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extend benchmark for sparse products

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This commit is contained in:
Gael Guennebaud 2010-01-05 16:03:35 +01:00
parent d8534be728
commit c3823dce72
2 changed files with 90 additions and 39 deletions
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2
bench/BenchSparseUtil.h
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@ -42,7 +42,7 @@ void fillMatrix(float density, int rows, int cols, EigenSparseMatrix& dst)
void fillMatrix2(int nnzPerCol, int rows, int cols, EigenSparseMatrix& dst) void fillMatrix2(int nnzPerCol, int rows, int cols, EigenSparseMatrix& dst)
{ {
std::cout << "alloc " << nnzPerCol*cols << "\n"; // std::cout << "alloc " << nnzPerCol*cols << "\n";
dst.reserve(nnzPerCol*cols); dst.reserve(nnzPerCol*cols);
for(int j = 0; j < cols; j++) for(int j = 0; j < cols; j++)
{ {

127
bench/sparse_product.cpp
View File

@ -8,17 +8,19 @@
#endif #endif
#ifndef NNZPERCOL #ifndef NNZPERCOL
#define NNZPERCOL 2 #define NNZPERCOL 32
#endif #endif
#ifndef REPEAT #ifndef REPEAT
#define REPEAT 1 #define REPEAT 1
#endif #endif
#include <algorithm>
#include "BenchTimer.h"
#include "BenchSparseUtil.h" #include "BenchSparseUtil.h"
#ifndef NBTRIES #ifndef NBTRIES
#define NBTRIES 1 #define NBTRIES 4
#endif #endif
#define BENCH(X) \ #define BENCH(X) \
@ -29,24 +31,67 @@
X \ X \
} timer.stop(); } } 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 #ifdef CSPARSE
cs* cs_sorted_multiply(const cs* a, const cs* b) cs* cs_sorted_multiply(const cs* a, const cs* b)
{ {
cs* A = cs_transpose (a, 1) ; // return cs_multiply(a,b);
cs* B = cs_transpose (b, 1) ; cs* A = cs_transpose(a, 1);
cs* D = cs_multiply (B,A) ; /* D = B'*A' */ cs* B = cs_transpose(b, 1);
cs* D = cs_multiply(B,A); /* D = B'*A' */
cs_spfree (A) ; cs_spfree (A) ;
cs_spfree (B) ; cs_spfree (B) ;
cs_dropzeros (D) ; /* drop zeros from D */ cs_dropzeros (D) ; /* drop zeros from D */
cs* C = cs_transpose (D, 1) ; /* C = D', so that C is sorted */ cs* C = cs_transpose (D, 1) ; /* C = D', so that C is sorted */
cs_spfree (D) ; cs_spfree (D) ;
return C; 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 #endif
void bench_sort();
int main(int argc, char *argv[]) int main(int argc, char *argv[])
{ {
// bench_sort();
int rows = SIZE; int rows = SIZE;
int cols = SIZE; int cols = SIZE;
float density = DENSITY; float density = DENSITY;
@ -54,10 +99,13 @@ int main(int argc, char *argv[])
EigenSparseMatrix sm1(rows,cols), sm2(rows,cols), sm3(rows,cols), sm4(rows,cols); EigenSparseMatrix sm1(rows,cols), sm2(rows,cols), sm3(rows,cols), sm4(rows,cols);
BenchTimer timer; BenchTimer timer;
for (int nnzPerCol = NNZPERCOL; nnzPerCol>1; nnzPerCol/=2) for (int nnzPerCol = NNZPERCOL; nnzPerCol>1; nnzPerCol/=1.1)
{ {
sm1.setZero();
sm2.setZero();
fillMatrix2(nnzPerCol, rows, cols, sm1); fillMatrix2(nnzPerCol, rows, cols, sm1);
fillMatrix2(nnzPerCol, rows, cols, sm2); fillMatrix2(nnzPerCol, rows, cols, sm2);
// std::cerr << "filling OK\n";
// dense matrices // dense matrices
#ifdef DENSEMATRIX #ifdef DENSEMATRIX
@ -102,40 +150,36 @@ int main(int argc, char *argv[])
std::cout << "Eigen sparse\t" << sm1.nonZeros()/(float(sm1.rows())*float(sm1.cols()))*100 << "% * " std::cout << "Eigen sparse\t" << sm1.nonZeros()/(float(sm1.rows())*float(sm1.cols()))*100 << "% * "
<< sm2.nonZeros()/(float(sm2.rows())*float(sm2.cols()))*100 << "%\n"; << sm2.nonZeros()/(float(sm2.rows())*float(sm2.cols()))*100 << "%\n";
// timer.reset(); BENCH(sm3 = sm1 * sm2; )
// timer.start();
BENCH(for (int k=0; k<REPEAT; ++k) sm3 = sm1 * sm2;)
// timer.stop();
std::cout << " a * b:\t" << timer.value() << endl; std::cout << " a * b:\t" << timer.value() << endl;
// std::cout << sm3 << "\n";
timer.reset(); // BENCH(sm3 = sm1.transpose() * sm2; )
timer.start(); // std::cout << " a' * b:\t" << timer.value() << endl;
// std::cerr << "transpose...\n"; //
// EigenSparseMatrix sm4 = sm1.transpose(); // BENCH(sm3 = sm1.transpose() * sm2.transpose(); )
// std::cout << sm4.nonZeros() << " == " << sm1.nonZeros() << "\n"; // std::cout << " a' * b':\t" << timer.value() << endl;
// exit(1); //
// std::cerr << "transpose OK\n"; // BENCH(sm3 = sm1 * sm2.transpose(); )
// std::cout << sm1 << "\n\n" << sm1.transpose() << "\n\n" << sm4.transpose() << "\n\n"; // std::cout << " a * b' :\t" << timer.value() << endl;
BENCH(for (int k=0; k<REPEAT; ++k) sm3 = sm1.transpose() * sm2;)
// timer.stop();
std::cout << " a' * b:\t" << timer.value() << endl;
// timer.reset();
// timer.start();
BENCH( for (int k=0; k<REPEAT; ++k) sm3 = sm1.transpose() * sm2.transpose(); )
// timer.stop();
std::cout << " a' * b':\t" << timer.value() << endl;
// timer.reset(); // std::cout << "\n\n";
// timer.start();
BENCH( for (int k=0; k<REPEAT; ++k) sm3 = sm1 * sm2.transpose(); ) BENCH( sm3.setprod(sm1, sm2); )
// timer.stop(); std::cout << " a * b:\t" << timer.value() << endl;
std::cout << " a * b' :\t" << timer.value() << endl;
// BENCH(sm3.setprod(sm1.transpose(),sm2); )
// std::cout << " a' * b:\t" << timer.value() << endl;
//
// BENCH(sm3.setprod(sm1.transpose(),sm2.transpose()); )
// std::cout << " a' * b':\t" << timer.value() << endl;
//
// BENCH(sm3.setprod(sm1, sm2.transpose());)
// std::cout << " a * b' :\t" << timer.value() << endl;
} }
// eigen dyn-sparse matrices // eigen dyn-sparse matrices
{ /*{
DynamicSparseMatrix<Scalar> m1(sm1), m2(sm2), m3(sm3); DynamicSparseMatrix<Scalar> m1(sm1), m2(sm2), m3(sm3);
std::cout << "Eigen dyn-sparse\t" << m1.nonZeros()/(float(m1.rows())*float(m1.cols()))*100 << "% * " 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"; << m2.nonZeros()/(float(m2.rows())*float(m2.cols()))*100 << "%\n";
@ -170,7 +214,7 @@ int main(int argc, char *argv[])
BENCH( for (int k=0; k<REPEAT; ++k) m3 = m1 * m2.transpose(); ) BENCH( for (int k=0; k<REPEAT; ++k) m3 = m1 * m2.transpose(); )
// timer.stop(); // timer.stop();
std::cout << " a * b' :\t" << timer.value() << endl; std::cout << " a * b' :\t" << timer.value() << endl;
} }*/
// CSparse // CSparse
#ifdef CSPARSE #ifdef CSPARSE
@ -180,9 +224,10 @@ int main(int argc, char *argv[])
eiToCSparse(sm1, m1); eiToCSparse(sm1, m1);
eiToCSparse(sm2, m2); eiToCSparse(sm2, m2);
timer.reset(); // timer.reset();
timer.start(); // timer.start();
for (int k=0; k<REPEAT; ++k) // for (int k=0; k<REPEAT; ++k)
BENCH(
{ {
m3 = cs_sorted_multiply(m1, m2); m3 = cs_sorted_multiply(m1, m2);
if (!m3) if (!m3)
@ -193,8 +238,12 @@ int main(int argc, char *argv[])
// cs_print(m3, 0); // cs_print(m3, 0);
cs_spfree(m3); cs_spfree(m3);
} }
timer.stop(); );
// timer.stop();
std::cout << " a * b:\t" << timer.value() << endl; 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 #endif
@ -289,3 +338,5 @@ int main(int argc, char *argv[])
return 0; return 0;
} }