[136] | 1 |
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| 2 | // g++ -I.. sparse_lu.cpp -O3 -g0 -I /usr/include/superlu/ -lsuperlu -lgfortran -DSIZE=1000 -DDENSITY=.05 && ./a.out
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| 3 |
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| 4 | #define EIGEN_SUPERLU_SUPPORT
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| 5 | #define EIGEN_UMFPACK_SUPPORT
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| 6 | #include <Eigen/Sparse>
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| 7 |
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| 8 | #define NOGMM
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| 9 | #define NOMTL
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| 10 |
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| 11 | #ifndef SIZE
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| 12 | #define SIZE 10
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| 13 | #endif
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| 14 |
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| 15 | #ifndef DENSITY
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| 16 | #define DENSITY 0.01
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| 17 | #endif
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| 18 |
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| 19 | #ifndef REPEAT
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| 20 | #define REPEAT 1
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| 21 | #endif
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| 22 |
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| 23 | #include "BenchSparseUtil.h"
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| 24 |
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| 25 | #ifndef MINDENSITY
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| 26 | #define MINDENSITY 0.0004
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| 27 | #endif
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| 28 |
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| 29 | #ifndef NBTRIES
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| 30 | #define NBTRIES 10
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| 31 | #endif
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| 32 |
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| 33 | #define BENCH(X) \
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| 34 | timer.reset(); \
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| 35 | for (int _j=0; _j<NBTRIES; ++_j) { \
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| 36 | timer.start(); \
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| 37 | for (int _k=0; _k<REPEAT; ++_k) { \
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| 38 | X \
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| 39 | } timer.stop(); }
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| 40 |
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| 41 | typedef Matrix<Scalar,Dynamic,1> VectorX;
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| 42 |
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| 43 | #include <Eigen/LU>
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| 44 |
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| 45 | template<int Backend>
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| 46 | void doEigen(const char* name, const EigenSparseMatrix& sm1, const VectorX& b, VectorX& x, int flags = 0)
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| 47 | {
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| 48 | std::cout << name << "..." << std::flush;
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| 49 | BenchTimer timer; timer.start();
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| 50 | SparseLU<EigenSparseMatrix,Backend> lu(sm1, flags);
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| 51 | timer.stop();
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| 52 | if (lu.succeeded())
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| 53 | std::cout << ":\t" << timer.value() << endl;
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| 54 | else
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| 55 | {
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| 56 | std::cout << ":\t FAILED" << endl;
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| 57 | return;
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| 58 | }
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| 59 |
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| 60 | bool ok;
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| 61 | timer.reset(); timer.start();
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| 62 | ok = lu.solve(b,&x);
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| 63 | timer.stop();
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| 64 | if (ok)
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| 65 | std::cout << " solve:\t" << timer.value() << endl;
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| 66 | else
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| 67 | std::cout << " solve:\t" << " FAILED" << endl;
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| 68 |
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| 69 | //std::cout << x.transpose() << "\n";
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| 70 | }
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| 71 |
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| 72 | int main(int argc, char *argv[])
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| 73 | {
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| 74 | int rows = SIZE;
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| 75 | int cols = SIZE;
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| 76 | float density = DENSITY;
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| 77 | BenchTimer timer;
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| 78 |
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| 79 | VectorX b = VectorX::Random(cols);
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| 80 | VectorX x = VectorX::Random(cols);
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| 81 |
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| 82 | bool densedone = false;
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| 83 |
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| 84 | //for (float density = DENSITY; density>=MINDENSITY; density*=0.5)
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| 85 | // float density = 0.5;
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| 86 | {
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| 87 | EigenSparseMatrix sm1(rows, cols);
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| 88 | fillMatrix(density, rows, cols, sm1);
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| 89 |
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| 90 | // dense matrices
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| 91 | #ifdef DENSEMATRIX
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| 92 | if (!densedone)
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| 93 | {
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| 94 | densedone = true;
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| 95 | std::cout << "Eigen Dense\t" << density*100 << "%\n";
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| 96 | DenseMatrix m1(rows,cols);
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| 97 | eiToDense(sm1, m1);
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| 98 |
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| 99 | BenchTimer timer;
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| 100 | timer.start();
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| 101 | FullPivLU<DenseMatrix> lu(m1);
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| 102 | timer.stop();
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| 103 | std::cout << "Eigen/dense:\t" << timer.value() << endl;
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| 104 |
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| 105 | timer.reset();
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| 106 | timer.start();
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| 107 | lu.solve(b,&x);
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| 108 | timer.stop();
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| 109 | std::cout << " solve:\t" << timer.value() << endl;
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| 110 | // std::cout << b.transpose() << "\n";
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| 111 | // std::cout << x.transpose() << "\n";
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| 112 | }
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| 113 | #endif
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| 114 |
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| 115 | #ifdef EIGEN_UMFPACK_SUPPORT
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| 116 | x.setZero();
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| 117 | doEigen<Eigen::UmfPack>("Eigen/UmfPack (auto)", sm1, b, x, 0);
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| 118 | #endif
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| 119 |
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| 120 | #ifdef EIGEN_SUPERLU_SUPPORT
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| 121 | x.setZero();
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| 122 | doEigen<Eigen::SuperLU>("Eigen/SuperLU (nat)", sm1, b, x, Eigen::NaturalOrdering);
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| 123 | // doEigen<Eigen::SuperLU>("Eigen/SuperLU (MD AT+A)", sm1, b, x, Eigen::MinimumDegree_AT_PLUS_A);
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| 124 | // doEigen<Eigen::SuperLU>("Eigen/SuperLU (MD ATA)", sm1, b, x, Eigen::MinimumDegree_ATA);
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| 125 | doEigen<Eigen::SuperLU>("Eigen/SuperLU (COLAMD)", sm1, b, x, Eigen::ColApproxMinimumDegree);
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| 126 | #endif
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| 127 |
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| 128 | }
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| 129 |
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| 130 | return 0;
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| 131 | }
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| 132 |
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