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Clang-format tests, examples, libraries, benchmarks, etc.
This commit is contained in:
Antonio Sánchez
committed by
Rasmus Munk Larsen
Rasmus Munk Larsen
parent
3252ecc7a4
commit
46e9cdb7fe
@@ -3,7 +3,17 @@
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#include <iostream>
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#include <Eigen/Sparse>
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// g++ -DSIZE=10000 -DDENSITY=0.001 sparse_cholesky.cpp -I.. -DDENSEMATRI -O3 -g0 -DNDEBUG -DNBTRIES=1 -I /home/gael/Coding/LinearAlgebra/taucs_full/src/ -I/home/gael/Coding/LinearAlgebra/taucs_full/build/linux/ -L/home/gael/Coding/LinearAlgebra/taucs_full/lib/linux/ -ltaucs /home/gael/Coding/LinearAlgebra/GotoBLAS/libgoto.a -lpthread -I /home/gael/Coding/LinearAlgebra/SuiteSparse/CHOLMOD/Include/ $CHOLLIB -I /home/gael/Coding/LinearAlgebra/SuiteSparse/UFconfig/ /home/gael/Coding/LinearAlgebra/SuiteSparse/CCOLAMD/Lib/libccolamd.a /home/gael/Coding/LinearAlgebra/SuiteSparse/CHOLMOD/Lib/libcholmod.a -lmetis /home/gael/Coding/LinearAlgebra/SuiteSparse/AMD/Lib/libamd.a /home/gael/Coding/LinearAlgebra/SuiteSparse/CAMD/Lib/libcamd.a /home/gael/Coding/LinearAlgebra/SuiteSparse/CCOLAMD/Lib/libccolamd.a /home/gael/Coding/LinearAlgebra/SuiteSparse/COLAMD/Lib/libcolamd.a -llapack && ./a.out
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// g++ -DSIZE=10000 -DDENSITY=0.001 sparse_cholesky.cpp -I.. -DDENSEMATRI -O3 -g0 -DNDEBUG -DNBTRIES=1 -I
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// /home/gael/Coding/LinearAlgebra/taucs_full/src/ -I/home/gael/Coding/LinearAlgebra/taucs_full/build/linux/
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// -L/home/gael/Coding/LinearAlgebra/taucs_full/lib/linux/ -ltaucs /home/gael/Coding/LinearAlgebra/GotoBLAS/libgoto.a
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// -lpthread -I /home/gael/Coding/LinearAlgebra/SuiteSparse/CHOLMOD/Include/ $CHOLLIB -I
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// /home/gael/Coding/LinearAlgebra/SuiteSparse/UFconfig/
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// /home/gael/Coding/LinearAlgebra/SuiteSparse/CCOLAMD/Lib/libccolamd.a
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// /home/gael/Coding/LinearAlgebra/SuiteSparse/CHOLMOD/Lib/libcholmod.a -lmetis
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// /home/gael/Coding/LinearAlgebra/SuiteSparse/AMD/Lib/libamd.a
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// /home/gael/Coding/LinearAlgebra/SuiteSparse/CAMD/Lib/libcamd.a
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// /home/gael/Coding/LinearAlgebra/SuiteSparse/CCOLAMD/Lib/libccolamd.a
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// /home/gael/Coding/LinearAlgebra/SuiteSparse/COLAMD/Lib/libcolamd.a -llapack && ./a.out
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#define NOGMM
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#define NOMTL
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@@ -30,52 +40,47 @@
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#define NBTRIES 10
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#endif
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#define BENCH(X) \
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timer.reset(); \
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for (int _j=0; _j<NBTRIES; ++_j) { \
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timer.start(); \
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for (int _k=0; _k<REPEAT; ++_k) { \
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X \
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} timer.stop(); }
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#define BENCH(X) \
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timer.reset(); \
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for (int _j = 0; _j < NBTRIES; ++_j) { \
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timer.start(); \
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for (int _k = 0; _k < REPEAT; ++_k) { \
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X \
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} \
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timer.stop(); \
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}
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// typedef SparseMatrix<Scalar,UpperTriangular> EigenSparseTriMatrix;
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typedef SparseMatrix<Scalar,SelfAdjoint|LowerTriangular> EigenSparseSelfAdjointMatrix;
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typedef SparseMatrix<Scalar, SelfAdjoint | LowerTriangular> EigenSparseSelfAdjointMatrix;
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void fillSpdMatrix(float density, int rows, int cols, EigenSparseSelfAdjointMatrix& dst)
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{
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dst.startFill(rows*cols*density);
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for(int j = 0; j < cols; j++)
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{
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dst.fill(j,j) = internal::random<Scalar>(10,20);
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for(int i = j+1; i < rows; i++)
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{
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Scalar v = (internal::random<float>(0,1) < density) ? internal::random<Scalar>() : 0;
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if (v!=0)
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dst.fill(i,j) = v;
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void fillSpdMatrix(float density, int rows, int cols, EigenSparseSelfAdjointMatrix& dst) {
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dst.startFill(rows * cols * density);
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for (int j = 0; j < cols; j++) {
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dst.fill(j, j) = internal::random<Scalar>(10, 20);
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for (int i = j + 1; i < rows; i++) {
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Scalar v = (internal::random<float>(0, 1) < density) ? internal::random<Scalar>() : 0;
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if (v != 0) dst.fill(i, j) = v;
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}
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}
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dst.endFill();
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}
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#include <Eigen/Cholesky>
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template<int Backend>
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void doEigen(const char* name, const EigenSparseSelfAdjointMatrix& sm1, int flags = 0)
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{
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template <int Backend>
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void doEigen(const char* name, const EigenSparseSelfAdjointMatrix& sm1, int flags = 0) {
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std::cout << name << "..." << std::flush;
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BenchTimer timer;
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timer.start();
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SparseLLT<EigenSparseSelfAdjointMatrix,Backend> chol(sm1, flags);
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SparseLLT<EigenSparseSelfAdjointMatrix, Backend> chol(sm1, flags);
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timer.stop();
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std::cout << ":\t" << timer.value() << endl;
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std::cout << " nnz: " << sm1.nonZeros() << " => " << chol.matrixL().nonZeros() << "\n";
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// std::cout << "sparse\n" << chol.matrixL() << "%\n";
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// std::cout << "sparse\n" << chol.matrixL() << "%\n";
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}
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int main(int argc, char *argv[])
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{
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int main(int argc, char* argv[]) {
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int rows = SIZE;
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int cols = SIZE;
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float density = DENSITY;
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@@ -86,27 +91,26 @@ int main(int argc, char *argv[])
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bool densedone = false;
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//for (float density = DENSITY; density>=MINDENSITY; density*=0.5)
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// float density = 0.5;
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// for (float density = DENSITY; density>=MINDENSITY; density*=0.5)
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// float density = 0.5;
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{
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EigenSparseSelfAdjointMatrix sm1(rows, cols);
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std::cout << "Generate sparse matrix (might take a while)...\n";
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fillSpdMatrix(density, rows, cols, sm1);
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std::cout << "DONE\n\n";
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// dense matrices
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#ifdef DENSEMATRIX
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if (!densedone)
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{
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// dense matrices
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#ifdef DENSEMATRIX
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if (!densedone) {
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densedone = true;
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std::cout << "Eigen Dense\t" << density*100 << "%\n";
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DenseMatrix m1(rows,cols);
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std::cout << "Eigen Dense\t" << density * 100 << "%\n";
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DenseMatrix m1(rows, cols);
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eiToDense(sm1, m1);
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m1 = (m1 + m1.transpose()).eval();
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m1.diagonal() *= 0.5;
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// BENCH(LLT<DenseMatrix> chol(m1);)
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// std::cout << "dense:\t" << timer.value() << endl;
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// BENCH(LLT<DenseMatrix> chol(m1);)
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// std::cout << "dense:\t" << timer.value() << endl;
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BenchTimer timer;
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timer.start();
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@@ -114,27 +118,27 @@ int main(int argc, char *argv[])
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timer.stop();
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std::cout << "dense:\t" << timer.value() << endl;
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int count = 0;
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for (int j=0; j<cols; ++j)
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for (int i=j; i<rows; ++i)
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if (!internal::isMuchSmallerThan(internal::abs(chol.matrixL()(i,j)), 0.1))
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count++;
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std::cout << "dense: " << "nnz = " << count << "\n";
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// std::cout << "dense:\n" << m1 << "\n\n" << chol.matrixL() << endl;
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for (int j = 0; j < cols; ++j)
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for (int i = j; i < rows; ++i)
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if (!internal::isMuchSmallerThan(internal::abs(chol.matrixL()(i, j)), 0.1)) count++;
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std::cout << "dense: "
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<< "nnz = " << count << "\n";
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// std::cout << "dense:\n" << m1 << "\n\n" << chol.matrixL() << endl;
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}
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#endif
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#endif
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// eigen sparse matrices
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doEigen<Eigen::DefaultBackend>("Eigen/Sparse", sm1, Eigen::IncompleteFactorization);
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#ifdef EIGEN_CHOLMOD_SUPPORT
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#ifdef EIGEN_CHOLMOD_SUPPORT
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doEigen<Eigen::Cholmod>("Eigen/Cholmod", sm1, Eigen::IncompleteFactorization);
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#endif
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#endif
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#ifdef EIGEN_TAUCS_SUPPORT
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#ifdef EIGEN_TAUCS_SUPPORT
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doEigen<Eigen::Taucs>("Eigen/Taucs", sm1, Eigen::IncompleteFactorization);
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#endif
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#endif
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#if 0
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#if 0
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// TAUCS
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{
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taucs_ccs_matrix A = sm1.asTaucsMatrix();
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@@ -153,7 +157,7 @@ int main(int argc, char *argv[])
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}
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// CHOLMOD
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#ifdef EIGEN_CHOLMOD_SUPPORT
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#ifdef EIGEN_CHOLMOD_SUPPORT
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{
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cholmod_common c;
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cholmod_start (&c);
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@@ -202,15 +206,10 @@ int main(int argc, char *argv[])
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// std::cout << chol->values.s[i] << " ";
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// }
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}
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#endif
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#endif
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#endif
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#endif
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}
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return 0;
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}
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