Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 1 | |
| 2 | //g++ -O3 -g0 -DNDEBUG sparse_product.cpp -I.. -I/home/gael/Coding/LinearAlgebra/mtl4/ -DDENSITY=0.005 -DSIZE=10000 && ./a.out |
| 3 | //g++ -O3 -g0 -DNDEBUG sparse_product.cpp -I.. -I/home/gael/Coding/LinearAlgebra/mtl4/ -DDENSITY=0.05 -DSIZE=2000 && ./a.out |
| 4 | // -DNOGMM -DNOMTL |
| 5 | // -I /home/gael/Coding/LinearAlgebra/CSparse/Include/ /home/gael/Coding/LinearAlgebra/CSparse/Lib/libcsparse.a |
| 6 | |
| 7 | #ifndef SIZE |
| 8 | #define SIZE 10000 |
| 9 | #endif |
| 10 | |
| 11 | #ifndef DENSITY |
| 12 | #define DENSITY 0.01 |
| 13 | #endif |
| 14 | |
| 15 | #ifndef REPEAT |
| 16 | #define REPEAT 1 |
| 17 | #endif |
| 18 | |
| 19 | #include "BenchSparseUtil.h" |
| 20 | |
| 21 | #ifndef MINDENSITY |
| 22 | #define MINDENSITY 0.0004 |
| 23 | #endif |
| 24 | |
| 25 | #ifndef NBTRIES |
| 26 | #define NBTRIES 10 |
| 27 | #endif |
| 28 | |
| 29 | #define BENCH(X) \ |
| 30 | timer.reset(); \ |
| 31 | for (int _j=0; _j<NBTRIES; ++_j) { \ |
| 32 | timer.start(); \ |
| 33 | for (int _k=0; _k<REPEAT; ++_k) { \ |
| 34 | X \ |
| 35 | } timer.stop(); } |
| 36 | |
| 37 | typedef SparseMatrix<Scalar,UpperTriangular> EigenSparseTriMatrix; |
| 38 | typedef SparseMatrix<Scalar,RowMajorBit|UpperTriangular> EigenSparseTriMatrixRow; |
| 39 | |
| 40 | void fillMatrix(float density, int rows, int cols, EigenSparseTriMatrix& dst) |
| 41 | { |
| 42 | dst.startFill(rows*cols*density); |
| 43 | for(int j = 0; j < cols; j++) |
| 44 | { |
| 45 | for(int i = 0; i < j; i++) |
| 46 | { |
| 47 | Scalar v = (internal::random<float>(0,1) < density) ? internal::random<Scalar>() : 0; |
| 48 | if (v!=0) |
| 49 | dst.fill(i,j) = v; |
| 50 | } |
| 51 | dst.fill(j,j) = internal::random<Scalar>(); |
| 52 | } |
| 53 | dst.endFill(); |
| 54 | } |
| 55 | |
| 56 | int main(int argc, char *argv[]) |
| 57 | { |
| 58 | int rows = SIZE; |
| 59 | int cols = SIZE; |
| 60 | float density = DENSITY; |
| 61 | BenchTimer timer; |
| 62 | #if 1 |
| 63 | EigenSparseTriMatrix sm1(rows,cols); |
| 64 | typedef Matrix<Scalar,Dynamic,1> DenseVector; |
| 65 | DenseVector b = DenseVector::Random(cols); |
| 66 | DenseVector x = DenseVector::Random(cols); |
| 67 | |
| 68 | bool densedone = false; |
| 69 | |
| 70 | for (float density = DENSITY; density>=MINDENSITY; density*=0.5) |
| 71 | { |
| 72 | EigenSparseTriMatrix sm1(rows, cols); |
| 73 | fillMatrix(density, rows, cols, sm1); |
| 74 | |
| 75 | // dense matrices |
| 76 | #ifdef DENSEMATRIX |
| 77 | if (!densedone) |
| 78 | { |
| 79 | densedone = true; |
| 80 | std::cout << "Eigen Dense\t" << density*100 << "%\n"; |
| 81 | DenseMatrix m1(rows,cols); |
| 82 | Matrix<Scalar,Dynamic,Dynamic,Dynamic,Dynamic,RowMajorBit> m2(rows,cols); |
| 83 | eiToDense(sm1, m1); |
| 84 | m2 = m1; |
| 85 | |
| 86 | BENCH(x = m1.marked<UpperTriangular>().solveTriangular(b);) |
| 87 | std::cout << " colmajor^-1 * b:\t" << timer.value() << endl; |
| 88 | // std::cerr << x.transpose() << "\n"; |
| 89 | |
| 90 | BENCH(x = m2.marked<UpperTriangular>().solveTriangular(b);) |
| 91 | std::cout << " rowmajor^-1 * b:\t" << timer.value() << endl; |
| 92 | // std::cerr << x.transpose() << "\n"; |
| 93 | } |
| 94 | #endif |
| 95 | |
| 96 | // eigen sparse matrices |
| 97 | { |
| 98 | std::cout << "Eigen sparse\t" << density*100 << "%\n"; |
| 99 | EigenSparseTriMatrixRow sm2 = sm1; |
| 100 | |
| 101 | BENCH(x = sm1.solveTriangular(b);) |
| 102 | std::cout << " colmajor^-1 * b:\t" << timer.value() << endl; |
| 103 | // std::cerr << x.transpose() << "\n"; |
| 104 | |
| 105 | BENCH(x = sm2.solveTriangular(b);) |
| 106 | std::cout << " rowmajor^-1 * b:\t" << timer.value() << endl; |
| 107 | // std::cerr << x.transpose() << "\n"; |
| 108 | |
| 109 | // x = b; |
| 110 | // BENCH(sm1.inverseProductInPlace(x);) |
| 111 | // std::cout << " colmajor^-1 * b:\t" << timer.value() << " (inplace)" << endl; |
| 112 | // std::cerr << x.transpose() << "\n"; |
| 113 | // |
| 114 | // x = b; |
| 115 | // BENCH(sm2.inverseProductInPlace(x);) |
| 116 | // std::cout << " rowmajor^-1 * b:\t" << timer.value() << " (inplace)" << endl; |
| 117 | // std::cerr << x.transpose() << "\n"; |
| 118 | } |
| 119 | |
| 120 | |
| 121 | |
| 122 | // CSparse |
| 123 | #ifdef CSPARSE |
| 124 | { |
| 125 | std::cout << "CSparse \t" << density*100 << "%\n"; |
| 126 | cs *m1; |
| 127 | eiToCSparse(sm1, m1); |
| 128 | |
| 129 | BENCH(x = b; if (!cs_lsolve (m1, x.data())){std::cerr << "cs_lsolve failed\n"; break;}; ) |
| 130 | std::cout << " colmajor^-1 * b:\t" << timer.value() << endl; |
| 131 | } |
| 132 | #endif |
| 133 | |
| 134 | // GMM++ |
| 135 | #ifndef NOGMM |
| 136 | { |
| 137 | std::cout << "GMM++ sparse\t" << density*100 << "%\n"; |
| 138 | GmmSparse m1(rows,cols); |
| 139 | gmm::csr_matrix<Scalar> m2; |
| 140 | eiToGmm(sm1, m1); |
| 141 | gmm::copy(m1,m2); |
| 142 | std::vector<Scalar> gmmX(cols), gmmB(cols); |
| 143 | Map<Matrix<Scalar,Dynamic,1> >(&gmmX[0], cols) = x; |
| 144 | Map<Matrix<Scalar,Dynamic,1> >(&gmmB[0], cols) = b; |
| 145 | |
| 146 | gmmX = gmmB; |
| 147 | BENCH(gmm::upper_tri_solve(m1, gmmX, false);) |
| 148 | std::cout << " colmajor^-1 * b:\t" << timer.value() << endl; |
| 149 | // std::cerr << Map<Matrix<Scalar,Dynamic,1> >(&gmmX[0], cols).transpose() << "\n"; |
| 150 | |
| 151 | gmmX = gmmB; |
| 152 | BENCH(gmm::upper_tri_solve(m2, gmmX, false);) |
| 153 | timer.stop(); |
| 154 | std::cout << " rowmajor^-1 * b:\t" << timer.value() << endl; |
| 155 | // std::cerr << Map<Matrix<Scalar,Dynamic,1> >(&gmmX[0], cols).transpose() << "\n"; |
| 156 | } |
| 157 | #endif |
| 158 | |
| 159 | // MTL4 |
| 160 | #ifndef NOMTL |
| 161 | { |
| 162 | std::cout << "MTL4\t" << density*100 << "%\n"; |
| 163 | MtlSparse m1(rows,cols); |
| 164 | MtlSparseRowMajor m2(rows,cols); |
| 165 | eiToMtl(sm1, m1); |
| 166 | m2 = m1; |
| 167 | mtl::dense_vector<Scalar> x(rows, 1.0); |
| 168 | mtl::dense_vector<Scalar> b(rows, 1.0); |
| 169 | |
| 170 | BENCH(x = mtl::upper_trisolve(m1,b);) |
| 171 | std::cout << " colmajor^-1 * b:\t" << timer.value() << endl; |
| 172 | // std::cerr << x << "\n"; |
| 173 | |
| 174 | BENCH(x = mtl::upper_trisolve(m2,b);) |
| 175 | std::cout << " rowmajor^-1 * b:\t" << timer.value() << endl; |
| 176 | // std::cerr << x << "\n"; |
| 177 | } |
| 178 | #endif |
| 179 | |
| 180 | |
| 181 | std::cout << "\n\n"; |
| 182 | } |
| 183 | #endif |
| 184 | |
| 185 | #if 0 |
| 186 | // bench small matrices (in-place versus return bye value) |
| 187 | { |
| 188 | timer.reset(); |
| 189 | for (int _j=0; _j<10; ++_j) { |
| 190 | Matrix4f m = Matrix4f::Random(); |
| 191 | Vector4f b = Vector4f::Random(); |
| 192 | Vector4f x = Vector4f::Random(); |
| 193 | timer.start(); |
| 194 | for (int _k=0; _k<1000000; ++_k) { |
| 195 | b = m.inverseProduct(b); |
| 196 | } |
| 197 | timer.stop(); |
| 198 | } |
| 199 | std::cout << "4x4 :\t" << timer.value() << endl; |
| 200 | } |
| 201 | |
| 202 | { |
| 203 | timer.reset(); |
| 204 | for (int _j=0; _j<10; ++_j) { |
| 205 | Matrix4f m = Matrix4f::Random(); |
| 206 | Vector4f b = Vector4f::Random(); |
| 207 | Vector4f x = Vector4f::Random(); |
| 208 | timer.start(); |
| 209 | for (int _k=0; _k<1000000; ++_k) { |
| 210 | m.inverseProductInPlace(x); |
| 211 | } |
| 212 | timer.stop(); |
| 213 | } |
| 214 | std::cout << "4x4 IP :\t" << timer.value() << endl; |
| 215 | } |
| 216 | #endif |
| 217 | |
| 218 | return 0; |
| 219 | } |
| 220 | |