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| | #define SCALAR double |
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| | #include <iostream> |
| | #include <algorithm> |
| | #include "BenchTimer.h" |
| | #include "BenchSparseUtil.h" |
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| | #define SPMV_BENCH(CODE) BENCH(t,tries,repeats,CODE); |
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| | int main(int argc, char *argv[]) |
| | { |
| | int size = 10000; |
| | int rows = size; |
| | int cols = size; |
| | int nnzPerCol = 40; |
| | int tries = 2; |
| | int repeats = 2; |
| |
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| | bool need_help = false; |
| | for(int i = 1; i < argc; i++) |
| | { |
| | if(argv[i][0] == 'r') |
| | { |
| | rows = atoi(argv[i]+1); |
| | } |
| | else if(argv[i][0] == 'c') |
| | { |
| | cols = atoi(argv[i]+1); |
| | } |
| | else if(argv[i][0] == 'n') |
| | { |
| | nnzPerCol = atoi(argv[i]+1); |
| | } |
| | else if(argv[i][0] == 't') |
| | { |
| | tries = atoi(argv[i]+1); |
| | } |
| | else if(argv[i][0] == 'p') |
| | { |
| | repeats = atoi(argv[i]+1); |
| | } |
| | else |
| | { |
| | need_help = true; |
| | } |
| | } |
| | if(need_help) |
| | { |
| | std::cout << argv[0] << " r<nb rows> c<nb columns> n<non zeros per column> t<nb tries> p<nb repeats>\n"; |
| | return 1; |
| | } |
| |
|
| | std::cout << "SpMV " << rows << " x " << cols << " with " << nnzPerCol << " non zeros per column. (" << repeats << " repeats, and " << tries << " tries)\n\n"; |
| |
|
| | EigenSparseMatrix sm(rows,cols); |
| | DenseVector dv(cols), res(rows); |
| | dv.setRandom(); |
| |
|
| | BenchTimer t; |
| | while (nnzPerCol>=4) |
| | { |
| | std::cout << "nnz: " << nnzPerCol << "\n"; |
| | sm.setZero(); |
| | fillMatrix2(nnzPerCol, rows, cols, sm); |
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| | |
| | #ifdef DENSEMATRIX |
| | { |
| | DenseMatrix dm(rows,cols), (rows,cols); |
| | eiToDense(sm, dm); |
| |
|
| | SPMV_BENCH(res = dm * sm); |
| | std::cout << "Dense " << t.value()/repeats << "\t"; |
| |
|
| | SPMV_BENCH(res = dm.transpose() * sm); |
| | std::cout << t.value()/repeats << endl; |
| | } |
| | #endif |
| |
|
| | |
| | { |
| | SPMV_BENCH(res.noalias() += sm * dv; ) |
| | std::cout << "Eigen " << t.value()/repeats << "\t"; |
| |
|
| | SPMV_BENCH(res.noalias() += sm.transpose() * dv; ) |
| | std::cout << t.value()/repeats << endl; |
| | } |
| |
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| | |
| | #ifdef CSPARSE |
| | { |
| | std::cout << "CSparse \n"; |
| | cs *csm; |
| | eiToCSparse(sm, csm); |
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| | |
| | } |
| | #endif |
| |
|
| | #ifdef OSKI |
| | { |
| | oski_matrix_t om; |
| | oski_vecview_t ov, ores; |
| | oski_Init(); |
| | om = oski_CreateMatCSC(sm._outerIndexPtr(), sm._innerIndexPtr(), sm._valuePtr(), rows, cols, |
| | SHARE_INPUTMAT, 1, INDEX_ZERO_BASED); |
| | ov = oski_CreateVecView(dv.data(), cols, STRIDE_UNIT); |
| | ores = oski_CreateVecView(res.data(), rows, STRIDE_UNIT); |
| |
|
| | SPMV_BENCH( oski_MatMult(om, OP_NORMAL, 1, ov, 0, ores) ); |
| | std::cout << "OSKI " << t.value()/repeats << "\t"; |
| |
|
| | SPMV_BENCH( oski_MatMult(om, OP_TRANS, 1, ov, 0, ores) ); |
| | std::cout << t.value()/repeats << "\n"; |
| |
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| | |
| | t.reset(); |
| | t.start(); |
| | oski_SetHintMatMult(om, OP_NORMAL, 1.0, SYMBOLIC_VEC, 0.0, SYMBOLIC_VEC, ALWAYS_TUNE_AGGRESSIVELY); |
| | oski_TuneMat(om); |
| | t.stop(); |
| | double tuning = t.value(); |
| |
|
| | SPMV_BENCH( oski_MatMult(om, OP_NORMAL, 1, ov, 0, ores) ); |
| | std::cout << "OSKI tuned " << t.value()/repeats << "\t"; |
| |
|
| | SPMV_BENCH( oski_MatMult(om, OP_TRANS, 1, ov, 0, ores) ); |
| | std::cout << t.value()/repeats << "\t(" << tuning << ")\n"; |
| |
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|
| | oski_DestroyMat(om); |
| | oski_DestroyVecView(ov); |
| | oski_DestroyVecView(ores); |
| | oski_Close(); |
| | } |
| | #endif |
| |
|
| | #ifndef NOUBLAS |
| | { |
| | using namespace boost::numeric; |
| | UblasMatrix um(rows,cols); |
| | eiToUblas(sm, um); |
| |
|
| | boost::numeric::ublas::vector<Scalar> uv(cols), ures(rows); |
| | Map<Matrix<Scalar,Dynamic,1> >(&uv[0], cols) = dv; |
| | Map<Matrix<Scalar,Dynamic,1> >(&ures[0], rows) = res; |
| |
|
| | SPMV_BENCH(ublas::axpy_prod(um, uv, ures, true)); |
| | std::cout << "ublas " << t.value()/repeats << "\t"; |
| |
|
| | SPMV_BENCH(ublas::axpy_prod(boost::numeric::ublas::trans(um), uv, ures, true)); |
| | std::cout << t.value()/repeats << endl; |
| | } |
| | #endif |
| |
|
| | |
| | #ifndef NOGMM |
| | { |
| | GmmSparse gm(rows,cols); |
| | eiToGmm(sm, gm); |
| |
|
| | std::vector<Scalar> gv(cols), gres(rows); |
| | Map<Matrix<Scalar,Dynamic,1> >(&gv[0], cols) = dv; |
| | Map<Matrix<Scalar,Dynamic,1> >(&gres[0], rows) = res; |
| |
|
| | SPMV_BENCH(gmm::mult(gm, gv, gres)); |
| | std::cout << "GMM++ " << t.value()/repeats << "\t"; |
| |
|
| | SPMV_BENCH(gmm::mult(gmm::transposed(gm), gv, gres)); |
| | std::cout << t.value()/repeats << endl; |
| | } |
| | #endif |
| |
|
| | |
| | #ifndef NOMTL |
| | { |
| | MtlSparse mm(rows,cols); |
| | eiToMtl(sm, mm); |
| | mtl::dense_vector<Scalar> mv(cols, 1.0); |
| | mtl::dense_vector<Scalar> mres(rows, 1.0); |
| |
|
| | SPMV_BENCH(mres = mm * mv); |
| | std::cout << "MTL4 " << t.value()/repeats << "\t"; |
| |
|
| | SPMV_BENCH(mres = trans(mm) * mv); |
| | std::cout << t.value()/repeats << endl; |
| | } |
| | #endif |
| |
|
| | std::cout << "\n"; |
| |
|
| | if(nnzPerCol==1) |
| | break; |
| | nnzPerCol -= nnzPerCol/2; |
| | } |
| |
|
| | return 0; |
| | } |
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