Squashed 'third_party/eigen/' content from commit 61d72f6
Change-Id: Iccc90fa0b55ab44037f018046d2fcffd90d9d025
git-subtree-dir: third_party/eigen
git-subtree-split: 61d72f6383cfa842868c53e30e087b0258177257
diff --git a/bench/sparse_dense_product.cpp b/bench/sparse_dense_product.cpp
new file mode 100644
index 0000000..f3f5194
--- /dev/null
+++ b/bench/sparse_dense_product.cpp
@@ -0,0 +1,187 @@
+
+//g++ -O3 -g0 -DNDEBUG sparse_product.cpp -I.. -I/home/gael/Coding/LinearAlgebra/mtl4/ -DDENSITY=0.005 -DSIZE=10000 && ./a.out
+//g++ -O3 -g0 -DNDEBUG sparse_product.cpp -I.. -I/home/gael/Coding/LinearAlgebra/mtl4/ -DDENSITY=0.05 -DSIZE=2000 && ./a.out
+// -DNOGMM -DNOMTL -DCSPARSE
+// -I /home/gael/Coding/LinearAlgebra/CSparse/Include/ /home/gael/Coding/LinearAlgebra/CSparse/Lib/libcsparse.a
+#ifndef SIZE
+#define SIZE 650000
+#endif
+
+#ifndef DENSITY
+#define DENSITY 0.01
+#endif
+
+#ifndef REPEAT
+#define REPEAT 1
+#endif
+
+#include "BenchSparseUtil.h"
+
+#ifndef MINDENSITY
+#define MINDENSITY 0.0004
+#endif
+
+#ifndef NBTRIES
+#define NBTRIES 10
+#endif
+
+#define BENCH(X) \
+ timer.reset(); \
+ for (int _j=0; _j<NBTRIES; ++_j) { \
+ timer.start(); \
+ for (int _k=0; _k<REPEAT; ++_k) { \
+ X \
+ } timer.stop(); }
+
+
+#ifdef CSPARSE
+cs* cs_sorted_multiply(const cs* a, const cs* b)
+{
+ cs* A = cs_transpose (a, 1) ;
+ cs* B = cs_transpose (b, 1) ;
+ cs* D = cs_multiply (B,A) ; /* D = B'*A' */
+ cs_spfree (A) ;
+ cs_spfree (B) ;
+ cs_dropzeros (D) ; /* drop zeros from D */
+ cs* C = cs_transpose (D, 1) ; /* C = D', so that C is sorted */
+ cs_spfree (D) ;
+ return C;
+}
+#endif
+
+int main(int argc, char *argv[])
+{
+ int rows = SIZE;
+ int cols = SIZE;
+ float density = DENSITY;
+
+ EigenSparseMatrix sm1(rows,cols);
+ DenseVector v1(cols), v2(cols);
+ v1.setRandom();
+
+ BenchTimer timer;
+ for (float density = DENSITY; density>=MINDENSITY; density*=0.5)
+ {
+ //fillMatrix(density, rows, cols, sm1);
+ fillMatrix2(7, rows, cols, sm1);
+
+ // dense matrices
+ #ifdef DENSEMATRIX
+ {
+ std::cout << "Eigen Dense\t" << density*100 << "%\n";
+ DenseMatrix m1(rows,cols);
+ eiToDense(sm1, m1);
+
+ timer.reset();
+ timer.start();
+ for (int k=0; k<REPEAT; ++k)
+ v2 = m1 * v1;
+ timer.stop();
+ std::cout << " a * v:\t" << timer.best() << " " << double(REPEAT)/timer.best() << " * / sec " << endl;
+
+ timer.reset();
+ timer.start();
+ for (int k=0; k<REPEAT; ++k)
+ v2 = m1.transpose() * v1;
+ timer.stop();
+ std::cout << " a' * v:\t" << timer.best() << endl;
+ }
+ #endif
+
+ // eigen sparse matrices
+ {
+ std::cout << "Eigen sparse\t" << sm1.nonZeros()/float(sm1.rows()*sm1.cols())*100 << "%\n";
+
+ BENCH(asm("#myc"); v2 = sm1 * v1; asm("#myd");)
+ std::cout << " a * v:\t" << timer.best()/REPEAT << " " << double(REPEAT)/timer.best(REAL_TIMER) << " * / sec " << endl;
+
+
+ BENCH( { asm("#mya"); v2 = sm1.transpose() * v1; asm("#myb"); })
+
+ std::cout << " a' * v:\t" << timer.best()/REPEAT << endl;
+ }
+
+// {
+// DynamicSparseMatrix<Scalar> m1(sm1);
+// std::cout << "Eigen dyn-sparse\t" << m1.nonZeros()/float(m1.rows()*m1.cols())*100 << "%\n";
+//
+// BENCH(for (int k=0; k<REPEAT; ++k) v2 = m1 * v1;)
+// std::cout << " a * v:\t" << timer.value() << endl;
+//
+// BENCH(for (int k=0; k<REPEAT; ++k) v2 = m1.transpose() * v1;)
+// std::cout << " a' * v:\t" << timer.value() << endl;
+// }
+
+ // GMM++
+ #ifndef NOGMM
+ {
+ std::cout << "GMM++ sparse\t" << density*100 << "%\n";
+ //GmmDynSparse gmmT3(rows,cols);
+ GmmSparse m1(rows,cols);
+ eiToGmm(sm1, m1);
+
+ std::vector<Scalar> gmmV1(cols), gmmV2(cols);
+ Map<Matrix<Scalar,Dynamic,1> >(&gmmV1[0], cols) = v1;
+ Map<Matrix<Scalar,Dynamic,1> >(&gmmV2[0], cols) = v2;
+
+ BENCH( asm("#myx"); gmm::mult(m1, gmmV1, gmmV2); asm("#myy"); )
+ std::cout << " a * v:\t" << timer.value() << endl;
+
+ BENCH( gmm::mult(gmm::transposed(m1), gmmV1, gmmV2); )
+ std::cout << " a' * v:\t" << timer.value() << endl;
+ }
+ #endif
+
+ #ifndef NOUBLAS
+ {
+ std::cout << "ublas sparse\t" << density*100 << "%\n";
+ UBlasSparse m1(rows,cols);
+ eiToUblas(sm1, m1);
+
+ boost::numeric::ublas::vector<Scalar> uv1, uv2;
+ eiToUblasVec(v1,uv1);
+ eiToUblasVec(v2,uv2);
+
+// std::vector<Scalar> gmmV1(cols), gmmV2(cols);
+// Map<Matrix<Scalar,Dynamic,1> >(&gmmV1[0], cols) = v1;
+// Map<Matrix<Scalar,Dynamic,1> >(&gmmV2[0], cols) = v2;
+
+ BENCH( uv2 = boost::numeric::ublas::prod(m1, uv1); )
+ std::cout << " a * v:\t" << timer.value() << endl;
+
+// BENCH( boost::ublas::prod(gmm::transposed(m1), gmmV1, gmmV2); )
+// std::cout << " a' * v:\t" << timer.value() << endl;
+ }
+ #endif
+
+ // MTL4
+ #ifndef NOMTL
+ {
+ std::cout << "MTL4\t" << density*100 << "%\n";
+ MtlSparse m1(rows,cols);
+ eiToMtl(sm1, m1);
+ mtl::dense_vector<Scalar> mtlV1(cols, 1.0);
+ mtl::dense_vector<Scalar> mtlV2(cols, 1.0);
+
+ timer.reset();
+ timer.start();
+ for (int k=0; k<REPEAT; ++k)
+ mtlV2 = m1 * mtlV1;
+ timer.stop();
+ std::cout << " a * v:\t" << timer.value() << endl;
+
+ timer.reset();
+ timer.start();
+ for (int k=0; k<REPEAT; ++k)
+ mtlV2 = trans(m1) * mtlV1;
+ timer.stop();
+ std::cout << " a' * v:\t" << timer.value() << endl;
+ }
+ #endif
+
+ std::cout << "\n\n";
+ }
+
+ return 0;
+}
+