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				| 
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| //g++-4.4 -DNOMTL  -Wl,-rpath /usr/local/lib/oski -L /usr/local/lib/oski/ -l oski -l oski_util -l oski_util_Tid  -DOSKI -I ~/Coding/LinearAlgebra/mtl4/  spmv.cpp  -I .. -O2 -DNDEBUG -lrt  -lm -l oski_mat_CSC_Tid  -loskilt && ./a.out r200000 c200000 n100 t1 p1 | |
|  | |
| #define SCALAR double | |
|  | |
| #include <iostream> | |
| #include <algorithm> | |
| #include "BenchTimer.h" | |
| #include "BenchSparseUtil.h" | |
|  | |
| #define SPMV_BENCH(CODE) BENCH(t,tries,repeats,CODE); | |
|  | |
| // #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 | |
|  | |
| int main(int argc, char *argv[]) | |
| { | |
|   int size = 10000; | |
|   int rows = size; | |
|   int cols = size; | |
|   int nnzPerCol = 40; | |
|   int tries = 2; | |
|   int repeats = 2; | |
| 
 | |
|   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); | |
| 
 | |
|     // dense matrices | |
|     #ifdef DENSEMATRIX | |
|     { | |
|       DenseMatrix dm(rows,cols), (rows,cols); | |
|       eiToDense(sm, dm); | |
| 
 | |
|       SPMV_BENCH(res = dm * sm); | |
|       std::cout << "Dense       " << t.value()/repeats << "\t"; | |
| 
 | |
|       SPMV_BENCHres = dm.transpose() * sm); | |
|       std::cout << t.value()/repeats << endl; | |
|     } | |
|     #endif | |
|  | |
|     // eigen sparse matrices | |
|     { | |
|       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; | |
|     } | |
| 
 | |
|     // CSparse | |
|     #ifdef CSPARSE | |
|     { | |
|       std::cout << "CSparse \n"; | |
|       cs *csm; | |
|       eiToCSparse(sm, csm); | |
| 
 | |
| //       BENCH(); | |
| //       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 | |
|  | |
|     #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"; | |
| 
 | |
|       // tune | |
|       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"; | |
| 
 | |
| 
 | |
|       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 | |
|  | |
|     // GMM++ | |
|     #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 | |
|  | |
|     // MTL4 | |
|     #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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