Added basic BLAS1 benchmark

bench/blas.cpp

@@ -0,0 +1,63 @@
+#include "viennacl/matrix.hpp"
+#include "viennacl/vector.hpp"
+#include "viennacl/tools/timer.hpp"
+
+#include "atidlas/model/import.hpp"
+#include "atidlas/model/model.hpp"
+
+#include <iomanip>
+#include <stdlib.h>
+
+namespace ad = atidlas;
+typedef atidlas::atidlas_int_t int_t;
+
+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;
+#define BENCHMARK(OP, resname) \
+  OP;\
+  viennacl::backend::finish();\
+  timer.start(); \
+  OP;\
+  viennacl::backend::finish();\
+  float resname = timer.get()
+
+  //BLAS1
+  {
+    for(std::vector<int_t>::const_iterator it = BLAS1_N.begin() ; it != BLAS1_N.end() ; ++it)
+    {
+      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::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);
+    res[i] = std::exp(std::log(min) + (float)(std::log(max) - std::log(min))*i/N);
+  return res;
+}
+
+int main()
+{
+  std::map<std::string, ad::tools::shared_ptr<ad::model> > models = ad::import("geforce_gt_540m.json");
+
+  std::vector<int_t> BLAS1_N = create_log_range(1e3, 1e7, 20);
+
+  std::cout << "Benchmark : BLAS" << std::endl;
+  std::cout << "----------------" << std::endl;
+  bench<float>(BLAS1_N, models);
+}