diff --git a/bench/sparse_setter.cpp b/bench/sparse_setter.cpp
new file mode 100644
index 0000000..a9f0b11
--- /dev/null
+++ b/bench/sparse_setter.cpp
@@ -0,0 +1,485 @@
+
+//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 100000
+#endif
+
+#ifndef NBPERROW
+#define NBPERROW 24
+#endif
+
+#ifndef REPEAT
+#define REPEAT 2
+#endif
+
+#ifndef NBTRIES
+#define NBTRIES 2
+#endif
+
+#ifndef KK
+#define KK 10
+#endif
+
+#ifndef NOGOOGLE
+#define EIGEN_GOOGLEHASH_SUPPORT
+#include <google/sparse_hash_map>
+#endif
+
+#include "BenchSparseUtil.h"
+
+#define CHECK_MEM
+// #define CHECK_MEM  std/**/::cout << "check mem\n"; getchar();
+
+#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* setinnerrand_eigen(const Coordinates& coords, const Values& vals);
+EIGEN_DONT_INLINE Scalar* setrand_eigen_dynamic(const Coordinates& coords, const Values& vals);
+EIGEN_DONT_INLINE Scalar* setrand_eigen_compact(const Coordinates& coords, const Values& vals);
+EIGEN_DONT_INLINE Scalar* setrand_eigen_sumeq(const Coordinates& coords, const Values& vals);
+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_scipy(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_ublas_genvec(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;
+  bool fullyrand = true;
+
+  BenchTimer timer;
+  Coordinates coords;
+  Values values;
+  if(fullyrand)
+  {
+    Coordinates pool;
+    pool.reserve(cols*NBPERROW);
+    std::cerr << "fill pool" << "\n";
+    for (int i=0; i<cols*NBPERROW; )
+    {
+//       DynamicSparseMatrix<int> stencil(SIZE,SIZE);
+      Vector2i ij(internal::random<int>(0,rows-1),internal::random<int>(0,cols-1));
+//       if(stencil.coeffRef(ij.x(), ij.y())==0)
+      {
+//         stencil.coeffRef(ij.x(), ij.y()) = 1;
+        pool.push_back(ij);
+
+      }
+      ++i;
+    }
+    std::cerr << "pool ok" << "\n";
+    int n = cols*NBPERROW*KK;
+    coords.reserve(n);
+    values.reserve(n);
+    for (int i=0; i<n; ++i)
+    {
+      int i = internal::random<int>(0,pool.size());
+      coords.push_back(pool[i]);
+      values.push_back(internal::random<Scalar>());
+    }
+  }
+  else
+  {
+    for (int j=0; j<cols; ++j)
+    for (int i=0; i<NBPERROW; ++i)
+    {
+      coords.push_back(Vector2i(internal::random<int>(0,rows-1),j));
+      values.push_back(internal::random<Scalar>());
+    }
+  }
+  std::cout << "nnz = " << coords.size()  << "\n";
+  CHECK_MEM
+
+    // dense matrices
+    #ifdef DENSEMATRIX
+    {
+      BENCH(setrand_eigen_dense(coords,values);)
+      std::cout << "Eigen Dense\t" << timer.value() << "\n";
+    }
+    #endif
+
+    // eigen sparse matrices
+//     if (!fullyrand)
+//     {
+//       BENCH(setinnerrand_eigen(coords,values);)
+//       std::cout << "Eigen fillrand\t" << timer.value() << "\n";
+//     }
+    {
+      BENCH(setrand_eigen_dynamic(coords,values);)
+      std::cout << "Eigen dynamic\t" << timer.value() << "\n";
+    }
+//     {
+//       BENCH(setrand_eigen_compact(coords,values);)
+//       std::cout << "Eigen compact\t" << timer.value() << "\n";
+//     }
+    {
+      BENCH(setrand_eigen_sumeq(coords,values);)
+      std::cout << "Eigen sumeq\t" << timer.value() << "\n";
+    }
+    {
+//       BENCH(setrand_eigen_gnu_hash(coords,values);)
+//       std::cout << "Eigen std::map\t" << timer.value() << "\n";
+    }
+    {
+      BENCH(setrand_scipy(coords,values);)
+      std::cout << "scipy\t" << timer.value() << "\n";
+    }
+    #ifndef NOGOOGLE
+    {
+      BENCH(setrand_eigen_google_dense(coords,values);)
+      std::cout << "Eigen google dense\t" << timer.value() << "\n";
+    }
+    {
+      BENCH(setrand_eigen_google_sparse(coords,values);)
+      std::cout << "Eigen google sparse\t" << timer.value() << "\n";
+    }
+    #endif
+
+    #ifndef NOUBLAS
+    {
+//       BENCH(setrand_ublas_mapped(coords,values);)
+//       std::cout << "ublas mapped\t" << timer.value() << "\n";
+    }
+    {
+      BENCH(setrand_ublas_genvec(coords,values);)
+      std::cout << "ublas vecofvec\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
+    {
+      BENCH(setrand_mtl(coords,values));
+      std::cout << "MTL\t" << timer.value() << "\n";
+    }
+    #endif
+
+  return 0;
+}
+
+EIGEN_DONT_INLINE Scalar* setinnerrand_eigen(const Coordinates& coords, const Values& vals)
+{
+  using namespace Eigen;
+  SparseMatrix<Scalar> mat(SIZE,SIZE);
+  //mat.startFill(2000000/*coords.size()*/);
+  for (int i=0; i<coords.size(); ++i)
+  {
+    mat.insert(coords[i].x(), coords[i].y()) = vals[i];
+  }
+  mat.finalize();
+  CHECK_MEM;
+  return 0;
+}
+
+EIGEN_DONT_INLINE Scalar* setrand_eigen_dynamic(const Coordinates& coords, const Values& vals)
+{
+  using namespace Eigen;
+  DynamicSparseMatrix<Scalar> mat(SIZE,SIZE);
+  mat.reserve(coords.size()/10);
+  for (int i=0; i<coords.size(); ++i)
+  {
+    mat.coeffRef(coords[i].x(), coords[i].y()) += vals[i];
+  }
+  mat.finalize();
+  CHECK_MEM;
+  return &mat.coeffRef(coords[0].x(), coords[0].y());
+}
+
+EIGEN_DONT_INLINE Scalar* setrand_eigen_sumeq(const Coordinates& coords, const Values& vals)
+{
+  using namespace Eigen;
+  int n = coords.size()/KK;
+  DynamicSparseMatrix<Scalar> mat(SIZE,SIZE);
+  for (int j=0; j<KK; ++j)
+  {
+    DynamicSparseMatrix<Scalar> aux(SIZE,SIZE);
+    mat.reserve(n);
+    for (int i=j*n; i<(j+1)*n; ++i)
+    {
+      aux.insert(coords[i].x(), coords[i].y()) += vals[i];
+    }
+    aux.finalize();
+    mat += aux;
+  }
+  return &mat.coeffRef(coords[0].x(), coords[0].y());
+}
+
+EIGEN_DONT_INLINE Scalar* setrand_eigen_compact(const Coordinates& coords, const Values& vals)
+{
+  using namespace Eigen;
+  DynamicSparseMatrix<Scalar> setter(SIZE,SIZE);
+  setter.reserve(coords.size()/10);
+  for (int i=0; i<coords.size(); ++i)
+  {
+    setter.coeffRef(coords[i].x(), coords[i].y()) += vals[i];
+  }
+  SparseMatrix<Scalar> mat = setter;
+  CHECK_MEM;
+  return &mat.coeffRef(coords[0].x(), coords[0].y());
+}
+
+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];
+    }
+    CHECK_MEM;
+  }
+  return &mat.coeffRef(coords[0].x(), coords[0].y());
+}
+
+#ifndef NOGOOGLE
+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];
+    CHECK_MEM;
+  }
+  return &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];
+    CHECK_MEM;
+  }
+  return &mat.coeffRef(coords[0].x(), coords[0].y());
+}
+#endif
+
+
+template <class T>
+void coo_tocsr(const int n_row,
+               const int n_col,
+               const int nnz,
+               const Coordinates Aij,
+               const Values Ax,
+                     int Bp[],
+                     int Bj[],
+                     T Bx[])
+{
+    //compute number of non-zero entries per row of A coo_tocsr
+    std::fill(Bp, Bp + n_row, 0);
+
+    for (int n = 0; n < nnz; n++){
+        Bp[Aij[n].x()]++;
+    }
+
+    //cumsum the nnz per row to get Bp[]
+    for(int i = 0, cumsum = 0; i < n_row; i++){
+        int temp = Bp[i];
+        Bp[i] = cumsum;
+        cumsum += temp;
+    }
+    Bp[n_row] = nnz;
+
+    //write Aj,Ax into Bj,Bx
+    for(int n = 0; n < nnz; n++){
+        int row  = Aij[n].x();
+        int dest = Bp[row];
+
+        Bj[dest] = Aij[n].y();
+        Bx[dest] = Ax[n];
+
+        Bp[row]++;
+    }
+
+    for(int i = 0, last = 0; i <= n_row; i++){
+        int temp = Bp[i];
+        Bp[i]  = last;
+        last   = temp;
+    }
+
+    //now Bp,Bj,Bx form a CSR representation (with possible duplicates)
+}
+
+template< class T1, class T2 >
+bool kv_pair_less(const std::pair<T1,T2>& x, const std::pair<T1,T2>& y){
+    return x.first < y.first;
+}
+
+
+template<class I, class T>
+void csr_sort_indices(const I n_row,
+                      const I Ap[],
+                            I Aj[],
+                            T Ax[])
+{
+    std::vector< std::pair<I,T> > temp;
+
+    for(I i = 0; i < n_row; i++){
+        I row_start = Ap[i];
+        I row_end   = Ap[i+1];
+
+        temp.clear();
+
+        for(I jj = row_start; jj < row_end; jj++){
+            temp.push_back(std::make_pair(Aj[jj],Ax[jj]));
+        }
+
+        std::sort(temp.begin(),temp.end(),kv_pair_less<I,T>);
+
+        for(I jj = row_start, n = 0; jj < row_end; jj++, n++){
+            Aj[jj] = temp[n].first;
+            Ax[jj] = temp[n].second;
+        }
+    }
+}
+
+template <class I, class T>
+void csr_sum_duplicates(const I n_row,
+                        const I n_col,
+                              I Ap[],
+                              I Aj[],
+                              T Ax[])
+{
+    I nnz = 0;
+    I row_end = 0;
+    for(I i = 0; i < n_row; i++){
+        I jj = row_end;
+        row_end = Ap[i+1];
+        while( jj < row_end ){
+            I j = Aj[jj];
+            T x = Ax[jj];
+            jj++;
+            while( jj < row_end && Aj[jj] == j ){
+                x += Ax[jj];
+                jj++;
+            }
+            Aj[nnz] = j;
+            Ax[nnz] = x;
+            nnz++;
+        }
+        Ap[i+1] = nnz;
+    }
+}
+
+EIGEN_DONT_INLINE Scalar* setrand_scipy(const Coordinates& coords, const Values& vals)
+{
+  using namespace Eigen;
+  SparseMatrix<Scalar> mat(SIZE,SIZE);
+  mat.resizeNonZeros(coords.size());
+//   std::cerr << "setrand_scipy...\n";
+  coo_tocsr<Scalar>(SIZE,SIZE, coords.size(), coords, vals, mat._outerIndexPtr(), mat._innerIndexPtr(), mat._valuePtr());
+//   std::cerr << "coo_tocsr ok\n";
+
+  csr_sort_indices(SIZE, mat._outerIndexPtr(), mat._innerIndexPtr(), mat._valuePtr());
+
+  csr_sum_duplicates(SIZE, SIZE, mat._outerIndexPtr(), mat._innerIndexPtr(), mat._valuePtr());
+
+  mat.resizeNonZeros(mat._outerIndexPtr()[SIZE]);
+
+  return &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];
+  }
+  CHECK_MEM;
+  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());
+}*/
+EIGEN_DONT_INLINE Scalar* setrand_ublas_genvec(const Coordinates& coords, const Values& vals)
+{
+  using namespace boost;
+  using namespace boost::numeric;
+  using namespace boost::numeric::ublas;
+
+//   ublas::vector<coordinate_vector<Scalar> > foo;
+  generalized_vector_of_vector<Scalar, row_major, ublas::vector<coordinate_vector<Scalar> > > aux(SIZE,SIZE);
+  for (int i=0; i<coords.size(); ++i)
+  {
+    aux(coords[i].x(), coords[i].y()) += vals[i];
+  }
+  CHECK_MEM;
+  compressed_matrix<Scalar,row_major> mat(aux);
+  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
+