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FastDeploy/third_party/eigen/bench/sparse_setter.cpp
Jack Zhou 355382ad63 Move eigen to third party (#282) 
* remove useless statement

* Add eigen to third_party dir

* remove reducdant lines
2022-09-26 19:24:02 +08:00

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// 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
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