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
|
#include <iostream>
#define BOOST_TEST_MAIN
#include <boost/test/included/unit_test.hpp>
#include <boost/test/floating_point_comparison.hpp>
#include <cmath>
#include "../simd_mix.hpp"
#include "test_helper.hpp"
#include "../benchmarks/cache_aligned_array.hpp"
using namespace nova;
using namespace std;
static const int size = 512;
template <typename float_type>
void test_mix(void)
{
aligned_array<float_type, size> sseval, mpval, generic, args0, args1;
randomize_buffer<float_type>(args0.c_array(), size);
randomize_buffer<float_type>(args1.c_array(), size);
float_type factor0 = 0.4;
float_type factor1 = 0.6;
mix_vec(generic.c_array(), args0.c_array(), factor0, args1.c_array(), factor1, size);
mix_vec_simd(sseval.c_array(), args0.c_array(), factor0, args1.c_array(), factor1, size);
mix_vec_simd<size>(mpval.c_array(), args0.c_array(), factor0, args1.c_array(), factor1);
for (int i = 0; i != size; ++i) {
BOOST_CHECK_CLOSE( sseval[i], generic[i], 0.0001 );
BOOST_CHECK_CLOSE( mpval[i], generic[i], 0.0001 );
}
}
BOOST_AUTO_TEST_CASE( mix_tests )
{
test_mix<float>();
test_mix<double>();
}
template <typename float_type>
void test_mix_ramp(void)
{
aligned_array<float_type, size> sseval, mpval, generic, args0, args1;
randomize_buffer<float_type>(args0.c_array(), size);
randomize_buffer<float_type>(args1.c_array(), size);
float_type factor0 = 0.4; float_type slope0 = 0.1/size;
float_type factor1 = 0.6; float_type slope1 = -0.1/size;
mix_vec(generic.c_array(), args0.c_array(), slope_argument(factor0, slope0), args1.c_array(), slope_argument(factor1, slope1), size);
mix_vec_simd(sseval.c_array(), args0.c_array(), slope_argument(factor0, slope0), args1.c_array(), slope_argument(factor1, slope1), size);
mix_vec_simd<size>(mpval.c_array(), args0.c_array(), slope_argument(factor0, slope0), args1.c_array(), slope_argument(factor1, slope1));
for (int i = 0; i != size; ++i) {
BOOST_CHECK_CLOSE( sseval[i], generic[i], 0.5 );
BOOST_CHECK_CLOSE( mpval[i], generic[i], 0.5 );
}
}
BOOST_AUTO_TEST_CASE( mix_ramp_tests )
{
test_mix_ramp<float>();
test_mix_ramp<double>();
}
template <typename float_type>
void test_sum(void)
{
aligned_array<float_type, size> sseval, mpval, generic, args0, args1;
randomize_buffer<float_type>(args0.c_array(), size);
randomize_buffer<float_type>(args1.c_array(), size);
sum_vec(generic.c_array(), args0.c_array(), args1.c_array(), size);
sum_vec_simd(sseval.c_array(), args0.c_array(), args1.c_array(), size);
sum_vec_simd<size>(mpval.c_array(), args0.c_array(), args1.c_array());
for (int i = 0; i != size; ++i) {
BOOST_CHECK_CLOSE( sseval[i], generic[i], 0.0001 );
BOOST_CHECK_CLOSE( mpval[i], generic[i], 0.0001 );
}
}
template <typename float_type>
void test_sum3(void)
{
aligned_array<float_type, size> sseval, mpval, generic, args0, args1, args2;
randomize_buffer<float_type>(args0.c_array(), size);
randomize_buffer<float_type>(args1.c_array(), size);
randomize_buffer<float_type>(args2.c_array(), size);
sum_vec(generic.c_array(), args0.c_array(), args1.c_array(), args2.c_array(), size);
sum_vec_simd(sseval.c_array(), args0.c_array(), args1.c_array(), args2.c_array(), size);
sum_vec_simd<size>(mpval.c_array(), args0.c_array(), args1.c_array(), args2.c_array());
for (int i = 0; i != size; ++i) {
BOOST_CHECK_CLOSE( sseval[i], generic[i], 0.0001 );
BOOST_CHECK_CLOSE( mpval[i], generic[i], 0.0001 );
}
}
template <typename float_type>
void test_sum4(void)
{
aligned_array<float_type, size> sseval, mpval, generic, args0, args1, args2, args3;
randomize_buffer<float_type>(args0.c_array(), size);
randomize_buffer<float_type>(args1.c_array(), size);
randomize_buffer<float_type>(args2.c_array(), size);
randomize_buffer<float_type>(args3.c_array(), size);
sum_vec(generic.c_array(), args0.c_array(), args1.c_array(), args2.c_array(), args3.c_array(), size);
sum_vec_simd(sseval.c_array(), args0.c_array(), args1.c_array(), args2.c_array(), args3.c_array(), size);
sum_vec_simd<size>(mpval.c_array(), args0.c_array(), args1.c_array(), args2.c_array(), args3.c_array());
for (int i = 0; i != size; ++i) {
BOOST_CHECK_CLOSE( sseval[i], generic[i], 0.0001 );
BOOST_CHECK_CLOSE( mpval[i], generic[i], 0.0001 );
}
}
BOOST_AUTO_TEST_CASE( sum_tests )
{
test_sum<float>();
test_sum<double>();
test_sum3<float>();
test_sum3<double>();
test_sum4<float>();
test_sum4<double>();
}
|
