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/*
This file is part of Leela Zero.
Copyright (C) 2017-2019 Gian-Carlo Pascutto and contributors
Leela Zero 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.
Leela Zero is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with Leela Zero. If not, see <http://www.gnu.org/licenses/>.
Additional permission under GNU GPL version 3 section 7
If you modify this Program, or any covered work, by linking or
combining it with NVIDIA Corporation's libraries from the
NVIDIA CUDA Toolkit and/or the NVIDIA CUDA Deep Neural
Network library and/or the NVIDIA TensorRT inference library
(or a modified version of those libraries), containing parts covered
by the terms of the respective license agreement, the licensors of
this Program grant you additional permission to convey the resulting
work.
*/
#ifndef SGEMM_TUNER_H_INCLUDED
#define SGEMM_TUNER_H_INCLUDED
#include "config.h"
#include <vector>
#include <map>
#include <string>
using Configurations = std::pair<std::string, std::vector<size_t>>;
using Parameters = std::map<std::string, size_t>;
template <typename net_t> class OpenCL;
template <typename net_t>
class Tuner {
OpenCL<net_t> & m_opencl;
cl::Context m_context;
cl::Device m_device;
bool m_use_tensorcore = false;
public:
std::string tune_sgemm(const int m, const int n, const int k,
const int batch_size, const int runs = 4);
std::string load_sgemm_tuners(const int m, const int n, const int k,
const int batch_size);
// list of device types that was tuned in this run.
// This is to prevent the same device from being tuned multiple times.
static std::vector<std::string> tuned_devices;
// version 0 : Initial release
// version 1 : Tuner with additional tensor cores (parameter TCE)
static constexpr auto TUNER_VERSION = 1;
Tuner(OpenCL<net_t> & opencl, cl::Context context, cl::Device device) :
m_opencl(opencl), m_context(context), m_device(device) {}
void enable_tensorcore();
private:
void store_sgemm_tuners(const int m, const int n, const int k,
const int batch_size, std::string tuners);
bool valid_config_sgemm(Parameters p, bool exhaustive);
std::string parameters_to_defines(const Parameters& p);
std::string parameters_to_string(const Parameters& p);
Parameters get_parameters_by_int(const std::vector<Configurations>& opts,
const int n);
std::string sgemm_tuners_from_line(std::string line, const int m,
const int n, const int k,
const int batch_size);
std::vector<Parameters> build_valid_params();
};
#endif