdeci">handle_type & handle()</div><div class="ttdef"><b>Definition:</b> <a href="sliced__ell__matrix_8hpp_source.html#l00118">sliced_ell_matrix.hpp:118</a></div></div>
<div class="ttc" id="classviennacl_1_1context_html"><div class="ttname"><a href="classviennacl_1_1context.html">viennacl::context</a></div><div class="ttdoc">Represents a generic 'context' similar to an OpenCL context, but is backend-agnostic and thus also su...</div><div class="ttdef"><b>Definition:</b> <a href="context_8hpp_source.html#l00039">context.hpp:39</a></div></div>
<div class="ttc" id="classviennacl_1_1sliced__ell__matrix_html_aa725bf2d5b213f119bd4b9fe9258c201"><div class="ttname"><a href="classviennacl_1_1sliced__ell__matrix.html#aa725bf2d5b213f119bd4b9fe9258c201">viennacl::sliced_ell_matrix::sliced_ell_matrix</a></div><div class="ttdeci">sliced_ell_matrix(viennacl::context ctx)</div><div class="ttdef"><b>Definition:</b> <a href="sliced__ell__matrix_8hpp_source.html#l00066">sliced_ell_matrix.hpp:66</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="classviennacl_1_1sliced__ell__matrix_html"><div class="ttname"><a href="classviennacl_1_1sliced__ell__matrix.html">viennacl::sliced_ell_matrix</a></div><div class="ttdoc">Sparse matrix class using the sliced ELLPACK with parameters C, . </div><div class="ttdef"><b>Definition:</b> <a href="forwards_8h_source.html#l00403">forwards.h:403</a></div></div>
<div class="ttc" id="sparse__matrix__operations_8hpp_html"><div class="ttname"><a href="sparse__matrix__operations_8hpp.html">sparse_matrix_operations.hpp</a></div><div class="ttdoc">Implementations of operations using sparse matrices. </div></div>
<div class="ttc" id="classviennacl_1_1tools_1_1const__sparse__matrix__adapter_html"><div class="ttname"><a href="classviennacl_1_1tools_1_1const__sparse__matrix__adapter.html">viennacl::tools::const_sparse_matrix_adapter</a></div><div class="ttdoc">Adapts a constant sparse matrix type made up from std::vector<std::map<SizeT, NumericT> > to basic ub...</div><div class="ttdef"><b>Definition:</b> <a href="adapter_8hpp_source.html#l00183">adapter.hpp:183</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_1sliced__ell__matrix_html_a16cd8194ca5b263de32f131362498d77"><div class="ttname"><a href="classviennacl_1_1sliced__ell__matrix.html#a16cd8194ca5b263de32f131362498d77">viennacl::sliced_ell_matrix::size1</a></div><div class="ttdeci">vcl_size_t size1() const </div><div class="ttdef"><b>Definition:</b> <a href="sliced__ell__matrix_8hpp_source.html#l00101">sliced_ell_matrix.hpp:101</a></div></div>
<div class="ttc" id="classviennacl_1_1sliced__ell__matrix_html_a9f244082eff24e93495d3b4abec735b0"><div class="ttname"><a href="classviennacl_1_1sliced__ell__matrix.html#a9f244082eff24e93495d3b4abec735b0">viennacl::sliced_ell_matrix::sliced_ell_matrix</a></div><div class="ttdeci">sliced_ell_matrix(size_type num_rows, size_type num_cols, size_type num_rows_per_block_=0)</div><div class="ttdoc">Standard constructor for setting the row and column sizes as well as the block size. </div><div class="ttdef"><b>Definition:</b> <a href="sliced__ell__matrix_8hpp_source.html#l00059">sliced_ell_matrix.hpp:59</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="classviennacl_1_1context_html_aadf575d49ed144e8fa4707cdad69c349"><div class="ttname"><a href="classviennacl_1_1context.html#aadf575d49ed144e8fa4707cdad69c349">viennacl::context::memory_type</a></div><div class="ttdeci">viennacl::memory_types memory_type() const </div><div class="ttdef"><b>Definition:</b> <a href="context_8hpp_source.html#l00076">context.hpp:76</a></div></div>
<div class="ttc" id="classviennacl_1_1sliced__ell__matrix_html_a1b9a6e9229a8694123562166eb2d4e32"><div class="ttname"><a href="classviennacl_1_1sliced__ell__matrix.html#a1b9a6e9229a8694123562166eb2d4e32">viennacl::sliced_ell_matrix::handle</a></div><div class="ttdeci">const handle_type & handle() const </div><div class="ttdef"><b>Definition:</b> <a href="sliced__ell__matrix_8hpp_source.html#l00119">sliced_ell_matrix.hpp:119</a></div></div>
<div class="ttc" id="classviennacl_1_1sliced__ell__matrix_html_ad4fd3359611ca475b85d2041bdec1377"><div class="ttname"><a href="classviennacl_1_1sliced__ell__matrix.html#ad4fd3359611ca475b85d2041bdec1377">viennacl::sliced_ell_matrix::internal_size2</a></div><div class="ttdeci">vcl_size_t internal_size2() const </div><div class="ttdef"><b>Definition:</b> <a href="sliced__ell__matrix_8hpp_source.html#l00099">sliced_ell_matrix.hpp:99</a></div></div>
<div class="ttc" id="classviennacl_1_1backend_1_1mem__handle_html_ac13e99f562746d6682116dec1e13a7da"><div class="ttname"><a href="classviennacl_1_1backend_1_1mem__handle.html#ac13e99f562746d6682116dec1e13a7da">viennacl::backend::mem_handle::switch_active_handle_id</a></div><div class="ttdeci">void switch_active_handle_id(memory_types new_id)</div><div class="ttdoc">Switches the currently active handle. If no support for that backend is provided, an exception is thr...</div><div class="ttdef"><b>Definition:</b> <a href="mem__handle_8hpp_source.html#l00121">mem_handle.hpp:121</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="vector_8hpp_html"><div class="ttname"><a href="vector_8hpp.html">vector.hpp</a></div><div class="ttdoc">The vector type with operator-overloads and proxy classes is defined here. Linear algebra operations ...</div></div>
<div class="ttc" id="classviennacl_1_1sliced__ell__matrix_html_aa59ae796d592a679a4c6036ba84f61b0"><div class="ttname"><a href="classviennacl_1_1sliced__ell__matrix.html#aa59ae796d592a679a4c6036ba84f61b0">viennacl::sliced_ell_matrix::handle3</a></div><div class="ttdeci">handle_type & handle3()</div><div class="ttdef"><b>Definition:</b> <a href="sliced__ell__matrix_8hpp_source.html#l00115">sliced_ell_matrix.hpp:115</a></div></div>
<div class="ttc" id="namespaceviennacl_html_a10b7f8cf6b8864a7aa196d670481a453"><div class="ttname"><a href="namespaceviennacl.html#a10b7f8cf6b8864a7aa196d670481a453">viennacl::copy</a></div><div class="ttdeci">void copy(std::vector< NumericT > &cpu_vec, circulant_matrix< NumericT, AlignmentV > &gpu_mat)</div><div class="ttdoc">Copies a circulant matrix from the std::vector to the OpenCL device (either GPU or multi-core CPU) ...</div><div class="ttdef"><b>Definition:</b> <a href="circulant__matrix_8hpp_source.html#l00150">circulant_matrix.hpp:150</a></div></div>
<div class="ttc" id="classviennacl_1_1backend_1_1typesafe__host__array_html_ac31bfde381eb40e0349678252c444af9"><div class="ttname"><a href="classviennacl_1_1backend_1_1typesafe__host__array.html#ac31bfde381eb40e0349678252c444af9">viennacl::backend::typesafe_host_array::set</a></div><div class="ttdeci">void set(vcl_size_t index, U value)</div><div class="ttdef"><b>Definition:</b> <a href="backend_2util_8hpp_source.html#l00115">util.hpp:115</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="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="namespaceviennacl_1_1linalg_html_aafc6db8d806f67c24f93eaaded84b853"><div class="ttname"><a href="namespaceviennacl_1_1linalg.html#aafc6db8d806f67c24f93eaaded84b853">viennacl::linalg::prod_impl</a></div><div class="ttdeci">void prod_impl(const matrix_base< NumericT > &mat, const vector_base< NumericT > &vec, vector_base< NumericT > &result)</div><div class="ttdoc">Carries out matrix-vector multiplication. </div><div class="ttdef"><b>Definition:</b> <a href="matrix__operations_8hpp_source.html#l00438">matrix_operations.hpp:438</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1traits_html_ae39853b7f291a697e119a139439178fb"><div class="ttname"><a href="namespaceviennacl_1_1traits.html#ae39853b7f291a697e119a139439178fb">viennacl::traits::handle</a></div><div class="ttdeci">viennacl::backend::mem_handle & handle(T &obj)</div><div class="ttdoc">Returns the generic memory handle of an object. Non-const version. </div><div class="ttdef"><b>Definition:</b> <a href="traits_2handle_8hpp_source.html#l00041">handle.hpp:41</a></div></div>
<div class="ttc" id="classviennacl_1_1sliced__ell__matrix_html_ae0afefc19f6dc7692a87cd8a16b51d30"><div class="ttname"><a href="classviennacl_1_1sliced__ell__matrix.html#ae0afefc19f6dc7692a87cd8a16b51d30">viennacl::sliced_ell_matrix::size2</a></div><div class="ttdeci">vcl_size_t size2() const </div><div class="ttdef"><b>Definition:</b> <a href="sliced__ell__matrix_8hpp_source.html#l00102">sliced_ell_matrix.hpp:102</a></div></div>
<div class="ttc" id="classviennacl_1_1sliced__ell__matrix_html_ab8a2233384ac8dcdb85b5385706548a1"><div class="ttname"><a href="classviennacl_1_1sliced__ell__matrix.html#ab8a2233384ac8dcdb85b5385706548a1">viennacl::sliced_ell_matrix::internal_size1</a></div><div class="ttdeci">vcl_size_t internal_size1() const </div><div class="ttdef"><b>Definition:</b> <a href="sliced__ell__matrix_8hpp_source.html#l00098">sliced_ell_matrix.hpp:98</a></div></div>
<div class="ttc" id="classviennacl_1_1sliced__ell__matrix_html_a94043424c01974b2db8062f74f625825"><div class="ttname"><a href="classviennacl_1_1sliced__ell__matrix.html#a94043424c01974b2db8062f74f625825">viennacl::sliced_ell_matrix::handle1</a></div><div class="ttdeci">handle_type & handle1()</div><div class="ttdef"><b>Definition:</b> <a href="sliced__ell__matrix_8hpp_source.html#l00109">sliced_ell_matrix.hpp:109</a></div></div>
<div class="ttc" id="classviennacl_1_1sliced__ell__matrix_html_a2cdf3aeccfe9a10b89c48b3430cb4c93"><div class="ttname"><a href="classviennacl_1_1sliced__ell__matrix.html#a2cdf3aeccfe9a10b89c48b3430cb4c93">viennacl::sliced_ell_matrix::handle_type</a></div><div class="ttdeci">viennacl::backend::mem_handle handle_type</div><div class="ttdef"><b>Definition:</b> <a href="sliced__ell__matrix_8hpp_source.html#l00049">sliced_ell_matrix.hpp:49</a></div></div>
<div class="ttc" id="structop__assign_html"><div class="ttname"><a href="structop__assign.html">op_assign</a></div><div class="ttdef"><b>Definition:</b> <a href="self__assign_8cpp_source.html#l00132">self_assign.cpp:132</a></div></div>
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