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[EM] Merge GPU partitioning with histogram building. (#10766)

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- Stop concatenating pages if there's no subsampling.
- Use a single iteration for histogram build and partitioning.
This commit is contained in:
Jiaming Yuan
2024-08-31 03:25:37 +08:00
committed by GitHub
parent 98ac153265
commit e1a2c1bbb3
7 changed files with 118 additions and 159 deletions
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26
tests/cpp/tree/gpu_hist/test_gradient_based_sampler.cu
View File

@@ -67,7 +67,6 @@ TEST(GradientBasedSampler, NoSampling) {
VerifySampling(kPageSize, kSubsample, kSamplingMethod);
}
// In external mode, when not sampling, we concatenate the pages together.
TEST(GradientBasedSampler, NoSamplingExternalMemory) {
constexpr size_t kRows = 2048;
constexpr size_t kCols = 1;
@@ -81,34 +80,11 @@ TEST(GradientBasedSampler, NoSamplingExternalMemory) {
gpair.SetDevice(ctx.Device());
auto param = BatchParam{256, tree::TrainParam::DftSparseThreshold()};
auto page = (*dmat->GetBatches<EllpackPage>(&ctx, param).begin()).Impl();
EXPECT_NE(page->n_rows, kRows);
GradientBasedSampler sampler(&ctx, kRows, param, kSubsample, TrainParam::kUniform, true);
auto sample = sampler.Sample(&ctx, gpair.DeviceSpan(), dmat.get());
auto p_fmat = sample.p_fmat;
EXPECT_EQ(sample.p_fmat->Info().num_row_, kRows);
EXPECT_EQ(sample.gpair.size(), gpair.Size());
EXPECT_EQ(sample.gpair.data(), gpair.DevicePointer());
EXPECT_EQ(p_fmat->Info().num_row_, kRows);
ASSERT_EQ(p_fmat->NumBatches(), 1);
for (auto const& sampled_page : p_fmat->GetBatches<EllpackPage>(&ctx, param)) {
std::vector<common::CompressedByteT> h_gidx_buffer;
auto h_accessor = sampled_page.Impl()->GetHostAccessor(&ctx, &h_gidx_buffer);
std::size_t offset = 0;
for (auto& batch : dmat->GetBatches<EllpackPage>(&ctx, param)) {
auto page = batch.Impl();
std::vector<common::CompressedByteT> h_page_gidx_buffer;
auto page_accessor = page->GetHostAccessor(&ctx, &h_page_gidx_buffer);
size_t num_elements = page->n_rows * page->row_stride;
for (size_t i = 0; i < num_elements; i++) {
EXPECT_EQ(h_accessor.gidx_iter[i + offset], page_accessor.gidx_iter[i]);
}
offset += num_elements;
}
}
ASSERT_EQ(p_fmat, dmat.get());
}
TEST(GradientBasedSampler, UniformSampling) {

16
tests/python-gpu/test_gpu_data_iterator.py
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@@ -4,7 +4,7 @@ import pytest
from hypothesis import given, settings, strategies
from xgboost.testing import no_cupy
from xgboost.testing.updater import check_quantile_loss_extmem
from xgboost.testing.updater import check_extmem_qdm, check_quantile_loss_extmem
sys.path.append("tests/python")
from test_data_iterator import run_data_iterator
@@ -59,6 +59,14 @@ def test_cpu_data_iterator() -> None:
)
def test_quantile_objective() -> None:
with pytest.raises(ValueError, match="external memory"):
check_quantile_loss_extmem(2, 2, 2, "hist", "cuda")
@given(
strategies.integers(1, 2048),
strategies.integers(1, 8),
strategies.integers(1, 4),
strategies.booleans(),
)
@settings(deadline=None, max_examples=10, print_blob=True)
def test_extmem_qdm(
n_samples_per_batch: int, n_features: int, n_batches: int, on_host: bool
) -> None:
check_extmem_qdm(n_samples_per_batch, n_features, n_batches, "cuda", on_host)