ec86d80f19
Also removed duplicate comments for subclass methods. PiperOrigin-RevId: 346807683 Change-Id: I2ab9b5038d5e5fc991bfee53d0081c5eecf51906
64 lines
2.4 KiB
C++
64 lines
2.4 KiB
C++
/* Copyright 2020 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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#ifndef TENSORFLOW_COMPILER_XLA_PJRT_GPU_DEVICE_H_
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#define TENSORFLOW_COMPILER_XLA_PJRT_GPU_DEVICE_H_
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#include <memory>
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#include "tensorflow/compiler/xla/pjrt/distributed/client.h"
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#include "tensorflow/compiler/xla/pjrt/pjrt_stream_executor_client.h"
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#include "tensorflow/compiler/xla/statusor.h"
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#include "tensorflow/core/common_runtime/bfc_allocator.h"
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namespace xla {
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class GpuDevice : public PjRtStreamExecutorDevice {
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public:
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GpuDevice(int id, std::unique_ptr<LocalDeviceState> local_device_state,
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std::string device_kind, int node_id);
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};
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struct GpuAllocatorConfig {
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enum class Kind {
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kDefault, // Client picks the best option for the platform.
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kPlatform, // The platform's default.
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kBFC, // Allocator using a "Best-Fit with Coalescing" algorithm. Currently
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// only available for GPU.
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};
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Kind kind = Kind::kDefault;
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// Only used if kind == kBFC. The maximum fraction of available memory to
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// allocate.
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double memory_fraction = 0.9;
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// Only used if kind == kBFC. If true, the allocator will immediately allocate
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// the maximum amount allowed by `memory_fraction`. This reduces
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// fragmentation, allowing more of the total memory to be used. If false, the
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// allocator will allocate more memory as allocations are requested.
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bool preallocate = true;
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};
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// distributed_client may be nullptr in non-distributed settings.
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// distributed_client should be in the connected state before calling this
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// function.
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StatusOr<std::unique_ptr<PjRtClient>> GetGpuClient(
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bool asynchronous, const GpuAllocatorConfig& allocator_config,
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std::shared_ptr<DistributedRuntimeClient> distributed_client, int node_id);
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} // namespace xla
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#endif // TENSORFLOW_COMPILER_XLA_PJRT_GPU_DEVICE_H_
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