1 /* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
2
3 Licensed under the Apache License, Version 2.0 (the "License");
4 you may not use this file except in compliance with the License.
5 You may obtain a copy of the License at
6
7 http://www.apache.org/licenses/LICENSE-2.0
8
9 Unless required by applicable law or agreed to in writing, software
10 distributed under the License is distributed on an "AS IS" BASIS,
11 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12 See the License for the specific language governing permissions and
13 limitations under the License.
14 ==============================================================================*/
15 #include "tensorflow/core/kernels/collective_nccl_reducer.h"
16
17 #if GOOGLE_CUDA || TENSORFLOW_USE_ROCM
18
19 #include "tensorflow/core/common_runtime/collective_util.h"
20 #include "tensorflow/core/nccl/nccl_manager.h"
21 #include "tensorflow/core/platform/tracing.h"
22 #include "tensorflow/core/profiler/lib/traceme.h"
23
24 namespace tensorflow {
25
Run(StatusCallback done)26 void NcclReducer::Run(StatusCallback done) {
27 Tensor group_size;
28 std::unique_ptr<Notification> group_size_ready;
29 Status group_size_status;
30 std::unique_ptr<Notification> nccl_done;
31 if (col_params_->final_op) {
32 group_size_ready = absl::make_unique<Notification>();
33 // Create an on-device scalar value from group_size_.
34 // TODO(ayushd, tucker): avoid this copy by either reusing across
35 // invocations or providing the scalar to the kernel in host memory.
36 Tensor group_size_val;
37 switch (col_ctx_->output->dtype()) {
38 case DT_HALF:
39 group_size_val =
40 Tensor(static_cast<Eigen::half>(col_params_->group.group_size));
41 break;
42 case DT_FLOAT:
43 group_size_val =
44 Tensor(static_cast<float>(col_params_->group.group_size));
45 break;
46 case DT_DOUBLE:
47 group_size_val =
48 Tensor(static_cast<double>(col_params_->group.group_size));
49 break;
50 case DT_INT32:
51 group_size_val =
52 Tensor(static_cast<int32>(col_params_->group.group_size));
53 break;
54 case DT_INT64:
55 group_size_val =
56 Tensor(static_cast<int64>(col_params_->group.group_size));
57 break;
58 default:
59 done(errors::Internal("Unsupported type ",
60 DataTypeString(col_ctx_->output->dtype())));
61 return;
62 }
63 group_size = Tensor(
64 col_ctx_->device->GetAllocator(col_ctx_->op_ctx->input_alloc_attr(0)),
65 col_ctx_->output->dtype(), TensorShape({}));
66 DeviceContext* op_dev_ctx = col_ctx_->op_ctx->op_device_context();
67 // Enqueue copy on gpu stream.
68 Notification* copy_note = group_size_ready.get();
69 op_dev_ctx->CopyCPUTensorToDevice(
70 &group_size_val, col_ctx_->device, &group_size,
71 [copy_note, &group_size_status](const Status& s) {
72 group_size_status = s;
73 copy_note->Notify();
74 });
75 nccl_done = absl::make_unique<Notification>();
76 }
77
78 Status nccl_status;
79 // If no final_op, then the NCCL callback is just `done`. Otherwise we notify
80 // `nccl_done` so that we can then perform `final_op`.
81 StatusCallback done_callback;
82 if (col_params_->final_op) {
83 Notification* nccl_note = nccl_done.get();
84 done_callback = [nccl_note, &nccl_status](const Status& s) {
85 nccl_status = s;
86 nccl_note->Notify();
87 };
88 } else {
89 done_callback = std::move(done);
90 }
91 // Hold a ref to col_params for the rest of this function.
92 col_params_->Ref();
93 core::ScopedUnref unref(col_params_);
94 col_ctx_->nccl_communicator->Enqueue(col_ctx_, std::move(done_callback));
95
96 // If no final_op, then this OpKernel is non-blocking.
97 if (!col_params_->final_op) {
98 return;
99 }
100
101 // Wait for nccl op and group_size copy to succeed, then do final_op. This
102 // kernel needs to wait for both notifications because they execute on
103 // different GPU streams with no ordering guarantees between them.
104 // TODO(b/80529858): make this entirely non-blocking by getting rid of the
105 // waits below and calling final op from the nccl kernel's DoneCallback.
106 {
107 profiler::TraceMe activity("Nccl", profiler::TraceMeLevel::kInfo);
108 nccl_done->WaitForNotification();
109 }
110 {
111 profiler::TraceMe activity("GroupSizeCopy", profiler::TraceMeLevel::kInfo);
112 group_size_ready->WaitForNotification();
113 }
114 Status final_status =
115 group_size_status.ok() ? nccl_status : group_size_status;
116 if (final_status.ok()) {
117 final_status = collective_util::ComputeBinOp(
118 col_ctx_->op_ctx, col_ctx_->op_params, col_ctx_->device,
119 col_params_->final_op, col_ctx_->output, &group_size);
120 }
121 done(final_status);
122 }
123
124 REGISTER_COLLECTIVE(NcclReduce, NcclReducer);
125
126 } // namespace tensorflow
127
128 #endif // GOOGLE_CUDA || TENSORFLOW_USE_ROCM
129