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These methods take reference to a boolean whose value signals whether benchmark instances pending for execution are to be skipped. void benchmark->run_or_skip(bool &) is called by Python to ensure that KeyboardInterrupt is properly handled in scripts that contain multiple benchmarks, or in case when single benchmark script is executed on a machine with more than one device.
95 lines
2.9 KiB
Plaintext
95 lines
2.9 KiB
Plaintext
/*
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* Copyright 2021 NVIDIA Corporation
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*
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* Licensed under the Apache License, Version 2.0 with the LLVM exception
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* (the "License"); you may not use this file except in compliance with
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* the License.
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*
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* You may obtain a copy of the License at
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*
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* http://llvm.org/foundation/relicensing/LICENSE.txt
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#pragma once
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#include <nvbench/axes_metadata.cuh>
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#include <nvbench/benchmark_base.cuh>
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#include <nvbench/runner.cuh>
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#include <nvbench/type_list.cuh>
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#include <string>
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#include <vector>
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namespace nvbench
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{
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/**
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* Holds a complete benchmark specification: a KernelGenerator and parameter
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* axes.
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*
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* Creation and configuration of this class is documented in the NVBench
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* [README](../README.md) file. Refer to that for usage details.
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*
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* This class is purposefully kept small to reduce the amount of template code
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* generated for each benchmark. Most of the functionality is implemented in
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* nvbench::benchmark_base -- this class only holds type aliases related to the
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* `KernelGenerator` and `TypeAxes` parameters, and exposes them to
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* `benchmark_base` through a private virtual API.
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*
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* Delegates responsibilities to the following classes:
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* - nvbench::benchmark_base: all non-templated benchmark handling.
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*
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* @tparam KernelGenerator See the [README](../README.md).
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* @tparam TypeAxes A `nvbench::type_list` of `nvbench::type_list`s. See the
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* [README](../README.md) for more details.
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*/
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template <typename KernelGenerator, typename TypeAxes = nvbench::type_list<>>
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struct benchmark final : public benchmark_base
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{
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using kernel_generator = KernelGenerator;
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using type_axes = TypeAxes;
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using type_configs = nvbench::tl::cartesian_product<type_axes>;
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static constexpr std::size_t num_type_configs = nvbench::tl::size<type_configs>{};
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benchmark(kernel_generator kgen = {})
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: benchmark_base(type_axes{})
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, m_kernel_generator(kgen)
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{}
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private:
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std::unique_ptr<benchmark_base> do_clone() const final
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{
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return std::make_unique<benchmark>(this->m_kernel_generator);
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}
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void do_set_type_axes_names(std::vector<std::string> names) final
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{
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m_axes.set_type_axes_names(std::move(names));
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}
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void do_run() final
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{
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nvbench::runner<benchmark> runner{*this, this->m_kernel_generator};
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runner.generate_states();
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runner.run();
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}
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void do_run_or_skip(bool &skip_remaining) final
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{
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nvbench::runner<benchmark> runner{*this, this->m_kernel_generator};
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runner.generate_states();
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runner.run_or_skip(skip_remaining);
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}
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kernel_generator m_kernel_generator;
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};
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} // namespace nvbench
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