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July 7, 2013 21:01
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/* | |
* This program is free software; you can redistribute it and/or modify | |
* it under the terms of the GNU General Public License as published by | |
* the Free Software Foundation; either version 3 of the License, or | |
* (at your option) any later version. | |
* | |
* Written (W) 2013 Soumyajit De | |
*/ | |
#include <shogun/lib/common.h> | |
#ifdef HAVE_EIGEN3 | |
#include <shogun/lib/Time.h> | |
#include <shogun/lib/SGVector.h> | |
#include <shogun/lib/SGSparseMatrix.h> | |
#include <shogun/lib/SGSparseVector.h> | |
#include <shogun/mathematics/Math.h> | |
#include <shogun/mathematics/eigen3.h> | |
#include <pthread.h> | |
using namespace shogun; | |
using namespace Eigen; | |
struct APPLY_THREAD_PARAM | |
{ | |
int32_t start; | |
int32_t stop; | |
float64_t* result; | |
float64_t* vec; | |
int32_t len; | |
SGSparseVector<float64_t>* sm; | |
}; | |
int32_t get_nnz(SGSparseMatrix<float64_t> m) | |
{ | |
int32_t nnz=0; | |
int32_t n=m.num_vectors; | |
for (int i=0; i<n; i++) | |
{ | |
nnz+=m[i].num_feat_entries; | |
} | |
return nnz; | |
} | |
static void* dot_helper(void* p) | |
{ | |
APPLY_THREAD_PARAM* par=(APPLY_THREAD_PARAM*) p; | |
float64_t* r = par->result; | |
SGSparseVector<float64_t>* m=par->sm; | |
float64_t* vec = par->vec; | |
int32_t len = par->len; | |
int32_t start = par->start; | |
int32_t stop = par->stop; | |
for (index_t i=start; i<stop; ++i) | |
r[i]=m[i].dense_dot(1.0, vec, len, 0.0); | |
} | |
SGVector<float64_t> sg_m_apply(SGSparseMatrix<float64_t> m, SGVector<float64_t> v) | |
{ | |
SGVector<float64_t> r(v.vlen); | |
ASSERT(v.vlen==m.num_vectors); | |
int num_threads=2; | |
pthread_t* threads = SG_MALLOC(pthread_t, num_threads-1); | |
APPLY_THREAD_PARAM* params = SG_MALLOC(APPLY_THREAD_PARAM, num_threads); | |
int32_t step= m.num_vectors/num_threads; | |
int32_t start=0; | |
int32_t stop=m.num_vectors; | |
int32_t t; | |
for (t=0; t<num_threads-1; t++) | |
{ | |
params[t].start = start+t*step; | |
params[t].stop = start+(t+1)*step; | |
params[t].result = r.vector; | |
params[t].sm=m.sparse_matrix; | |
params[t].vec=v.vector; | |
params[t].len=v.vlen; | |
pthread_create(&threads[t], NULL, | |
dot_helper, (void*)¶ms[t]); | |
} | |
params[t].start = start+t*step; | |
params[t].stop = stop; | |
params[t].result = r.vector; | |
params[t].sm=m.sparse_matrix; | |
params[t].vec=v.vector; | |
params[t].len=v.vlen; | |
dot_helper((void*) ¶ms[t]); | |
for (t=0; t<num_threads-1; t++) | |
pthread_join(threads[t], NULL); | |
SG_FREE(params); | |
SG_FREE(threads); | |
return r; | |
} | |
int main(int argc, char** argv) | |
{ | |
Eigen::initParallel(); | |
init_shogun_with_defaults(); | |
//sg_io->set_loglevel(MSG_GCDEBUG); | |
const index_t n=100; | |
const index_t times=5; | |
const index_t size=1000000; | |
SGVector<float64_t> v(size); | |
v.set_const(1.0); | |
Map<VectorXd> map_v(v.vector, v.vlen); | |
CTime time; | |
CMath::init_random(17); | |
SG_SPRINT("time\tshogun (s)\teigen3 (s)\n\n"); | |
for (index_t t=0; t<times; ++t) | |
{ | |
//#ifdef RUN_SHOGUN | |
SGSparseMatrix<float64_t> sg_m(size, size); | |
typedef SGSparseVectorEntry<float64_t> Entry; | |
SGSparseVector<float64_t> *vec=SG_MALLOC(SGSparseVector<float64_t>, size); | |
// for first row | |
Entry *first=SG_MALLOC(Entry, size); | |
// the digonal index for row #1 | |
first[0].feat_index=0; | |
first[0].entry=1.836593; | |
for (index_t i=1; i<size; ++i) | |
{ | |
// fill the index for row #1 | |
first[i].feat_index=i; | |
first[i].entry=0.02; | |
} | |
vec[0].features=first; | |
vec[0].num_feat_entries=size; | |
sg_m[0]=vec[0].get(); | |
// fill the rest of the rows | |
Entry** rest=SG_MALLOC(Entry*, size-1); | |
for (index_t i=0; i<size-1; ++i) | |
{ | |
int num=40; | |
// the first col | |
rest[i]=SG_MALLOC(Entry, num); | |
for (int j=0; j<i && j<num; j++) | |
{ | |
rest[i][j].feat_index=j; | |
rest[i][j].entry=0.01+j; | |
} | |
if (i>num) | |
{ | |
//// the diagonal element | |
rest[i][num-1].feat_index=i+1; | |
rest[i][num-1].entry=1.836593; | |
} | |
vec[i+1].features=rest[i]; | |
vec[i+1].num_feat_entries=num; | |
sg_m[i+1]=vec[i+1].get(); | |
} | |
SGVector<float64_t> r(size); | |
SG_SPRINT("nnz=%d\n", get_nnz(sg_m)); | |
// sg starts | |
time.start(); | |
for (index_t i=0; i<n; ++i) | |
r=sg_m_apply(sg_m, v); | |
float64_t sg_time = time.cur_time_diff(); | |
Map<VectorXd> map_r(r.vector, r.vlen); | |
float64_t sg_norm=map_r.norm(); | |
//#endif // RUN_SHOGUN | |
#ifdef RUN_EIGEN | |
const SparseMatrix<float64_t> &eig_m=EigenSparseUtil<float64_t>::toEigenSparse(sg_m); | |
VectorXd eig_r(size); | |
// eigen3 starts | |
time.start(); | |
for (index_t i=0; i<n; ++i) | |
eig_r=eig_m*map_v; | |
float64_t eig_time = time.cur_time_diff(); | |
float64_t eig_norm=eig_r.norm(); | |
#endif // RUN_EIGEN | |
SG_SPRINT("%d\t%lf\t%lf\n", t, sg_time, eig_time); | |
//ASSERT(sg_time>eig_time); | |
ASSERT(CMath::abs(sg_norm-eig_norm)<=CMath::MACHINE_EPSILON) | |
SG_FREE(vec); | |
SG_FREE(rest); | |
} | |
exit_shogun(); | |
return 0; | |
} | |
#endif // HAVE_EIGEN3 |
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