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//g++ -O3 -g0 -DNDEBUG sparse_product.cpp -I.. -I/home/gael/Coding/LinearAlgebra/mtl4/ -DDENSITY=0.005 -DSIZE=10000 && ./a.out
//g++ -O3 -g0 -DNDEBUG sparse_product.cpp -I.. -I/home/gael/Coding/LinearAlgebra/mtl4/ -DDENSITY=0.05 -DSIZE=2000 && ./a.out
// -DNOGMM -DNOMTL -DCSPARSE
// -I /home/gael/Coding/LinearAlgebra/CSparse/Include/ /home/gael/Coding/LinearAlgebra/CSparse/Lib/libcsparse.a
#include <typeinfo>
#ifndef SIZE
#define SIZE 1000000
#endif
#ifndef NNZPERCOL
#define NNZPERCOL 6
#endif
#ifndef REPEAT
#define REPEAT 1
#endif
#include <algorithm>
#include "BenchTimer.h"
#include "BenchUtil.h"
#include "BenchSparseUtil.h"
#ifndef NBTRIES
#define NBTRIES 1
#endif
#define BENCH(X) \
timer.reset(); \
for (int _j=0; _j<NBTRIES; ++_j) { \
timer.start(); \
for (int _k=0; _k<REPEAT; ++_k) { \
X \
} timer.stop(); }
// #ifdef MKL
//
// #include "mkl_types.h"
// #include "mkl_spblas.h"
//
// template<typename Lhs,typename Rhs,typename Res>
// void mkl_multiply(const Lhs& lhs, const Rhs& rhs, Res& res)
// {
// char n = 'N';
// float alpha = 1;
// char matdescra[6];
// matdescra[0] = 'G';
// matdescra[1] = 0;
// matdescra[2] = 0;
// matdescra[3] = 'C';
// mkl_scscmm(&n, lhs.rows(), rhs.cols(), lhs.cols(), &alpha, matdescra,
// lhs._valuePtr(), lhs._innerIndexPtr(), lhs.outerIndexPtr(),
// pntre, b, &ldb, &beta, c, &ldc);
// // mkl_somatcopy('C', 'T', lhs.rows(), lhs.cols(), 1,
// // lhs._valuePtr(), lhs.rows(), DST, dst_stride);
// }
//
// #endif
#ifdef CSPARSE
cs* cs_sorted_multiply(const cs* a, const cs* b)
{
// return cs_multiply(a,b);
cs* A = cs_transpose(a, 1);
cs* B = cs_transpose(b, 1);
cs* D = cs_multiply(B,A); /* D = B'*A' */
cs_spfree (A) ;
cs_spfree (B) ;
cs_dropzeros (D) ; /* drop zeros from D */
cs* C = cs_transpose (D, 1) ; /* C = D', so that C is sorted */
cs_spfree (D) ;
return C;
// cs* A = cs_transpose(a, 1);
// cs* C = cs_transpose(A, 1);
// return C;
}
cs* cs_sorted_multiply2(const cs* a, const cs* b)
{
cs* D = cs_multiply(a,b);
cs* E = cs_transpose(D,1);
cs_spfree(D);
cs* C = cs_transpose(E,1);
cs_spfree(E);
return C;
}
#endif
void bench_sort();
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;
}
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