Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 1 | |
| 2 | #include <iostream> |
| 3 | #include <Eigen/Core> |
| 4 | #include <bench/BenchTimer.h> |
| 5 | using namespace Eigen; |
| 6 | |
| 7 | #ifndef SIZE |
| 8 | #define SIZE 50 |
| 9 | #endif |
| 10 | |
| 11 | #ifndef REPEAT |
| 12 | #define REPEAT 10000 |
| 13 | #endif |
| 14 | |
| 15 | typedef 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 | |
| 21 | int 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 | |
| 79 | void benchVec(MatrixXf& a, MatrixXf& b, MatrixXf& c) |
| 80 | { |
| 81 | for (int k=0; k<REPEAT; ++k) |
| 82 | a = a + b; |
| 83 | } |
| 84 | |
| 85 | void benchVec(VectorXf& a, VectorXf& b, VectorXf& c) |
| 86 | { |
| 87 | for (int k=0; k<REPEAT; ++k) |
| 88 | a = a + b; |
| 89 | } |
| 90 | |
| 91 | void 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 | } |