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authorGravatar Gael Guennebaud <g.gael@free.fr>2008-06-29 21:29:12 +0000
committerGravatar Gael Guennebaud <g.gael@free.fr>2008-06-29 21:29:12 +0000
commit37a50fa5268d6d408c74ab2d380785ce07ec302c (patch)
treecfb51b6dd0a9f89a67cbc5af4f16cbcc7eba7f58 /bench/sparse_trisolver.cpp
parentfbdecf09e174c0b9bc45695cab8fb9c49656ebfa (diff)
* added an in-place version of inverseProduct which
might be twice faster fot small fixed size matrix * added a sparse triangular solver (sparse version of inverseProduct) * various other improvements in the Sparse module
Diffstat (limited to 'bench/sparse_trisolver.cpp')
-rw-r--r--bench/sparse_trisolver.cpp206
1 files changed, 206 insertions, 0 deletions
diff --git a/bench/sparse_trisolver.cpp b/bench/sparse_trisolver.cpp
new file mode 100644
index 000000000..27362c11b
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+++ b/bench/sparse_trisolver.cpp
@@ -0,0 +1,206 @@
+
+//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
+
+#ifndef SIZE
+#define SIZE 10000
+#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(); }
+
+typedef SparseMatrix<Scalar,Upper> EigenSparseTriMatrix;
+typedef SparseMatrix<Scalar,RowMajorBit|Upper> EigenSparseTriMatrixRow;
+
+void fillMatrix(float density, int rows, int cols, EigenSparseTriMatrix& dst)
+{
+ dst.startFill(rows*cols*density);
+ for(int j = 0; j < cols; j++)
+ {
+ for(int i = 0; i < j; i++)
+ {
+ Scalar v = (ei_random<float>(0,1) < density) ? ei_random<Scalar>() : 0;
+ if (v!=0)
+ dst.fill(i,j) = v;
+ }
+ dst.fill(j,j) = ei_random<Scalar>();
+ }
+ dst.endFill();
+}
+
+int main(int argc, char *argv[])
+{
+ int rows = SIZE;
+ int cols = SIZE;
+ float density = DENSITY;
+ BenchTimer timer;
+ #if 1
+ EigenSparseTriMatrix sm1(rows,cols);
+ VectorXf b = VectorXf::random(cols);
+ VectorXf x = VectorXf::random(cols);
+
+ bool densedone = false;
+
+ for (float density = DENSITY; density>=MINDENSITY; density*=0.5)
+ {
+ EigenSparseTriMatrix sm1(rows, cols);
+ fillMatrix(density, rows, cols, sm1);
+
+ // dense matrices
+ #ifdef DENSEMATRIX
+ if (!densedone)
+ {
+ densedone = true;
+ std::cout << "Eigen Dense\t" << density*100 << "%\n";
+ DenseMatrix m1(rows,cols);
+ Matrix<Scalar,Dynamic,Dynamic,Dynamic,Dynamic,RowMajorBit> m2(rows,cols);
+ eiToDense(sm1, m1);
+ m2 = m1;
+
+ BENCH(x = m1.marked<Upper>().inverseProduct(b);)
+ std::cout << " colmajor^-1 * b:\t" << timer.value() << endl;
+ std::cerr << x.transpose() << "\n";
+
+ BENCH(x = m2.marked<Upper>().inverseProduct(b);)
+ std::cout << " rowmajor^-1 * b:\t" << timer.value() << endl;
+ std::cerr << x.transpose() << "\n";
+ }
+ #endif
+
+ // eigen sparse matrices
+ {
+ std::cout << "Eigen sparse\t" << density*100 << "%\n";
+ EigenSparseTriMatrixRow sm2 = sm1;
+
+ BENCH(x = sm1.inverseProduct(b);)
+ std::cout << " colmajor^-1 * b:\t" << timer.value() << endl;
+ std::cerr << x.transpose() << "\n";
+
+ BENCH(x = sm2.inverseProduct(b);)
+ std::cout << " rowmajor^-1 * b:\t" << timer.value() << endl;
+ std::cerr << x.transpose() << "\n";
+
+// x = b;
+// BENCH(sm1.inverseProductInPlace(x);)
+// std::cout << " colmajor^-1 * b:\t" << timer.value() << " (inplace)" << endl;
+// std::cerr << x.transpose() << "\n";
+//
+// x = b;
+// BENCH(sm2.inverseProductInPlace(x);)
+// std::cout << " rowmajor^-1 * b:\t" << timer.value() << " (inplace)" << endl;
+// std::cerr << x.transpose() << "\n";
+ }
+
+ // GMM++
+ #ifndef NOGMM
+ {
+ std::cout << "GMM++ sparse\t" << density*100 << "%\n";
+ GmmSparse m1(rows,cols);
+ gmm::csr_matrix<Scalar> m2;
+ eiToGmm(sm1, m1);
+ gmm::copy(m1,m2);
+ std::vector<Scalar> gmmX(cols), gmmB(cols);
+ Map<Matrix<Scalar,Dynamic,1> >(&gmmX[0], cols) = x;
+ Map<Matrix<Scalar,Dynamic,1> >(&gmmB[0], cols) = b;
+
+ gmmX = gmmB;
+ BENCH(gmm::upper_tri_solve(m1, gmmX, false);)
+ std::cout << " colmajor^-1 * b:\t" << timer.value() << endl;
+ std::cerr << Map<Matrix<Scalar,Dynamic,1> >(&gmmX[0], cols).transpose() << "\n";
+
+ gmmX = gmmB;
+ BENCH(gmm::upper_tri_solve(m2, gmmX, false);)
+ timer.stop();
+ std::cout << " rowmajor^-1 * b:\t" << timer.value() << endl;
+ std::cerr << Map<Matrix<Scalar,Dynamic,1> >(&gmmX[0], cols).transpose() << "\n";
+ }
+ #endif
+
+ // MTL4
+ #ifndef NOMTL
+ {
+ std::cout << "MTL4\t" << density*100 << "%\n";
+ MtlSparse m1(rows,cols);
+ MtlSparseRowMajor m2(rows,cols);
+ eiToMtl(sm1, m1);
+ m2 = m1;
+ mtl::dense_vector<Scalar> x(rows, 1.0);
+ mtl::dense_vector<Scalar> b(rows, 1.0);
+
+ BENCH(x = mtl::upper_trisolve(m1,b);)
+ std::cout << " colmajor^-1 * b:\t" << timer.value() << endl;
+// std::cerr << x << "\n";
+
+ BENCH(x = mtl::upper_trisolve(m2,b);)
+ std::cout << " rowmajor^-1 * b:\t" << timer.value() << endl;
+// std::cerr << x << "\n";
+ }
+ #endif
+
+
+
+ }
+ #endif
+
+ #if 0
+ // bench small matrices (in-place versus return bye value)
+ {
+ timer.reset();
+ for (int _j=0; _j<10; ++_j) {
+ Matrix4f m = Matrix4f::random();
+ Vector4f b = Vector4f::random();
+ Vector4f x = Vector4f::random();
+ timer.start();
+ for (int _k=0; _k<1000000; ++_k) {
+ b = m.inverseProduct(b);
+ }
+ timer.stop();
+ }
+ std::cout << "4x4 :\t" << timer.value() << endl;
+ }
+
+ {
+ timer.reset();
+ for (int _j=0; _j<10; ++_j) {
+ Matrix4f m = Matrix4f::random();
+ Vector4f b = Vector4f::random();
+ Vector4f x = Vector4f::random();
+ timer.start();
+ for (int _k=0; _k<1000000; ++_k) {
+ m.inverseProductInPlace(x);
+ }
+ timer.stop();
+ }
+ std::cout << "4x4 IP :\t" << timer.value() << endl;
+ }
+ #endif
+
+ std::cout << "\n\n";
+
+ return 0;
+}
+