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Move device histogram storage into histogram.cuh. (#10608)

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This commit is contained in:
Jiaming Yuan
2024-07-21 14:10:13 +08:00
committed by GitHub
parent cb62f9e73b
commit 6d9fcb771e
6 changed files with 171 additions and 167 deletions
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40
tests/cpp/tree/gpu_hist/test_histogram.cu
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@@ -14,6 +14,46 @@
#include "../../helpers.h"
namespace xgboost::tree {
TEST(Histogram, DeviceHistogramStorage) {
// Ensures that node allocates correctly after reaching `kStopGrowingSize`.
auto ctx = MakeCUDACtx(0);
constexpr size_t kNBins = 128;
constexpr int kNNodes = 4;
constexpr size_t kStopGrowing = kNNodes * kNBins * 2u;
DeviceHistogramStorage<kStopGrowing> histogram;
histogram.Init(FstCU(), kNBins);
for (int i = 0; i < kNNodes; ++i) {
histogram.AllocateHistograms(&ctx, {i});
}
histogram.Reset(&ctx);
ASSERT_EQ(histogram.Data().size(), kStopGrowing);
// Use allocated memory but do not erase nidx_map.
for (int i = 0; i < kNNodes; ++i) {
histogram.AllocateHistograms(&ctx, {i});
}
for (int i = 0; i < kNNodes; ++i) {
ASSERT_TRUE(histogram.HistogramExists(i));
}
// Add two new nodes
histogram.AllocateHistograms(&ctx, {kNNodes});
histogram.AllocateHistograms(&ctx, {kNNodes + 1});
// Old cached nodes should still exist
for (int i = 0; i < kNNodes; ++i) {
ASSERT_TRUE(histogram.HistogramExists(i));
}
// Should be deleted
ASSERT_FALSE(histogram.HistogramExists(kNNodes));
// Most recent node should exist
ASSERT_TRUE(histogram.HistogramExists(kNNodes + 1));
// Add same node again - should fail
EXPECT_ANY_THROW(histogram.AllocateHistograms(&ctx, {kNNodes + 1}););
}
void TestDeterministicHistogram(bool is_dense, int shm_size, bool force_global) {
Context ctx = MakeCUDACtx(0);
size_t constexpr kBins = 256, kCols = 120, kRows = 16384, kRounds = 16;

61
tests/cpp/tree/test_gpu_hist.cu
View File

@@ -6,7 +6,6 @@
#include <thrust/host_vector.h>
#include <xgboost/base.h>
#include <random>
#include <string>
#include <vector>
@@ -23,46 +22,6 @@
#include "xgboost/json.h"
namespace xgboost::tree {
TEST(GpuHist, DeviceHistogramStorage) {
// Ensures that node allocates correctly after reaching `kStopGrowingSize`.
dh::safe_cuda(cudaSetDevice(0));
constexpr size_t kNBins = 128;
constexpr int kNNodes = 4;
constexpr size_t kStopGrowing = kNNodes * kNBins * 2u;
DeviceHistogramStorage<kStopGrowing> histogram;
histogram.Init(FstCU(), kNBins);
for (int i = 0; i < kNNodes; ++i) {
histogram.AllocateHistograms({i});
}
histogram.Reset();
ASSERT_EQ(histogram.Data().size(), kStopGrowing);
// Use allocated memory but do not erase nidx_map.
for (int i = 0; i < kNNodes; ++i) {
histogram.AllocateHistograms({i});
}
for (int i = 0; i < kNNodes; ++i) {
ASSERT_TRUE(histogram.HistogramExists(i));
}
// Add two new nodes
histogram.AllocateHistograms({kNNodes});
histogram.AllocateHistograms({kNNodes + 1});
// Old cached nodes should still exist
for (int i = 0; i < kNNodes; ++i) {
ASSERT_TRUE(histogram.HistogramExists(i));
}
// Should be deleted
ASSERT_FALSE(histogram.HistogramExists(kNNodes));
// Most recent node should exist
ASSERT_TRUE(histogram.HistogramExists(kNNodes + 1));
// Add same node again - should fail
EXPECT_ANY_THROW(histogram.AllocateHistograms({kNNodes + 1}););
}
std::vector<GradientPairPrecise> GetHostHistGpair() {
// 24 bins, 3 bins for each feature (column).
std::vector<GradientPairPrecise> hist_gpair = {
@@ -108,7 +67,7 @@ void TestBuildHist(bool use_shared_memory_histograms) {
maker.row_partitioner = std::make_unique<RowPartitioner>(&ctx, kNRows, 0);
maker.hist.Init(ctx.Device(), page->Cuts().TotalBins());
maker.hist.AllocateHistograms({0});
maker.hist.AllocateHistograms(&ctx, {0});
maker.gpair = gpair.DeviceSpan();
maker.quantiser = std::make_unique<GradientQuantiser>(&ctx, maker.gpair, MetaInfo());
@@ -425,8 +384,8 @@ TEST(GpuHist, MaxDepth) {
namespace {
RegTree GetHistTree(Context const* ctx, DMatrix* dmat) {
ObjInfo task{ObjInfo::kRegression};
GPUHistMaker hist_maker{ctx, &task};
hist_maker.Configure(Args{});
std::unique_ptr<TreeUpdater> hist_maker {TreeUpdater::Create("grow_gpu_hist", ctx, &task)};
hist_maker->Configure(Args{});
TrainParam param;
param.UpdateAllowUnknown(Args{});
@@ -436,8 +395,8 @@ RegTree GetHistTree(Context const* ctx, DMatrix* dmat) {
std::vector<HostDeviceVector<bst_node_t>> position(1);
RegTree tree;
hist_maker.Update(&param, &gpair, dmat, common::Span<HostDeviceVector<bst_node_t>>{position},
{&tree});
hist_maker->Update(&param, &gpair, dmat, common::Span<HostDeviceVector<bst_node_t>>{position},
{&tree});
return tree;
}
@@ -476,8 +435,8 @@ TEST_F(MGPUHistTest, HistColumnSplit) {
namespace {
RegTree GetApproxTree(Context const* ctx, DMatrix* dmat) {
ObjInfo task{ObjInfo::kRegression};
GPUGlobalApproxMaker approx_maker{ctx, &task};
approx_maker.Configure(Args{});
std::unique_ptr<TreeUpdater> approx_maker{TreeUpdater::Create("grow_gpu_approx", ctx, &task)};
approx_maker->Configure(Args{});
TrainParam param;
param.UpdateAllowUnknown(Args{});
@@ -487,13 +446,13 @@ RegTree GetApproxTree(Context const* ctx, DMatrix* dmat) {
std::vector<HostDeviceVector<bst_node_t>> position(1);
RegTree tree;
approx_maker.Update(&param, &gpair, dmat, common::Span<HostDeviceVector<bst_node_t>>{position},
{&tree});
approx_maker->Update(&param, &gpair, dmat, common::Span<HostDeviceVector<bst_node_t>>{position},
{&tree});
return tree;
}
void VerifyApproxColumnSplit(bst_idx_t rows, bst_feature_t cols, RegTree const& expected_tree) {
Context ctx(MakeCUDACtx(GPUIDX));
auto ctx = MakeCUDACtx(DistGpuIdx());
auto Xy = RandomDataGenerator{rows, cols, 0}.GenerateDMatrix(true);
auto const world_size = collective::GetWorldSize();