106 lines
3.6 KiB
C++
106 lines
3.6 KiB
C++
/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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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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#include <memory>
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#include "tensorflow/core/grappler/devices.h"
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#include "tensorflow/core/platform/byte_order.h"
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#include "tensorflow/core/platform/cpu_info.h"
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#if GOOGLE_CUDA || TENSORFLOW_USE_ROCM
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#include "tensorflow/core/common_runtime/gpu/gpu_init.h"
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#include "tensorflow/core/platform/stream_executor.h"
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#endif // GOOGLE_CUDA
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namespace tensorflow {
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namespace grappler {
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int GetNumAvailableGPUs(
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const std::pair<int, int>& min_cuda_compute_capability) {
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int num_eligible_gpus = 0;
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#if TENSORFLOW_USE_ROCM
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if (min_cuda_compute_capability.first != 0 ||
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min_cuda_compute_capability.second != 0) {
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LOG(ERROR) << "GetNumAvailableGPUs() should receive zero "
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"min_cuda_compute_capability";
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return 0;
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}
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#endif
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#if GOOGLE_CUDA || TENSORFLOW_USE_ROCM
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if (ValidateGPUMachineManager().ok()) {
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se::Platform* gpu_manager = GPUMachineManager();
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if (gpu_manager != nullptr) {
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int num_gpus = gpu_manager->VisibleDeviceCount();
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for (int i = 0; i < num_gpus; i++) {
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#if GOOGLE_CUDA
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auto desc_status = gpu_manager->DescriptionForDevice(i);
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if (desc_status.ok()) {
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auto desc = desc_status.ConsumeValueOrDie();
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int cc_major = 0;
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int cc_minor = 0;
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desc->cuda_compute_capability(&cc_major, &cc_minor);
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std::pair<int, int> cuda_compute_capability(cc_major, cc_minor);
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int min_gpu_core_count = 8;
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if (desc->core_count() >= min_gpu_core_count &&
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cuda_compute_capability >= min_cuda_compute_capability) {
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num_eligible_gpus++;
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}
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}
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#else
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num_eligible_gpus++;
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#endif
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}
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}
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}
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#if GOOGLE_CUDA
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LOG(INFO)
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<< "Number of eligible GPUs (core count >= 8, compute capability >= "
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<< min_cuda_compute_capability.first << "."
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<< min_cuda_compute_capability.second << "): " << num_eligible_gpus;
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#else
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LOG(INFO) << "Number of eligible GPUs: " << num_eligible_gpus;
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#endif
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#else // GOOGLE_CUDA || TENSORFLOW_USE_ROCM
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LOG(INFO)
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<< "Number of eligible GPUs (core count >= 8, compute capability >= "
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<< min_cuda_compute_capability.first << "."
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<< min_cuda_compute_capability.second << "): " << num_eligible_gpus
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<< " (Note: TensorFlow was not compiled with CUDA or ROCm support)";
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#endif // GOOGLE_CUDA || TENSORFLOW_USE_ROCM
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return num_eligible_gpus;
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}
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int64 AvailableGPUMemory(int gpu_id) {
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#if GOOGLE_CUDA || TENSORFLOW_USE_ROCM
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// Look up the device, to see its attributes.
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se::Platform* gpu_platform = GPUMachineManager();
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CHECK_LT(gpu_id, gpu_platform->VisibleDeviceCount());
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se::StreamExecutor* se = gpu_platform->ExecutorForDevice(gpu_id).ValueOrDie();
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int64 total_memory, available_memory;
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CHECK(se->DeviceMemoryUsage(&available_memory, &total_memory));
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return available_memory;
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#else
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return 0;
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#endif
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}
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int GetNumAvailableLogicalCPUCores() { return port::NumSchedulableCPUs(); }
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} // end namespace grappler
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} // end namespace tensorflow
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