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Improved benchmark suite

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This commit is contained in:
Philippe Tillet
2014-11-06 07:07:27 -05:00
parent 2be82fc272
commit 146f54b32c
5 changed files with 174 additions and 70 deletions
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100
bench/blas.cpp
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@@ -1,26 +1,31 @@
//#define VIENNACL_DEBUG_ALL
#include "viennacl/matrix.hpp"
#include "viennacl/vector.hpp"
#include "viennacl/tools/timer.hpp"
#include "viennacl/linalg/prod.hpp"
#include "viennacl/linalg/inner_prod.hpp"
#include "viennacl/scheduler/execute.hpp"
#include "atidlas/tools/misc.hpp"
#include "atidlas/model/import.hpp"
#include "atidlas/model/model.hpp"
#include "common.hpp"
#include <iomanip>
#include <stdlib.h>
namespace ad = atidlas;
typedef atidlas::atidlas_int_t int_t;
template<class T>
float bandwidth(std::size_t N, float t)
void bench(std::map<std::string, ad::tools::shared_ptr<ad::model> > & models)
{
return N * sizeof(T) * 1e-9 / t;
}
typedef viennacl::matrix<T,viennacl::column_major> matrix_type;
typedef viennacl::vector<T> vector_type;
template<class T>
void bench(std::vector<int_t> BLAS1_N, std::map<std::string, ad::tools::shared_ptr<ad::model> > & models)
{
viennacl::tools::timer timer;
float total_time = 0;
std::vector<T> times;
@@ -30,7 +35,7 @@ void bench(std::vector<int_t> BLAS1_N, std::map<std::string, ad::tools::shared_p
total_time = 0;\
OP;\
viennacl::backend::finish();\
while(total_time < 1e-1){\
while(total_time < 1e-2){\
timer.start(); \
OP;\
viennacl::backend::finish();\
@@ -40,36 +45,67 @@ void bench(std::vector<int_t> BLAS1_N, std::map<std::string, ad::tools::shared_p
viennacl::backend::finish();\
float resname = ad::tools::median(times);
std::cout << "#N PerfNaive PerfModel PerfOpt" << std::endl;
#define BENCH(declarations, statement_op, sizes, measure, N, key) \
std::cout << "#" << key << std::endl;\
for(std::vector<int_t>::const_iterator it = sizes.begin() ; it != sizes.end() ; ++it)\
{\
declarations;\
viennacl::scheduler::statement statement(statement_op);\
BENCHMARK(y = x + y, time_viennacl);\
BENCHMARK(models[key]->execute(statement), time_model);\
BENCHMARK(models[key]->execute(statement, true), time_unique_kernel);\
models[key]->tune(statement);\
BENCHMARK(models[key]->execute(statement), time_opt);\
std::cout << *it << " " << measure<T>(N, time_viennacl) << " " << measure<T>(N,time_unique_kernel) << " " << measure<T>(N,time_model) << " " << measure<T>(N,time_opt) << std::endl;\
if(models.find(key)!=models.end()){\
if(!first)\
{\
std::cout << std::endl;\
std::cout << std::endl;\
}\
std::cout << "#" << key << std::endl;\
for(std::vector<int_t>::const_iterator it = sizes.begin() ; it != sizes.end() ; ++it)\
{\
declarations;\
viennacl::scheduler::statement statement(statement_op);\
BENCHMARK(models.at(key)->execute(statement), time_model);\
BENCHMARK(models[key]->execute(statement, true), time_unique_kernel);\
models[key]->tune(statement);\
BENCHMARK(models[key]->execute(statement), time_opt);\
std::cout << *it << " " << measure<T>(N,time_unique_kernel) << " " << measure<T>(N,time_model) << " " << measure<T>(N,time_opt) << std::endl;\
}\
}\
#define DECLARE(type, ...) type __VA_ARGS__
#define ARGS(...) __VA_ARGS__
BENCH(DECLARE(viennacl::vector<T>, x(*it), y(*it)), ARGS(y, viennacl::op_assign(), x + y), BLAS1_N, bandwidth, 3*(*it), "vector-axpy-float32");
std::cout << std::endl;
std::cout << std::endl;
}
/*---------*/
/*--BLAS1--*/
/*---------*/
std::vector<int_t> create_log_range(int_t min, int_t max, int_t N)
{
std::vector<int_t> res(N);
for(int_t i = 0 ; i < N ; ++i)
res[i] = std::exp(std::log(min) + (float)(std::log(max) - std::log(min))*i/N);
return res;
//AXPY
bool first =true;
BENCH(DECLARE(viennacl::vector<T>, x(*it), y(*it)), ARGS(y, viennacl::op_assign(), x + y),
BLAS1_N, bandwidth, 3*(*it), "vector-axpy-float32");
first=false;
//DOT
BENCH(DECLARE(viennacl::scalar<T> s(0)); DECLARE(vector_type, x(*it), y(*it)), ARGS(s, viennacl::op_assign(), viennacl::linalg::inner_prod(x,y)),
BLAS1_N, bandwidth, 2*(*it), "reduction-float32");
/*---------*/
/*--BLAS2--*/
/*---------*/
//N-layout
for(std::vector<int>::const_iterator Mit = BLAS2_M.begin() ; Mit != BLAS2_M.end() ; ++Mit)
{
BENCH(DECLARE(matrix_type, A(*Mit,*it)); DECLARE(vector_type, y(*Mit), x(*it)),ARGS(y, viennacl::op_assign(), viennacl::linalg::prod(A,x)), BLAS2_N,
bandwidth, (*Mit)*(*it), "row-wise-reductionN-float32");
}
//T-layout
for(std::vector<int>::const_iterator Mit = BLAS2_M.begin() ; Mit != BLAS2_M.end() ; ++Mit)
{
BENCH(DECLARE(matrix_type, A(*it,*Mit)) ; DECLARE(vector_type, y(*Mit), x(*it)), ARGS(y, viennacl::op_assign(), viennacl::linalg::prod(viennacl::trans(A),x)), BLAS2_N,
bandwidth, (*Mit)*(*it), "row-wise-reductionT-float32");
}
/*---------*/
/*--BLAS3--*/
/*---------*/
}
int main(int argc, char* argv[])
@@ -81,9 +117,7 @@ int main(int argc, char* argv[])
}
std::map<std::string, ad::tools::shared_ptr<ad::model> > models = ad::import(argv[1]);
std::vector<int_t> BLAS1_N = create_log_range(1e3, 2e7, 50);
std::cout << "#Benchmark : BLAS" << std::endl;
std::cout << "#----------------" << std::endl;
bench<float>(BLAS1_N, models);
bench<float>(models);
}