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Optimisations for gpu_hist. (#4248)

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* Optimisations for gpu_hist.

* Use streams to overlap operations.

* ColumnSampler now uses HostDeviceVector to prevent repeatedly copying feature vectors to the device.
This commit is contained in:
Rory Mitchell
2019-03-20 13:30:06 +13:00
committed by GitHub
parent 7814183199
commit 00465d243d
8 changed files with 278 additions and 119 deletions
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24
tests/cpp/common/test_random.cc
View File

@@ -11,38 +11,40 @@ TEST(ColumnSampler, Test) {
// No node sampling
cs.Init(n, 1.0f, 0.5f, 0.5f);
auto set0 = *cs.GetFeatureSet(0);
ASSERT_EQ(set0.size(), 32);
ASSERT_EQ(set0.Size(), 32);
auto set1 = *cs.GetFeatureSet(0);
ASSERT_EQ(set0, set1);
ASSERT_EQ(set0.HostVector(), set1.HostVector());
auto set2 = *cs.GetFeatureSet(1);
ASSERT_NE(set1, set2);
ASSERT_EQ(set2.size(), 32);
ASSERT_NE(set1.HostVector(), set2.HostVector());
ASSERT_EQ(set2.Size(), 32);
// Node sampling
cs.Init(n, 0.5f, 1.0f, 0.5f);
auto set3 = *cs.GetFeatureSet(0);
ASSERT_EQ(set3.size(), 32);
ASSERT_EQ(set3.Size(), 32);
auto set4 = *cs.GetFeatureSet(0);
ASSERT_NE(set3, set4);
ASSERT_EQ(set4.size(), 32);
ASSERT_NE(set3.HostVector(), set4.HostVector());
ASSERT_EQ(set4.Size(), 32);
// No level or node sampling, should be the same at different depth
cs.Init(n, 1.0f, 1.0f, 0.5f);
ASSERT_EQ(*cs.GetFeatureSet(0), *cs.GetFeatureSet(1));
ASSERT_EQ(cs.GetFeatureSet(0)->HostVector(), cs.GetFeatureSet(1)->HostVector());
cs.Init(n, 1.0f, 1.0f, 1.0f);
auto set5 = *cs.GetFeatureSet(0);
ASSERT_EQ(set5.size(), n);
ASSERT_EQ(set5.Size(), n);
cs.Init(n, 1.0f, 1.0f, 1.0f);
auto set6 = *cs.GetFeatureSet(0);
ASSERT_EQ(set5, set6);
ASSERT_EQ(set5.HostVector(), set6.HostVector());
// Should always be a minimum of one feature
cs.Init(n, 1e-16f, 1e-16f, 1e-16f);
ASSERT_EQ(cs.GetFeatureSet(0)->size(), 1);
ASSERT_EQ(cs.GetFeatureSet(0)->Size(), 1);
}
} // namespace common

20
tests/cpp/tree/test_gpu_hist.cu
View File

@@ -304,11 +304,13 @@ TEST(GpuHist, EvaluateSplits) {
hist_maker.node_value_constraints_[0].lower_bound = -1.0;
hist_maker.node_value_constraints_[0].upper_bound = 1.0;
DeviceSplitCandidate res =
hist_maker.EvaluateSplit(0, &tree);
std::vector<DeviceSplitCandidate> res =
hist_maker.EvaluateSplits({ 0,0 }, &tree);
ASSERT_EQ(res.findex, 7);
ASSERT_NEAR(res.fvalue, 0.26, xgboost::kRtEps);
ASSERT_EQ(res[0].findex, 7);
ASSERT_EQ(res[1].findex, 7);
ASSERT_NEAR(res[0].fvalue, 0.26, xgboost::kRtEps);
ASSERT_NEAR(res[1].fvalue, 0.26, xgboost::kRtEps);
}
TEST(GpuHist, ApplySplit) {
@@ -400,7 +402,9 @@ TEST(GpuHist, ApplySplit) {
void TestSortPosition(const std::vector<int>& position_in, int left_idx,
int right_idx) {
int left_count = std::count(position_in.begin(), position_in.end(), left_idx);
std::vector<int64_t> left_count = {
std::count(position_in.begin(), position_in.end(), left_idx)};
thrust::device_vector<int64_t> d_left_count = left_count;
thrust::device_vector<int> position = position_in;
thrust::device_vector<int> position_out(position.size());
@@ -413,7 +417,7 @@ void TestSortPosition(const std::vector<int>& position_in, int left_idx,
common::Span<int>(position_out.data().get(), position_out.size()),
common::Span<bst_uint>(ridx.data().get(), ridx.size()),
common::Span<bst_uint>(ridx_out.data().get(), ridx_out.size()), left_idx,
right_idx, left_count);
right_idx, d_left_count.data().get());
thrust::host_vector<int> position_result = position_out;
thrust::host_vector<int> ridx_result = ridx_out;
@@ -421,9 +425,9 @@ void TestSortPosition(const std::vector<int>& position_in, int left_idx,
EXPECT_TRUE(std::is_sorted(position_result.begin(), position_result.end()));
// Check row indices are sorted inside left and right segment
EXPECT_TRUE(
std::is_sorted(ridx_result.begin(), ridx_result.begin() + left_count));
std::is_sorted(ridx_result.begin(), ridx_result.begin() + left_count[0]));
EXPECT_TRUE(
std::is_sorted(ridx_result.begin() + left_count, ridx_result.end()));
std::is_sorted(ridx_result.begin() + left_count[0], ridx_result.end()));
// Check key value pairs are the same
for (auto i = 0ull; i < ridx_result.size(); i++) {