experiments/STT-tensorflow
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Update to NCCL version 1.3.5. Remove temporary buffer for ncclReduce, it's no longer needed in this version.

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PiperOrigin-RevId: 169221983
This commit is contained in:
A. Unique TensorFlower 2017-09-19 04:07:01 -07:00 committed by TensorFlower Gardener
parent 23da21150d
commit 5882ae35d3
4 changed files with 13 additions and 19 deletions
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10
tensorflow/contrib/nccl/kernels/nccl_manager.cc
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@ -312,11 +312,11 @@ void NcclManager::AddReduceSend(int num_devices, const string& key,
perftools::gputools::StreamExecutor* executor,
int gpu_device_id, EventMgr* event_mgr,
perftools::gputools::Stream* tensor_stream,
const Tensor* in_t, Tensor* temp_t,
const Tensor* in_t,
DoneCallback done_callback) {
std::unique_ptr<Participant> participant(
new Participant(in_t, temp_t, event_mgr, tensor_stream, executor,
gpu_device_id, std::move(done_callback)));
new Participant(in_t, nullptr /* out_t */, event_mgr, tensor_stream,
executor, gpu_device_id, std::move(done_callback)));
AddParticipant(num_devices, key, std::move(participant), in_t->dtype(),
kReduce, reduction_op);
}
@ -462,7 +462,9 @@ void NcclManager::LoopKernelLaunches(NcclStream* nccl_stream) {
}
case kReduce: {
const void* sendbuff = p->in_t->tensor_data().data();
void* recvbuff = const_cast<char*>(p->out_t->tensor_data().data());
void* recvbuff = p->out_t
? const_cast<char*>(p->out_t->tensor_data().data())
: nullptr;
nccl_result = ncclReduce(sendbuff, recvbuff, p->in_t->NumElements(),
data_type, collective->reduction_op,
collective->root_rank, nccl_comm, *cu_stream);

3
tensorflow/contrib/nccl/kernels/nccl_manager.h
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@ -82,8 +82,7 @@ class NcclManager {
perftools::gputools::StreamExecutor* executor,
int gpu_device_id, EventMgr* event_mgr,
perftools::gputools::Stream* tensor_stream,
const Tensor* in_t, Tensor* temp_t,
DoneCallback done_callback);
const Tensor* in_t, DoneCallback done_callback);
void AddReduceRecv(int num_devices, const string& key,
ncclRedOp_t reduction_op,
perftools::gputools::StreamExecutor* executor,

11
tensorflow/contrib/nccl/kernels/nccl_ops.cc
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@ -121,14 +121,7 @@ class NcclReduceSendKernel : public NcclReduceOpBase {
: NcclReduceOpBase(c) {}
void ComputeAsync(OpKernelContext* c, DoneCallback done) override {
const Tensor& in_t = c->input(0);
std::unique_ptr<Tensor> temp_ptr(new Tensor());
OP_REQUIRES_OK_ASYNC(
c, c->allocate_temp(in_t.dtype(), in_t.shape(), temp_ptr.get()), done);
Tensor* temp_t = temp_ptr.release();
auto actual_done = [c, done, temp_t](Status s) {
delete temp_t;
auto actual_done = [c, done](Status s) {
OP_REQUIRES_OK_ASYNC(c, s, done);
done();
};
@ -138,7 +131,7 @@ class NcclReduceSendKernel : public NcclReduceOpBase {
NcclManager::instance()->AddReduceSend(
num_devices(), GetCollectiveKey(c), reduction_op(),
compute_stream->parent(), gpu_info->gpu_id, gpu_info->event_mgr,
compute_stream, &in_t, temp_t, std::move(actual_done));
compute_stream, &c->input(0), std::move(actual_done));
}
};
REGISTER_KERNEL_BUILDER(Name("NcclReduceSend").Device(DEVICE_GPU),

8
tensorflow/workspace.bzl
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@ -629,11 +629,11 @@ def tf_workspace(path_prefix="", tf_repo_name=""):
temp_workaround_http_archive(
name = "nccl_archive",
urls = [
"http://mirror.bazel.build/github.com/nvidia/nccl/archive/29a1a916dc14bb2c00feed3d4820d51fa85be1e6.tar.gz",
"https://github.com/nvidia/nccl/archive/29a1a916dc14bb2c00feed3d4820d51fa85be1e6.tar.gz",
"http://mirror.bazel.build/github.com/nvidia/nccl/archive/03d856977ecbaac87e598c0c4bafca96761b9ac7.tar.gz",
"https://github.com/nvidia/nccl/archive/03d856977ecbaac87e598c0c4bafca96761b9ac7.tar.gz",
],
sha256 = "6387030e37d14762f87eefbc86ee527293ec04745c66ccd820cf7fc0fdc23f92",
strip_prefix = "nccl-29a1a916dc14bb2c00feed3d4820d51fa85be1e6",
sha256 = "2ca86fb6179ecbff789cc67c836139c1bbc0324ed8c04643405a30bf26325176",
strip_prefix = "nccl-03d856977ecbaac87e598c0c4bafca96761b9ac7",
build_file = str(Label("//third_party:nccl.BUILD")),
repository = tf_repo_name,
)