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Now using the median for benchmarking

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This commit is contained in:
Philippe Tillet
2014-10-29 17:03:24 +01:00
parent 4712e3f235
commit 83bce648a0
2 changed files with 34 additions and 8 deletions
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31
bench/blas.cpp
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@@ -2,6 +2,7 @@
#include "viennacl/vector.hpp"
#include "viennacl/tools/timer.hpp"
#include "atidlas/tools/misc.hpp"
#include "atidlas/model/import.hpp"
#include "atidlas/model/model.hpp"
@@ -15,13 +16,23 @@ 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;
#define BENCHMARK(OP, resname) \
times.clear();\
total_time = 0;\
OP;\
viennacl::backend::finish();\
timer.start(); \
OP;\
while(total_time < 1e-1){\
timer.start(); \
OP;\
viennacl::backend::finish();\
times.push_back(timer.get());\
total_time += times.back();\
}\
viennacl::backend::finish();\
float resname = timer.get()
float resname = ad::tools::median(times);
//BLAS1
{
@@ -29,13 +40,13 @@ void bench(std::vector<int_t> BLAS1_N, std::map<std::string, ad::tools::shared_p
{
viennacl::vector<T> x(*it), y(*it), z(*it);
viennacl::scheduler::statement statement(z, viennacl::op_assign(), x + y);
BENCHMARK(models["vector-axpy-float32"]->execute(statement), time_model);
BENCHMARK(models["vector-axpy-float32"]->execute(statement, true), time_unique_kernel);
models["vector-axpy-float32"]->tune(statement);
BENCHMARK(models["vector-axpy-float32"]->execute(statement), time_opt);
std::cout << *it << " " << time_unique_kernel << " " << time_model << " " << time_opt << std::endl;
std::cout << *it << " " << 3*(*it)*sizeof(T)*1e-9/time_unique_kernel << " " << 3*(*it)*sizeof(T)*1e-9/time_model << " " << 3*(*it)*sizeof(T)*1e-9/time_opt << std::endl;
}
}
@@ -51,11 +62,15 @@ std::vector<int_t> create_log_range(int_t min, int_t max, int_t N)
return res;
}
int main()
int main(int argc, char* argv[])
{
std::map<std::string, ad::tools::shared_ptr<ad::model> > models = ad::import("geforce_gt_540m.json");
if(argc != 2)
{
std::cerr << "Usage : PROG model_file" << std::endl;
}
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, 1e7, 20);
std::vector<int_t> BLAS1_N = create_log_range(1e3, 2e7, 50);
std::cout << "Benchmark : BLAS" << std::endl;
std::cout << "----------------" << std::endl;