add a sparse setter bench
diff --git a/bench/sparse_setter.cpp b/bench/sparse_setter.cpp
new file mode 100644
index 0000000..9011295
--- /dev/null
+++ b/bench/sparse_setter.cpp
@@ -0,0 +1,224 @@
+
+//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 300000
+#endif
+
+#ifndef NBPERROW
+#define NBPERROW 12
+#endif
+
+#ifndef REPEAT
+#define REPEAT 1
+#endif
+
+#define EIGEN_GOOGLEHASH_SUPPORT
+#include <google/sparse_hash_map>
+#include "BenchSparseUtil.h"
+
+
+#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 std::vector<Vector2i> Coordinates;
+typedef std::vector<float> Values;
+
+EIGEN_DONT_INLINE Scalar* setrand_eigen_gnu_hash(const Coordinates& coords, const Values& vals);
+EIGEN_DONT_INLINE Scalar* setrand_eigen_google_dense(const Coordinates& coords, const Values& vals);
+EIGEN_DONT_INLINE Scalar* setrand_eigen_google_sparse(const Coordinates& coords, const Values& vals);
+EIGEN_DONT_INLINE Scalar* setrand_ublas_mapped(const Coordinates& coords, const Values& vals);
+EIGEN_DONT_INLINE Scalar* setrand_ublas_coord(const Coordinates& coords, const Values& vals);
+EIGEN_DONT_INLINE Scalar* setrand_ublas_compressed(const Coordinates& coords, const Values& vals);
+EIGEN_DONT_INLINE Scalar* setrand_mtl(const Coordinates& coords, const Values& vals);
+
+int main(int argc, char *argv[])
+{
+ int rows = SIZE;
+ int cols = SIZE;
+ //float density = float(NBPERROW)/float(SIZE);
+
+ BenchTimer timer;
+ Coordinates coords;
+ Values values;
+ for (int i=0; i<cols*NBPERROW; ++i)
+ {
+ coords.push_back(Vector2i(ei_random<int>(0,rows-1),ei_random<int>(0,cols-1)));
+ values.push_back(ei_random<Scalar>());
+ }
+ std::cout << "nnz = " << coords.size() << "\n";
+
+ // dense matrices
+ #ifdef DENSEMATRIX
+ {
+ timer.reset();
+ timer.start();
+ for (int k=0; k<REPEAT; ++k)
+ setrand_eigen_dense(coords,values);
+ timer.stop();
+ std::cout << "Eigen Dense\t" << timer.value() << "\n";
+ }
+ #endif
+
+ // eigen sparse matrices
+ {
+ timer.reset();
+ timer.start();
+ for (int k=0; k<REPEAT; ++k)
+ setrand_eigen_gnu_hash(coords,values);
+ timer.stop();
+ std::cout << "Eigen gnu hashmap\t" << timer.value() << "\n";
+ }
+ {
+ timer.reset();
+ timer.start();
+ for (int k=0; k<REPEAT; ++k)
+ setrand_eigen_google_dense(coords,values);
+ timer.stop();
+ std::cout << "Eigen google dense\t" << timer.value() << "\n";
+ }
+ {
+ timer.reset();
+ timer.start();
+ for (int k=0; k<REPEAT; ++k)
+ setrand_eigen_google_sparse(coords,values);
+ timer.stop();
+ std::cout << "Eigen google sparse\t" << timer.value() << "\n";
+ }
+
+ #ifndef NOUBLAS
+ {
+ timer.reset();
+ timer.start();
+ for (int k=0; k<REPEAT; ++k)
+ setrand_ublas_mapped(coords,values);
+ timer.stop();
+ std::cout << "ublas mapped\t" << timer.value() << "\n";
+ }
+ {
+ timer.reset();
+ timer.start();
+ for (int k=0; k<REPEAT; ++k)
+ setrand_ublas_compressed(coords,values);
+ timer.stop();
+ std::cout << "ublas comp\t" << timer.value() << "\n";
+ }
+ {
+ timer.reset();
+ timer.start();
+ for (int k=0; k<REPEAT; ++k)
+ setrand_ublas_coord(coords,values);
+ timer.stop();
+ std::cout << "ublas coord\t" << timer.value() << "\n";
+ }
+ #endif
+
+
+ // MTL4
+ #ifndef NOMTL
+ {
+ timer.reset();
+ timer.start();
+ for (int k=0; k<REPEAT; ++k)
+ setrand_mtl(coords,values);
+ timer.stop();
+ std::cout << "MTL\t" << timer.value() << "\n";
+ }
+ #endif
+
+ return 0;
+}
+
+EIGEN_DONT_INLINE Scalar* setrand_eigen_gnu_hash(const Coordinates& coords, const Values& vals)
+{
+ using namespace Eigen;
+ SparseMatrix<Scalar> mat(SIZE,SIZE);
+ {
+ RandomSetter<SparseMatrix<Scalar>, StdMapTraits > setter(mat);
+ for (int i=0; i<coords.size(); ++i)
+ {
+ setter(coords[i].x(), coords[i].y()) = vals[i];
+ }
+// std::cout << "check mem\n"; getchar();
+ }
+ return 0;//&mat.coeffRef(coords[0].x(), coords[0].y());
+}
+
+EIGEN_DONT_INLINE Scalar* setrand_eigen_google_dense(const Coordinates& coords, const Values& vals)
+{
+ using namespace Eigen;
+ SparseMatrix<Scalar> mat(SIZE,SIZE);
+ {
+ RandomSetter<SparseMatrix<Scalar>, GoogleDenseHashMapTraits> setter(mat);
+ for (int i=0; i<coords.size(); ++i)
+ setter(coords[i].x(), coords[i].y()) = vals[i];
+// std::cout << "check mem\n"; getchar();
+ }
+ return 0;//&mat.coeffRef(coords[0].x(), coords[0].y());
+}
+
+EIGEN_DONT_INLINE Scalar* setrand_eigen_google_sparse(const Coordinates& coords, const Values& vals)
+{
+ using namespace Eigen;
+ SparseMatrix<Scalar> mat(SIZE,SIZE);
+ {
+ RandomSetter<SparseMatrix<Scalar>, GoogleSparseHashMapTraits> setter(mat);
+ for (int i=0; i<coords.size(); ++i)
+ setter(coords[i].x(), coords[i].y()) = vals[i];
+// std::cout << "check mem\n"; getchar();
+ }
+ return 0;//&mat.coeffRef(coords[0].x(), coords[0].y());
+}
+#ifndef NOUBLAS
+EIGEN_DONT_INLINE Scalar* setrand_ublas_mapped(const Coordinates& coords, const Values& vals)
+{
+ using namespace boost;
+ using namespace boost::numeric;
+ using namespace boost::numeric::ublas;
+ mapped_matrix<Scalar> aux(SIZE,SIZE);
+ for (int i=0; i<coords.size(); ++i)
+ {
+ aux(coords[i].x(), coords[i].y()) = vals[i];
+ }
+// std::cout << "check mem\n"; getchar();
+ compressed_matrix<Scalar> mat(aux);
+ return 0;// &mat(coords[0].x(), coords[0].y());
+}
+EIGEN_DONT_INLINE Scalar* setrand_ublas_coord(const Coordinates& coords, const Values& vals)
+{
+ using namespace boost;
+ using namespace boost::numeric;
+ using namespace boost::numeric::ublas;
+ coordinate_matrix<Scalar> aux(SIZE,SIZE);
+ for (int i=0; i<coords.size(); ++i)
+ {
+ aux(coords[i].x(), coords[i].y()) = vals[i];
+ }
+ compressed_matrix<Scalar> mat(aux);
+ return 0;//&mat(coords[0].x(), coords[0].y());
+}
+EIGEN_DONT_INLINE Scalar* setrand_ublas_compressed(const Coordinates& coords, const Values& vals)
+{
+ using namespace boost;
+ using namespace boost::numeric;
+ using namespace boost::numeric::ublas;
+ compressed_matrix<Scalar> mat(SIZE,SIZE);
+ for (int i=0; i<coords.size(); ++i)
+ {
+ mat(coords[i].x(), coords[i].y()) = vals[i];
+ }
+ return 0;//&mat(coords[0].x(), coords[0].y());
+}
+#endif
+
+#ifndef NOMTL
+EIGEN_DONT_INLINE void setrand_mtl(const Coordinates& coords, const Values& vals);
+#endif
+