1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
|
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
// SPDX-FileCopyrightText: Copyright Contributors to the Kokkos project
// This file tests the categorical tuner
#include <Kokkos_Macros.hpp>
#ifdef KOKKOS_ENABLE_EXPERIMENTAL_CXX20_MODULES
import kokkos.core;
#else
#include <Kokkos_Core.hpp>
#endif
#include <unistd.h>
struct point {
float x;
float y;
float z;
};
void do_computation(const point& test_point) {
usleep(((unsigned int)test_point.x) * 100);
}
using namespace Kokkos::Tools::Experimental;
int main(int argc, char* argv[]) {
Kokkos::initialize(argc, argv);
{
VariableInfo info;
info.category = StatisticalCategory::kokkos_value_categorical;
info.valueQuantity = CandidateValueType::kokkos_value_unbounded;
info.type = ValueType::kokkos_value_string;
size_t input = declare_input_type("kernel", info);
VariableValue kernel_value = make_variable_value(input, "abs");
size_t kernel_context = get_new_context_id();
begin_context(kernel_context);
set_input_values(kernel_context, 1, &kernel_value);
std::vector<point> points;
points.push_back({1.0, 1.0, 1.0});
points.push_back({10.0, 10.0, 10.0});
points.push_back({0.0, 0.0, 0.0});
auto tuner =
Kokkos::Tools::Experimental::make_categorical_tuner("points", points);
for (decltype(points)::size_type x = 0; x < 3000; ++x) {
point test_point = tuner.begin();
do_computation(test_point);
tuner.end();
}
end_context(kernel_context);
}
Kokkos::finalize();
}
|
