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remove device shards (#4867)

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This commit is contained in:
Rong Ou
2019-09-24 22:15:46 -07:00
committed by Jiaming Yuan
parent 0b89cd1dfa
commit 562bb0ae31
8 changed files with 572 additions and 635 deletions
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47
src/tree/updater_gpu_hist.cu
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@@ -435,7 +435,7 @@ __global__ void SharedMemHistKernel(xgboost::ELLPackMatrix matrix,
// Manage memory for a single GPU
template <typename GradientSumT>
struct DeviceShard {
struct GPUHistMakerDevice {
int device_id;
EllpackPageImpl* page;
@@ -474,12 +474,12 @@ struct DeviceShard {
std::function<bool(ExpandEntry, ExpandEntry)>>;
std::unique_ptr<ExpandQueue> qexpand;
DeviceShard(int _device_id,
EllpackPageImpl* _page,
bst_uint _n_rows,
TrainParam _param,
uint32_t column_sampler_seed,
uint32_t n_features)
GPUHistMakerDevice(int _device_id,
EllpackPageImpl* _page,
bst_uint _n_rows,
TrainParam _param,
uint32_t column_sampler_seed,
uint32_t n_features)
: device_id(_device_id),
page(_page),
n_rows(_n_rows),
@@ -487,12 +487,12 @@ struct DeviceShard {
prediction_cache_initialised(false),
column_sampler(column_sampler_seed),
interaction_constraints(param, n_features) {
monitor.Init(std::string("DeviceShard") + std::to_string(device_id));
monitor.Init(std::string("GPUHistMakerDevice") + std::to_string(device_id));
}
void InitHistogram();
~DeviceShard() { // NOLINT
~GPUHistMakerDevice() { // NOLINT
dh::safe_cuda(cudaSetDevice(device_id));
for (auto& stream : streams) {
dh::safe_cuda(cudaStreamDestroy(stream));
@@ -781,7 +781,7 @@ struct DeviceShard {
auto left_node_rows = row_partitioner->GetRows(nidx_left).size();
auto right_node_rows = row_partitioner->GetRows(nidx_right).size();
// Decide whether to build the left histogram or right histogram
// Find the largest number of training instances on any given Shard
// Find the largest number of training instances on any given device
// Assume this will be the bottleneck and avoid building this node if
// possible
std::vector<size_t> max_reduce;
@@ -939,7 +939,7 @@ struct DeviceShard {
};
template <typename GradientSumT>
inline void DeviceShard<GradientSumT>::InitHistogram() {
inline void GPUHistMakerDevice<GradientSumT>::InitHistogram() {
CHECK(!(param.max_leaves == 0 && param.max_depth == 0))
<< "Max leaves and max depth cannot both be unconstrained for "
"gpu_hist.";
@@ -1026,19 +1026,17 @@ class GPUHistMakerSpecialised {
page->Init(device_, param_.max_bin, hist_maker_param_.gpu_batch_nrows);
}
// Create device shard
dh::safe_cuda(cudaSetDevice(device_));
shard_.reset(new DeviceShard<GradientSumT>(device_,
page,
info_->num_row_,
param_,
column_sampling_seed,
info_->num_col_));
maker_.reset(new GPUHistMakerDevice<GradientSumT>(device_,
page,
info_->num_row_,
param_,
column_sampling_seed,
info_->num_col_));
// Init global data for each shard
monitor_.StartCuda("InitHistogram");
dh::safe_cuda(cudaSetDevice(device_));
shard_->InitHistogram();
maker_->InitHistogram();
monitor_.StopCuda("InitHistogram");
p_last_fmat_ = dmat;
@@ -1077,18 +1075,17 @@ class GPUHistMakerSpecialised {
monitor_.StopCuda("InitData");
gpair->SetDevice(device_);
shard_->UpdateTree(gpair, p_fmat, p_tree, &reducer_);
maker_->UpdateTree(gpair, p_fmat, p_tree, &reducer_);
}
bool UpdatePredictionCache(
const DMatrix* data, HostDeviceVector<bst_float>* p_out_preds) {
if (shard_ == nullptr || p_last_fmat_ == nullptr || p_last_fmat_ != data) {
if (maker_ == nullptr || p_last_fmat_ == nullptr || p_last_fmat_ != data) {
return false;
}
monitor_.StartCuda("UpdatePredictionCache");
p_out_preds->SetDevice(device_);
dh::safe_cuda(cudaSetDevice(shard_->device_id));
shard_->UpdatePredictionCache(p_out_preds->DevicePointer());
maker_->UpdatePredictionCache(p_out_preds->DevicePointer());
monitor_.StopCuda("UpdatePredictionCache");
return true;
}
@@ -1096,7 +1093,7 @@ class GPUHistMakerSpecialised {
TrainParam param_; // NOLINT
MetaInfo* info_{}; // NOLINT
std::unique_ptr<DeviceShard<GradientSumT>> shard_; // NOLINT
std::unique_ptr<GPUHistMakerDevice<GradientSumT>> maker_; // NOLINT
private:
bool initialised_;