132 lines
5.4 KiB
C++
132 lines
5.4 KiB
C++
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#include <iostream>
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#include <Eigen/Core>
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#include <bench/BenchTimer.h>
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using namespace Eigen;
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#ifndef SIZE
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#define SIZE 50
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#endif
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#ifndef REPEAT
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#define REPEAT 10000
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#endif
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typedef float Scalar;
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__attribute__((noinline)) void benchVec(Scalar* a, Scalar* b, Scalar* c, int size);
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__attribute__((noinline)) void benchVec(MatrixXf& a, MatrixXf& b, MatrixXf& c);
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__attribute__((noinline)) void benchVec(VectorXf& a, VectorXf& b, VectorXf& c);
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int main(int argc, char* argv[]) {
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int size = SIZE * 8;
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int size2 = size * size;
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Scalar* a = internal::aligned_new<Scalar>(size2);
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Scalar* b = internal::aligned_new<Scalar>(size2 + 4) + 1;
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Scalar* c = internal::aligned_new<Scalar>(size2);
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for (int i = 0; i < size; ++i) {
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a[i] = b[i] = c[i] = 0;
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}
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BenchTimer timer;
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timer.reset();
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for (int k = 0; k < 10; ++k) {
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timer.start();
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benchVec(a, b, c, size2);
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timer.stop();
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}
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std::cout << timer.value() << "s " << (double(size2 * REPEAT) / timer.value()) / (1024. * 1024. * 1024.)
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<< " GFlops\n";
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return 0;
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for (int innersize = size; innersize > 2; --innersize) {
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if (size2 % innersize == 0) {
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int outersize = size2 / innersize;
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MatrixXf ma = Map<MatrixXf>(a, innersize, outersize);
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MatrixXf mb = Map<MatrixXf>(b, innersize, outersize);
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MatrixXf mc = Map<MatrixXf>(c, innersize, outersize);
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timer.reset();
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for (int k = 0; k < 3; ++k) {
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timer.start();
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benchVec(ma, mb, mc);
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timer.stop();
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}
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std::cout << innersize << " x " << outersize << " " << timer.value() << "s "
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<< (double(size2 * REPEAT) / timer.value()) / (1024. * 1024. * 1024.) << " GFlops\n";
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}
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}
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VectorXf va = Map<VectorXf>(a, size2);
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VectorXf vb = Map<VectorXf>(b, size2);
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VectorXf vc = Map<VectorXf>(c, size2);
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timer.reset();
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for (int k = 0; k < 3; ++k) {
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timer.start();
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benchVec(va, vb, vc);
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timer.stop();
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}
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std::cout << timer.value() << "s " << (double(size2 * REPEAT) / timer.value()) / (1024. * 1024. * 1024.)
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<< " GFlops\n";
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return 0;
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}
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void benchVec(MatrixXf& a, MatrixXf& b, MatrixXf& c) {
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for (int k = 0; k < REPEAT; ++k) a = a + b;
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}
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void benchVec(VectorXf& a, VectorXf& b, VectorXf& c) {
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for (int k = 0; k < REPEAT; ++k) a = a + b;
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}
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void benchVec(Scalar* a, Scalar* b, Scalar* c, int size) {
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typedef internal::packet_traits<Scalar>::type PacketScalar;
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const int PacketSize = internal::packet_traits<Scalar>::size;
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PacketScalar a0, a1, a2, a3, b0, b1, b2, b3;
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for (int k = 0; k < REPEAT; ++k)
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for (int i = 0; i < size; i += PacketSize * 8) {
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// a0 = internal::pload(&a[i]);
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// b0 = internal::pload(&b[i]);
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// a1 = internal::pload(&a[i+1*PacketSize]);
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// b1 = internal::pload(&b[i+1*PacketSize]);
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// a2 = internal::pload(&a[i+2*PacketSize]);
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// b2 = internal::pload(&b[i+2*PacketSize]);
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// a3 = internal::pload(&a[i+3*PacketSize]);
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// b3 = internal::pload(&b[i+3*PacketSize]);
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// internal::pstore(&a[i], internal::padd(a0, b0));
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// a0 = internal::pload(&a[i+4*PacketSize]);
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// b0 = internal::pload(&b[i+4*PacketSize]);
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//
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// internal::pstore(&a[i+1*PacketSize], internal::padd(a1, b1));
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// a1 = internal::pload(&a[i+5*PacketSize]);
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// b1 = internal::pload(&b[i+5*PacketSize]);
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//
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// internal::pstore(&a[i+2*PacketSize], internal::padd(a2, b2));
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// a2 = internal::pload(&a[i+6*PacketSize]);
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// b2 = internal::pload(&b[i+6*PacketSize]);
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//
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// internal::pstore(&a[i+3*PacketSize], internal::padd(a3, b3));
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// a3 = internal::pload(&a[i+7*PacketSize]);
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// b3 = internal::pload(&b[i+7*PacketSize]);
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//
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// internal::pstore(&a[i+4*PacketSize], internal::padd(a0, b0));
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// internal::pstore(&a[i+5*PacketSize], internal::padd(a1, b1));
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// internal::pstore(&a[i+6*PacketSize], internal::padd(a2, b2));
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// internal::pstore(&a[i+7*PacketSize], internal::padd(a3, b3));
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internal::pstore(&a[i + 2 * PacketSize], internal::padd(internal::ploadu(&a[i + 2 * PacketSize]),
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internal::ploadu(&b[i + 2 * PacketSize])));
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internal::pstore(&a[i + 3 * PacketSize], internal::padd(internal::ploadu(&a[i + 3 * PacketSize]),
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internal::ploadu(&b[i + 3 * PacketSize])));
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internal::pstore(&a[i + 4 * PacketSize], internal::padd(internal::ploadu(&a[i + 4 * PacketSize]),
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internal::ploadu(&b[i + 4 * PacketSize])));
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internal::pstore(&a[i + 5 * PacketSize], internal::padd(internal::ploadu(&a[i + 5 * PacketSize]),
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internal::ploadu(&b[i + 5 * PacketSize])));
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internal::pstore(&a[i + 6 * PacketSize], internal::padd(internal::ploadu(&a[i + 6 * PacketSize]),
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internal::ploadu(&b[i + 6 * PacketSize])));
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internal::pstore(&a[i + 7 * PacketSize], internal::padd(internal::ploadu(&a[i + 7 * PacketSize]),
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internal::ploadu(&b[i + 7 * PacketSize])));
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}
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}
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