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Partial rewrite EllpackPage (#5352)

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This commit is contained in:
Rory Mitchell
2020-03-11 10:15:53 +13:00
committed by GitHub
parent 7a99f8f27f
commit 3ad4333b0e
23 changed files with 496 additions and 733 deletions
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32
src/tree/updater_gpu_hist.cu
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@@ -180,15 +180,15 @@ template <int BLOCK_THREADS, typename ReduceT, typename ScanT,
typename MaxReduceT, typename TempStorageT, typename GradientSumT>
__device__ void EvaluateFeature(
int fidx, common::Span<const GradientSumT> node_histogram,
const xgboost::EllpackMatrix& matrix,
const EllpackDeviceAccessor& matrix,
DeviceSplitCandidate* best_split, // shared memory storing best split
const DeviceNodeStats& node, const GPUTrainingParam& param,
TempStorageT* temp_storage, // temp memory for cub operations
int constraint, // monotonic_constraints
const ValueConstraint& value_constraint) {
// Use pointer from cut to indicate begin and end of bins for each feature.
uint32_t gidx_begin = matrix.info.feature_segments[fidx]; // begining bin
uint32_t gidx_end = matrix.info.feature_segments[fidx + 1]; // end bin for i^th feature
uint32_t gidx_begin = matrix.feature_segments[fidx]; // begining bin
uint32_t gidx_end = matrix.feature_segments[fidx + 1]; // end bin for i^th feature
// Sum histogram bins for current feature
GradientSumT const feature_sum = ReduceFeature<BLOCK_THREADS, ReduceT>(
@@ -236,9 +236,9 @@ __device__ void EvaluateFeature(
int split_gidx = (scan_begin + threadIdx.x) - 1;
float fvalue;
if (split_gidx < static_cast<int>(gidx_begin)) {
fvalue = matrix.info.min_fvalue[fidx];
fvalue = matrix.min_fvalue[fidx];
} else {
fvalue = matrix.info.gidx_fvalue_map[split_gidx];
fvalue = matrix.gidx_fvalue_map[split_gidx];
}
GradientSumT left = missing_left ? bin + missing : bin;
GradientSumT right = parent_sum - left;
@@ -254,7 +254,7 @@ __global__ void EvaluateSplitKernel(
common::Span<const GradientSumT> node_histogram, // histogram for gradients
common::Span<const bst_feature_t> feature_set, // Selected features
DeviceNodeStats node,
xgboost::EllpackMatrix matrix,
xgboost::EllpackDeviceAccessor matrix,
GPUTrainingParam gpu_param,
common::Span<DeviceSplitCandidate> split_candidates, // resulting split
ValueConstraint value_constraint,
@@ -601,7 +601,7 @@ struct GPUHistMakerDevice {
uint32_t constexpr kBlockThreads = 256;
dh::LaunchKernel {uint32_t(d_feature_set.size()), kBlockThreads, 0, streams[i]} (
EvaluateSplitKernel<kBlockThreads, GradientSumT>,
hist.GetNodeHistogram(nidx), d_feature_set, node, page->matrix,
hist.GetNodeHistogram(nidx), d_feature_set, node, page->GetDeviceAccessor(device_id),
gpu_param, d_split_candidates, node_value_constraints[nidx],
monotone_constraints);
@@ -625,9 +625,7 @@ struct GPUHistMakerDevice {
hist.AllocateHistogram(nidx);
auto d_node_hist = hist.GetNodeHistogram(nidx);
auto d_ridx = row_partitioner->GetRows(nidx);
auto d_gpair = gpair.data();
BuildGradientHistogram(page->matrix, gpair, d_ridx, d_node_hist,
BuildGradientHistogram(page->GetDeviceAccessor(device_id), gpair, d_ridx, d_node_hist,
histogram_rounding, use_shared_memory_histograms);
}
@@ -637,7 +635,7 @@ struct GPUHistMakerDevice {
auto d_node_hist_histogram = hist.GetNodeHistogram(nidx_histogram);
auto d_node_hist_subtraction = hist.GetNodeHistogram(nidx_subtraction);
dh::LaunchN(device_id, page->matrix.info.n_bins, [=] __device__(size_t idx) {
dh::LaunchN(device_id, page->cuts_.TotalBins(), [=] __device__(size_t idx) {
d_node_hist_subtraction[idx] =
d_node_hist_parent[idx] - d_node_hist_histogram[idx];
});
@@ -652,7 +650,7 @@ struct GPUHistMakerDevice {
}
void UpdatePosition(int nidx, RegTree::Node split_node) {
auto d_matrix = page->matrix;
auto d_matrix = page->GetDeviceAccessor(device_id);
row_partitioner->UpdatePosition(
nidx, split_node.LeftChild(), split_node.RightChild(),
@@ -689,7 +687,7 @@ struct GPUHistMakerDevice {
row_partitioner.reset(); // Release the device memory first before reallocating
row_partitioner.reset(new RowPartitioner(device_id, p_fmat->Info().num_row_));
}
if (page->matrix.n_rows == p_fmat->Info().num_row_) {
if (page->n_rows == p_fmat->Info().num_row_) {
FinalisePositionInPage(page, d_nodes);
} else {
for (auto& batch : p_fmat->GetBatches<EllpackPage>(batch_param)) {
@@ -699,7 +697,7 @@ struct GPUHistMakerDevice {
}
void FinalisePositionInPage(EllpackPageImpl* page, const common::Span<RegTree::Node> d_nodes) {
auto d_matrix = page->matrix;
auto d_matrix = page->GetDeviceAccessor(device_id);
row_partitioner->FinalisePosition(
[=] __device__(size_t row_id, int position) {
if (!d_matrix.IsInRange(row_id)) {
@@ -765,7 +763,7 @@ struct GPUHistMakerDevice {
reducer->AllReduceSum(
reinterpret_cast<typename GradientSumT::ValueT*>(d_node_hist),
reinterpret_cast<typename GradientSumT::ValueT*>(d_node_hist),
page->matrix.info.n_bins * (sizeof(GradientSumT) / sizeof(typename GradientSumT::ValueT)));
page->cuts_.TotalBins() * (sizeof(GradientSumT) / sizeof(typename GradientSumT::ValueT)));
reducer->Synchronize();
monitor.StopCuda("AllReduce");
@@ -954,14 +952,14 @@ inline void GPUHistMakerDevice<GradientSumT>::InitHistogram() {
// check if we can use shared memory for building histograms
// (assuming atleast we need 2 CTAs per SM to maintain decent latency
// hiding)
auto histogram_size = sizeof(GradientSumT) * page->matrix.info.n_bins;
auto histogram_size = sizeof(GradientSumT) * page->cuts_.TotalBins();
auto max_smem = dh::MaxSharedMemory(device_id);
if (histogram_size <= max_smem) {
use_shared_memory_histograms = true;
}
// Init histogram
hist.Init(device_id, page->matrix.info.n_bins);
hist.Init(device_id, page->cuts_.TotalBins());
}
template <typename GradientSumT>