bench/sparse_product.cpp File Reference

#include <typeinfo>
#include <algorithm>
#include "BenchTimer.h"
#include "BenchUtil.h"
#include "BenchSparseUtil.h"

Macros
#define	SIZE   1000000
#define	NNZPERCOL   6
#define	REPEAT   1
#define	NBTRIES   1
#define	BENCH(X)

Functions
void	bench_sort ()
int	main (int argc, char *argv[])

Macro Definition Documentation

BENCH

#define BENCH

(

X

)

Value:

  timer.reset();                          \
  for (int _j = 0; _j < NBTRIES; ++_j) {  \
    timer.start();                        \
    for (int _k = 0; _k < REPEAT; ++_k) { \
      X                                   \
    }                                     \
    timer.stop();                         \
  }

NBTRIES

#define NBTRIES   1

NNZPERCOL

#define NNZPERCOL   6

REPEAT

#define REPEAT   1

SIZE

#define SIZE   1000000

Function Documentation

bench_sort()

void bench_sort

(

)

main()

int main	(	int argc	,
		char *	argv[]
	)

                                 {
  //   bench_sort();
 
  int rows = SIZE;
  int cols = SIZE;
  float density = DENSITY;
 
  EigenSparseMatrix sm1(rows, cols), sm2(rows, cols), sm3(rows, cols), sm4(rows, cols);
 
  BenchTimer timer;
  for (int nnzPerCol = NNZPERCOL; nnzPerCol > 1; nnzPerCol /= 1.1) {
    sm1.setZero();
    sm2.setZero();
    fillMatrix2(nnzPerCol, rows, cols, sm1);
    fillMatrix2(nnzPerCol, rows, cols, sm2);
    //     std::cerr << "filling OK\n";
 
// dense matrices
#ifdef DENSEMATRIX
    {
      std::cout << "Eigen Dense\t" << nnzPerCol << "%\n";
      DenseMatrix m1(rows, cols), m2(rows, cols), m3(rows, cols);
      eiToDense(sm1, m1);
      eiToDense(sm2, m2);
 
      timer.reset();
      timer.start();
      for (int k = 0; k < REPEAT; ++k) m3 = m1 * m2;
      timer.stop();
      std::cout << "   a * b:\t" << timer.value() << endl;
 
      timer.reset();
      timer.start();
      for (int k = 0; k < REPEAT; ++k) m3 = m1.transpose() * m2;
      timer.stop();
      std::cout << "   a' * b:\t" << timer.value() << endl;
 
      timer.reset();
      timer.start();
      for (int k = 0; k < REPEAT; ++k) m3 = m1.transpose() * m2.transpose();
      timer.stop();
      std::cout << "   a' * b':\t" << timer.value() << endl;
 
      timer.reset();
      timer.start();
      for (int k = 0; k < REPEAT; ++k) m3 = m1 * m2.transpose();
      timer.stop();
      std::cout << "   a * b':\t" << timer.value() << endl;
    }
#endif
 
    // eigen sparse matrices
    {
      std::cout << "Eigen sparse\t" << sm1.nonZeros() / (float(sm1.rows()) * float(sm1.cols())) * 100 << "% * "
                << sm2.nonZeros() / (float(sm2.rows()) * float(sm2.cols())) * 100 << "%\n";
 
      BENCH(sm3 = sm1 * sm2;)
      std::cout << "   a * b:\t" << timer.value() << endl;
 
      //       BENCH(sm3 = sm1.transpose() * sm2; )
      //       std::cout << "   a' * b:\t" << timer.value() << endl;
      // //
      //       BENCH(sm3 = sm1.transpose() * sm2.transpose(); )
      //       std::cout << "   a' * b':\t" << timer.value() << endl;
      // //
      //       BENCH(sm3 = sm1 * sm2.transpose(); )
      //       std::cout << "   a * b' :\t" << timer.value() << endl;
 
      //       std::cout << "\n";
      //
      //       BENCH( sm3._experimentalNewProduct(sm1, sm2); )
      //       std::cout << "   a * b:\t" << timer.value() << endl;
      //
      //       BENCH(sm3._experimentalNewProduct(sm1.transpose(),sm2); )
      //       std::cout << "   a' * b:\t" << timer.value() << endl;
      // //
      //       BENCH(sm3._experimentalNewProduct(sm1.transpose(),sm2.transpose()); )
      //       std::cout << "   a' * b':\t" << timer.value() << endl;
      // //
      //       BENCH(sm3._experimentalNewProduct(sm1, sm2.transpose());)
      //       std::cout << "   a * b' :\t" << timer.value() << endl;
    }
 
// eigen dyn-sparse matrices
/*{
  DynamicSparseMatrix<Scalar> m1(sm1), m2(sm2), m3(sm3);
  std::cout << "Eigen dyn-sparse\t" << m1.nonZeros()/(float(m1.rows())*float(m1.cols()))*100 << "% * "
            << m2.nonZeros()/(float(m2.rows())*float(m2.cols()))*100 << "%\n";
 
//       timer.reset();
//       timer.start();
  BENCH(for (int k=0; k<REPEAT; ++k) m3 = m1 * m2;)
//       timer.stop();
  std::cout << "   a * b:\t" << timer.value() << endl;
//       std::cout << sm3 << "\n";
 
  timer.reset();
  timer.start();
//       std::cerr << "transpose...\n";
//       EigenSparseMatrix sm4 = sm1.transpose();
//       std::cout << sm4.nonZeros() << " == " << sm1.nonZeros() << "\n";
//       exit(1);
//       std::cerr << "transpose OK\n";
//       std::cout << sm1 << "\n\n" << sm1.transpose() << "\n\n" << sm4.transpose() << "\n\n";
  BENCH(for (int k=0; k<REPEAT; ++k) m3 = m1.transpose() * m2;)
//       timer.stop();
  std::cout << "   a' * b:\t" << timer.value() << endl;
 
//       timer.reset();
//       timer.start();
  BENCH( for (int k=0; k<REPEAT; ++k) m3 = m1.transpose() * m2.transpose(); )
//       timer.stop();
  std::cout << "   a' * b':\t" << timer.value() << endl;
 
//       timer.reset();
//       timer.start();
  BENCH( for (int k=0; k<REPEAT; ++k) m3 = m1 * m2.transpose(); )
//       timer.stop();
  std::cout << "   a * b' :\t" << timer.value() << endl;
}*/
 
// CSparse
#ifdef CSPARSE
    {
      std::cout << "CSparse \t" << nnzPerCol << "%\n";
      cs *m1, *m2, *m3;
      eiToCSparse(sm1, m1);
      eiToCSparse(sm2, m2);
 
      BENCH({
        m3 = cs_sorted_multiply(m1, m2);
        if (!m3) {
          std::cerr << "cs_multiply failed\n";
        }
        //         cs_print(m3, 0);
        cs_spfree(m3);
      });
      //       timer.stop();
      std::cout << "   a * b:\t" << timer.value() << endl;
 
      //       BENCH( { m3 = cs_sorted_multiply2(m1, m2); cs_spfree(m3); } );
      //       std::cout << "   a * b:\t" << timer.value() << endl;
    }
#endif
 
#ifndef NOUBLAS
    {
      std::cout << "ublas\t" << nnzPerCol << "%\n";
      UBlasSparse m1(rows, cols), m2(rows, cols), m3(rows, cols);
      eiToUblas(sm1, m1);
      eiToUblas(sm2, m2);
 
      BENCH(boost::numeric::ublas::prod(m1, m2, m3););
      std::cout << "   a * b:\t" << timer.value() << endl;
    }
#endif
 
// GMM++
#ifndef NOGMM
    {
      std::cout << "GMM++ sparse\t" << nnzPerCol << "%\n";
      GmmDynSparse gmmT3(rows, cols);
      GmmSparse m1(rows, cols), m2(rows, cols), m3(rows, cols);
      eiToGmm(sm1, m1);
      eiToGmm(sm2, m2);
 
      BENCH(gmm::mult(m1, m2, gmmT3););
      std::cout << "   a * b:\t" << timer.value() << endl;
 
      //       BENCH(gmm::mult(gmm::transposed(m1), m2, gmmT3););
      //       std::cout << "   a' * b:\t" << timer.value() << endl;
      //
      //       if (rows<500)
      //       {
      //         BENCH(gmm::mult(gmm::transposed(m1), gmm::transposed(m2), gmmT3););
      //         std::cout << "   a' * b':\t" << timer.value() << endl;
      //
      //         BENCH(gmm::mult(m1, gmm::transposed(m2), gmmT3););
      //         std::cout << "   a * b':\t" << timer.value() << endl;
      //       }
      //       else
      //       {
      //         std::cout << "   a' * b':\t" << "forever" << endl;
      //         std::cout << "   a * b':\t" << "forever" << endl;
      //       }
    }
#endif
 
// MTL4
#ifndef NOMTL
    {
      std::cout << "MTL4\t" << nnzPerCol << "%\n";
      MtlSparse m1(rows, cols), m2(rows, cols), m3(rows, cols);
      eiToMtl(sm1, m1);
      eiToMtl(sm2, m2);
 
      BENCH(m3 = m1 * m2;);
      std::cout << "   a * b:\t" << timer.value() << endl;
 
      //       BENCH(m3 = trans(m1) * m2;);
      //       std::cout << "   a' * b:\t" << timer.value() << endl;
      //
      //       BENCH(m3 = trans(m1) * trans(m2););
      //       std::cout << "  a' * b':\t" << timer.value() << endl;
      //
      //       BENCH(m3 = m1 * trans(m2););
      //       std::cout << "   a * b' :\t" << timer.value() << endl;
    }
#endif
 
    std::cout << "\n\n";
  }
 
  return 0;
}

References BENCH, cols, UniformPSDSelfTest::density, DENSITY, eiToDense(), eiToGmm(), eiToMtl(), eiToUblas(), fillMatrix2(), k, m1, m2(), NNZPERCOL, prod(), REPEAT, rows, and SIZE.