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Use double for GPU Hist node sum. (#7507)

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This commit is contained in:
Jiaming Yuan
2021-12-22 08:41:35 +08:00
committed by GitHub
parent eabec370e4
commit 7f399eac8b
5 changed files with 85 additions and 98 deletions
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88
src/tree/updater_gpu_hist.cu
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@@ -173,7 +173,7 @@ struct GPUHistMakerDevice {
dh::caching_device_vector<int> monotone_constraints;
/*! \brief Sum gradient for each node. */
std::vector<GradientPair> node_sum_gradients;
std::vector<GradientPairPrecise> node_sum_gradients;
TrainParam param;
@@ -239,8 +239,7 @@ struct GPUHistMakerDevice {
dh::safe_cuda(cudaSetDevice(device_id));
tree_evaluator = TreeEvaluator(param, dmat->Info().num_col_, device_id);
this->interaction_constraints.Reset();
std::fill(node_sum_gradients.begin(), node_sum_gradients.end(),
GradientPair());
std::fill(node_sum_gradients.begin(), node_sum_gradients.end(), GradientPairPrecise{});
if (d_gpair.size() != dh_gpair->Size()) {
d_gpair.resize(dh_gpair->Size());
@@ -260,7 +259,7 @@ struct GPUHistMakerDevice {
}
DeviceSplitCandidate EvaluateRootSplit(GradientPair root_sum) {
DeviceSplitCandidate EvaluateRootSplit(GradientPairPrecise root_sum) {
int nidx = RegTree::kRoot;
dh::TemporaryArray<DeviceSplitCandidate> splits_out(1);
GPUTrainingParam gpu_param(param);
@@ -269,16 +268,15 @@ struct GPUHistMakerDevice {
common::Span<bst_feature_t> feature_set =
interaction_constraints.Query(sampled_features->DeviceSpan(), nidx);
auto matrix = page->GetDeviceAccessor(device_id);
EvaluateSplitInputs<GradientSumT> inputs{
nidx,
{root_sum.GetGrad(), root_sum.GetHess()},
gpu_param,
feature_set,
feature_types,
matrix.feature_segments,
matrix.gidx_fvalue_map,
matrix.min_fvalue,
hist.GetNodeHistogram(nidx)};
EvaluateSplitInputs<GradientSumT> inputs{nidx,
root_sum,
gpu_param,
feature_set,
feature_types,
matrix.feature_segments,
matrix.gidx_fvalue_map,
matrix.min_fvalue,
hist.GetNodeHistogram(nidx)};
auto gain_calc = tree_evaluator.GetEvaluator<GPUTrainingParam>();
EvaluateSingleSplit(dh::ToSpan(splits_out), gain_calc, inputs);
std::vector<DeviceSplitCandidate> result(1);
@@ -307,28 +305,24 @@ struct GPUHistMakerDevice {
left_nidx);
auto matrix = page->GetDeviceAccessor(device_id);
EvaluateSplitInputs<GradientSumT> left{
left_nidx,
{candidate.split.left_sum.GetGrad(),
candidate.split.left_sum.GetHess()},
gpu_param,
left_feature_set,
feature_types,
matrix.feature_segments,
matrix.gidx_fvalue_map,
matrix.min_fvalue,
hist.GetNodeHistogram(left_nidx)};
EvaluateSplitInputs<GradientSumT> right{
right_nidx,
{candidate.split.right_sum.GetGrad(),
candidate.split.right_sum.GetHess()},
gpu_param,
right_feature_set,
feature_types,
matrix.feature_segments,
matrix.gidx_fvalue_map,
matrix.min_fvalue,
hist.GetNodeHistogram(right_nidx)};
EvaluateSplitInputs<GradientSumT> left{left_nidx,
candidate.split.left_sum,
gpu_param,
left_feature_set,
feature_types,
matrix.feature_segments,
matrix.gidx_fvalue_map,
matrix.min_fvalue,
hist.GetNodeHistogram(left_nidx)};
EvaluateSplitInputs<GradientSumT> right{right_nidx,
candidate.split.right_sum,
gpu_param,
right_feature_set,
feature_types,
matrix.feature_segments,
matrix.gidx_fvalue_map,
matrix.min_fvalue,
hist.GetNodeHistogram(right_nidx)};
auto d_splits_out = dh::ToSpan(splits_out);
EvaluateSplits(d_splits_out, tree_evaluator.GetEvaluator<GPUTrainingParam>(), left, right);
dh::TemporaryArray<GPUExpandEntry> entries(2);
@@ -502,12 +496,11 @@ struct GPUHistMakerDevice {
auto d_ridx = row_partitioner->GetRows();
GPUTrainingParam param_d(param);
dh::TemporaryArray<GradientPair> device_node_sum_gradients(node_sum_gradients.size());
dh::TemporaryArray<GradientPairPrecise> device_node_sum_gradients(node_sum_gradients.size());
dh::safe_cuda(
cudaMemcpyAsync(device_node_sum_gradients.data().get(), node_sum_gradients.data(),
sizeof(GradientPair) * node_sum_gradients.size(),
cudaMemcpyHostToDevice));
dh::safe_cuda(cudaMemcpyAsync(device_node_sum_gradients.data().get(), node_sum_gradients.data(),
sizeof(GradientPairPrecise) * node_sum_gradients.size(),
cudaMemcpyHostToDevice));
auto d_position = row_partitioner->GetPosition();
auto d_node_sum_gradients = device_node_sum_gradients.data().get();
auto evaluator = tree_evaluator.GetEvaluator<GPUTrainingParam>();
@@ -623,13 +616,12 @@ struct GPUHistMakerDevice {
GPUExpandEntry InitRoot(RegTree* p_tree, dh::AllReducer* reducer) {
constexpr bst_node_t kRootNIdx = 0;
dh::XGBCachingDeviceAllocator<char> alloc;
GradientPair root_sum = dh::Reduce(
thrust::cuda::par(alloc),
thrust::device_ptr<GradientPair const>(gpair.data()),
thrust::device_ptr<GradientPair const>(gpair.data() + gpair.size()),
GradientPair{}, thrust::plus<GradientPair>{});
rabit::Allreduce<rabit::op::Sum, float>(reinterpret_cast<float*>(&root_sum),
2);
auto gpair_it = dh::MakeTransformIterator<GradientPairPrecise>(
dh::tbegin(gpair), [] __device__(auto const& gpair) { return GradientPairPrecise{gpair}; });
GradientPairPrecise root_sum =
dh::Reduce(thrust::cuda::par(alloc), gpair_it, gpair_it + gpair.size(),
GradientPairPrecise{}, thrust::plus<GradientPairPrecise>{});
rabit::Allreduce<rabit::op::Sum, double>(reinterpret_cast<double*>(&root_sum), 2);
this->BuildHist(kRootNIdx);
this->AllReduceHist(kRootNIdx, reducer);