bench/benchVecAdd.cpp

#include <iostream>
#include <Eigen/Core>
#include <bench/BenchTimer.h>
using namespace Eigen;

#ifndef SIZE
#define SIZE 50
#endif

#ifndef REPEAT
#define REPEAT 10000
#endif

typedef float Scalar;

__attribute__((noinline)) void benchVec(Scalar* a, Scalar* b, Scalar* c, int size);
__attribute__((noinline)) void benchVec(MatrixXf& a, MatrixXf& b, MatrixXf& c);
__attribute__((noinline)) void benchVec(VectorXf& a, VectorXf& b, VectorXf& c);

int main(int argc, char* argv[]) {
  int size = SIZE * 8;
  int size2 = size * size;
  Scalar* a = internal::aligned_new<Scalar>(size2);
  Scalar* b = internal::aligned_new<Scalar>(size2 + 4) + 1;
  Scalar* c = internal::aligned_new<Scalar>(size2);

  for (int i = 0; i < size; ++i) {
    a[i] = b[i] = c[i] = 0;
  }

  BenchTimer timer;

  timer.reset();
  for (int k = 0; k < 10; ++k) {
    timer.start();
    benchVec(a, b, c, size2);
    timer.stop();
  }
  std::cout << timer.value() << "s  " << (double(size2 * REPEAT) / timer.value()) / (1024. * 1024. * 1024.)
            << " GFlops\n";
  return 0;
  for (int innersize = size; innersize > 2; --innersize) {
    if (size2 % innersize == 0) {
      int outersize = size2 / innersize;
      MatrixXf ma = Map<MatrixXf>(a, innersize, outersize);
      MatrixXf mb = Map<MatrixXf>(b, innersize, outersize);
      MatrixXf mc = Map<MatrixXf>(c, innersize, outersize);
      timer.reset();
      for (int k = 0; k < 3; ++k) {
        timer.start();
        benchVec(ma, mb, mc);
        timer.stop();
      }
      std::cout << innersize << " x " << outersize << "  " << timer.value() << "s   "
                << (double(size2 * REPEAT) / timer.value()) / (1024. * 1024. * 1024.) << " GFlops\n";
    }
  }

  VectorXf va = Map<VectorXf>(a, size2);
  VectorXf vb = Map<VectorXf>(b, size2);
  VectorXf vc = Map<VectorXf>(c, size2);
  timer.reset();
  for (int k = 0; k < 3; ++k) {
    timer.start();
    benchVec(va, vb, vc);
    timer.stop();
  }
  std::cout << timer.value() << "s   " << (double(size2 * REPEAT) / timer.value()) / (1024. * 1024. * 1024.)
            << " GFlops\n";

  return 0;
}

void benchVec(MatrixXf& a, MatrixXf& b, MatrixXf& c) {
  for (int k = 0; k < REPEAT; ++k) a = a + b;
}

void benchVec(VectorXf& a, VectorXf& b, VectorXf& c) {
  for (int k = 0; k < REPEAT; ++k) a = a + b;
}

void benchVec(Scalar* a, Scalar* b, Scalar* c, int size) {
  typedef internal::packet_traits<Scalar>::type PacketScalar;
  const int PacketSize = internal::packet_traits<Scalar>::size;
  PacketScalar a0, a1, a2, a3, b0, b1, b2, b3;
  for (int k = 0; k < REPEAT; ++k)
    for (int i = 0; i < size; i += PacketSize * 8) {
      //             a0 = internal::pload(&a[i]);
      //             b0 = internal::pload(&b[i]);
      //             a1 = internal::pload(&a[i+1*PacketSize]);
      //             b1 = internal::pload(&b[i+1*PacketSize]);
      //             a2 = internal::pload(&a[i+2*PacketSize]);
      //             b2 = internal::pload(&b[i+2*PacketSize]);
      //             a3 = internal::pload(&a[i+3*PacketSize]);
      //             b3 = internal::pload(&b[i+3*PacketSize]);
      //             internal::pstore(&a[i], internal::padd(a0, b0));
      //             a0 = internal::pload(&a[i+4*PacketSize]);
      //             b0 = internal::pload(&b[i+4*PacketSize]);
      //
      //             internal::pstore(&a[i+1*PacketSize], internal::padd(a1, b1));
      //             a1 = internal::pload(&a[i+5*PacketSize]);
      //             b1 = internal::pload(&b[i+5*PacketSize]);
      //
      //             internal::pstore(&a[i+2*PacketSize], internal::padd(a2, b2));
      //             a2 = internal::pload(&a[i+6*PacketSize]);
      //             b2 = internal::pload(&b[i+6*PacketSize]);
      //
      //             internal::pstore(&a[i+3*PacketSize], internal::padd(a3, b3));
      //             a3 = internal::pload(&a[i+7*PacketSize]);
      //             b3 = internal::pload(&b[i+7*PacketSize]);
      //
      //             internal::pstore(&a[i+4*PacketSize], internal::padd(a0, b0));
      //             internal::pstore(&a[i+5*PacketSize], internal::padd(a1, b1));
      //             internal::pstore(&a[i+6*PacketSize], internal::padd(a2, b2));
      //             internal::pstore(&a[i+7*PacketSize], internal::padd(a3, b3));

      internal::pstore(&a[i + 2 * PacketSize], internal::padd(internal::ploadu(&a[i + 2 * PacketSize]),
                                                              internal::ploadu(&b[i + 2 * PacketSize])));
      internal::pstore(&a[i + 3 * PacketSize], internal::padd(internal::ploadu(&a[i + 3 * PacketSize]),
                                                              internal::ploadu(&b[i + 3 * PacketSize])));
      internal::pstore(&a[i + 4 * PacketSize], internal::padd(internal::ploadu(&a[i + 4 * PacketSize]),
                                                              internal::ploadu(&b[i + 4 * PacketSize])));
      internal::pstore(&a[i + 5 * PacketSize], internal::padd(internal::ploadu(&a[i + 5 * PacketSize]),
                                                              internal::ploadu(&b[i + 5 * PacketSize])));
      internal::pstore(&a[i + 6 * PacketSize], internal::padd(internal::ploadu(&a[i + 6 * PacketSize]),
                                                              internal::ploadu(&b[i + 6 * PacketSize])));
      internal::pstore(&a[i + 7 * PacketSize], internal::padd(internal::ploadu(&a[i + 7 * PacketSize]),
                                                              internal::ploadu(&b[i + 7 * PacketSize])));
    }
}