source: pacpussensors/trunk/Vislab/lib3dv-1.2.0/lib3dv/eigen/bench/benchVecAdd.cpp@ 148

Last change on this file since 148 was 136, checked in by ldecherf, 8 years ago

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1
2#include <iostream>
3#include <Eigen/Core>
4#include <bench/BenchTimer.h>
5using namespace Eigen;
6
7#ifndef SIZE
8#define SIZE 50
9#endif
10
11#ifndef REPEAT
12#define REPEAT 10000
13#endif
14
15typedef float Scalar;
16
17__attribute__ ((noinline)) void benchVec(Scalar* a, Scalar* b, Scalar* c, int size);
18__attribute__ ((noinline)) void benchVec(MatrixXf& a, MatrixXf& b, MatrixXf& c);
19__attribute__ ((noinline)) void benchVec(VectorXf& a, VectorXf& b, VectorXf& c);
20
21int main(int argc, char* argv[])
22{
23 int size = SIZE * 8;
24 int size2 = size * size;
25 Scalar* a = internal::aligned_new<Scalar>(size2);
26 Scalar* b = internal::aligned_new<Scalar>(size2+4)+1;
27 Scalar* c = internal::aligned_new<Scalar>(size2);
28
29 for (int i=0; i<size; ++i)
30 {
31 a[i] = b[i] = c[i] = 0;
32 }
33
34 BenchTimer timer;
35
36 timer.reset();
37 for (int k=0; k<10; ++k)
38 {
39 timer.start();
40 benchVec(a, b, c, size2);
41 timer.stop();
42 }
43 std::cout << timer.value() << "s " << (double(size2*REPEAT)/timer.value())/(1024.*1024.*1024.) << " GFlops\n";
44 return 0;
45 for (int innersize = size; innersize>2 ; --innersize)
46 {
47 if (size2%innersize==0)
48 {
49 int outersize = size2/innersize;
50 MatrixXf ma = Map<MatrixXf>(a, innersize, outersize );
51 MatrixXf mb = Map<MatrixXf>(b, innersize, outersize );
52 MatrixXf mc = Map<MatrixXf>(c, innersize, outersize );
53 timer.reset();
54 for (int k=0; k<3; ++k)
55 {
56 timer.start();
57 benchVec(ma, mb, mc);
58 timer.stop();
59 }
60 std::cout << innersize << " x " << outersize << " " << timer.value() << "s " << (double(size2*REPEAT)/timer.value())/(1024.*1024.*1024.) << " GFlops\n";
61 }
62 }
63
64 VectorXf va = Map<VectorXf>(a, size2);
65 VectorXf vb = Map<VectorXf>(b, size2);
66 VectorXf vc = Map<VectorXf>(c, size2);
67 timer.reset();
68 for (int k=0; k<3; ++k)
69 {
70 timer.start();
71 benchVec(va, vb, vc);
72 timer.stop();
73 }
74 std::cout << timer.value() << "s " << (double(size2*REPEAT)/timer.value())/(1024.*1024.*1024.) << " GFlops\n";
75
76 return 0;
77}
78
79void benchVec(MatrixXf& a, MatrixXf& b, MatrixXf& c)
80{
81 for (int k=0; k<REPEAT; ++k)
82 a = a + b;
83}
84
85void benchVec(VectorXf& a, VectorXf& b, VectorXf& c)
86{
87 for (int k=0; k<REPEAT; ++k)
88 a = a + b;
89}
90
91void benchVec(Scalar* a, Scalar* b, Scalar* c, int size)
92{
93 typedef internal::packet_traits<Scalar>::type PacketScalar;
94 const int PacketSize = internal::packet_traits<Scalar>::size;
95 PacketScalar a0, a1, a2, a3, b0, b1, b2, b3;
96 for (int k=0; k<REPEAT; ++k)
97 for (int i=0; i<size; i+=PacketSize*8)
98 {
99// a0 = internal::pload(&a[i]);
100// b0 = internal::pload(&b[i]);
101// a1 = internal::pload(&a[i+1*PacketSize]);
102// b1 = internal::pload(&b[i+1*PacketSize]);
103// a2 = internal::pload(&a[i+2*PacketSize]);
104// b2 = internal::pload(&b[i+2*PacketSize]);
105// a3 = internal::pload(&a[i+3*PacketSize]);
106// b3 = internal::pload(&b[i+3*PacketSize]);
107// internal::pstore(&a[i], internal::padd(a0, b0));
108// a0 = internal::pload(&a[i+4*PacketSize]);
109// b0 = internal::pload(&b[i+4*PacketSize]);
110//
111// internal::pstore(&a[i+1*PacketSize], internal::padd(a1, b1));
112// a1 = internal::pload(&a[i+5*PacketSize]);
113// b1 = internal::pload(&b[i+5*PacketSize]);
114//
115// internal::pstore(&a[i+2*PacketSize], internal::padd(a2, b2));
116// a2 = internal::pload(&a[i+6*PacketSize]);
117// b2 = internal::pload(&b[i+6*PacketSize]);
118//
119// internal::pstore(&a[i+3*PacketSize], internal::padd(a3, b3));
120// a3 = internal::pload(&a[i+7*PacketSize]);
121// b3 = internal::pload(&b[i+7*PacketSize]);
122//
123// internal::pstore(&a[i+4*PacketSize], internal::padd(a0, b0));
124// internal::pstore(&a[i+5*PacketSize], internal::padd(a1, b1));
125// internal::pstore(&a[i+6*PacketSize], internal::padd(a2, b2));
126// internal::pstore(&a[i+7*PacketSize], internal::padd(a3, b3));
127
128 internal::pstore(&a[i+2*PacketSize], internal::padd(internal::ploadu(&a[i+2*PacketSize]), internal::ploadu(&b[i+2*PacketSize])));
129 internal::pstore(&a[i+3*PacketSize], internal::padd(internal::ploadu(&a[i+3*PacketSize]), internal::ploadu(&b[i+3*PacketSize])));
130 internal::pstore(&a[i+4*PacketSize], internal::padd(internal::ploadu(&a[i+4*PacketSize]), internal::ploadu(&b[i+4*PacketSize])));
131 internal::pstore(&a[i+5*PacketSize], internal::padd(internal::ploadu(&a[i+5*PacketSize]), internal::ploadu(&b[i+5*PacketSize])));
132 internal::pstore(&a[i+6*PacketSize], internal::padd(internal::ploadu(&a[i+6*PacketSize]), internal::ploadu(&b[i+6*PacketSize])));
133 internal::pstore(&a[i+7*PacketSize], internal::padd(internal::ploadu(&a[i+7*PacketSize]), internal::ploadu(&b[i+7*PacketSize])));
134 }
135}
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