Enable threaded data initialization for CPU. by trivialfis · Pull Request #11974 · dmlc/xgboost

trivialfis · 2026-01-29T11:07:18Z

Extracted from #11390 , modified to use the context instead. In addition, a new ParallelForBlock is created.

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Pull request overview

This PR refactors gradient index construction on CPU to consistently use Context-based threading and introduces a new block-based parallel helper for initializing reference-counted buffers.

Changes:

Update GHistIndexMatrix constructors and internal methods to take Context and use new MakeFixedVecWithMalloc(ctx, ...) for multi-threaded, malloc-backed buffers on CPU (and hook up corresponding call sites and tests).
Refactor gradient-index page sources (SparsePageDMatrix::GetGradientIndex and GradientIndexPageSource) to accept a Context and construct GHistIndexMatrix with it, including for external-memory workflows.
Add ParallelForBlock and a Context-aware MakeFixedVecWithMalloc in ref_resource_view, using block-parallel initialization, and wire GPU-side code to the new ResizeIndex(ctx, ...) API.

Reviewed changes

Copilot reviewed 11 out of 11 changed files in this pull request and generated 1 comment.

Show a summary per file

File	Description
`tests/cpp/tree/test_quantile_hist.cc`	Adjusts quantile histogram partitioner tests to use the new `GHistIndexMatrix` constructor taking `Context const*` instead of a raw thread count.
`tests/cpp/tree/hist/test_histogram.cc`	Updates external-memory histogram test to construct `GHistIndexMatrix` with `Context const*`, matching the new API.
`tests/cpp/data/test_sparse_page_dmatrix.cc`	Updates gradient index external-memory tests to use the `Context`-aware `GHistIndexMatrix` constructor.
`src/data/sparse_page_dmatrix.cc`	Refactors `GetGradientIndex` to construct `GradientIndexPageSource` with a `Context const*`, so downstream gradient-index construction can use `ctx->Threads()`.
`src/data/gradient_index_page_source.h`	Changes `GradientIndexPageSource` to accept `Context const*` and pass `ctx->Threads()` into `PageSourceIncMixIn`, preparing for `Context`-driven CPU threading.
`src/data/gradient_index_page_source.cc`	In `GradientIndexPageSource::Fetch`, constructs a local `Context` with `nthreads_` and uses it to build `GHistIndexMatrix` with the new `(Context const*, SparsePage const&, ...)` constructor.
`src/data/gradient_index.h`	Refactors `GHistIndexMatrix` API: `PushBatch` and `PushBatchImpl` now take `Context const`, the external-memory constructor is updated to take `Context const`, and `ResizeIndex` now also receives `Context const*`.
`src/data/gradient_index.cu`	Updates the GPU-side constructor to call `ResizeIndex(ctx, ...)`, aligning with the new CPU/GPU-agnostic signature.
`src/data/gradient_index.cc`	Uses `MakeFixedVecWithMalloc(ctx, ...)` for `hit_count` and `row_ptr`, switches `PushBatch` and `PushAdapterBatch` to the `Context`-aware versions, and updates `ResizeIndex` to allocate using the new `MakeFixedVecWithMalloc(ctx, ...)`.
`src/data/gradient_index_page_source.h`	(Same as above file) Ensures CPU gradient-index page source derives its thread count from `Context` instead of a bare `nthreads` parameter.
`src/common/threading_utils.h`	Adds `ParallelForBlock` intended to use `n_threads` as block count, but the current implementation can construct invalid `Range1d` and out-of-bounds ranges when `size <= n_threads` and ignores the clamped `end` variable.
`src/common/ref_resource_view.h`	Adds a `Context`-aware `MakeFixedVecWithMalloc` that uses `ParallelForBlock` to parallelize initialization of `RefResourceView` storage, and wires in the necessary includes for `Context` and threading utilities.

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src/common/threading_utils.h

trivialfis · 2026-01-29T11:49:11Z

@razdoburdin Could you please help review the PR when you are available? I have listed you as the author. Please let me know if you prefer otherwise.

razdoburdin · 2026-01-29T11:53:33Z

@razdoburdin Could you please help review the PR when you are available? I have listed you as the author. Please let me know if you prefer otherwise.

yes, I will take a look

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razdoburdin

looks good for me

razdoburdin · 2026-02-02T09:04:34Z

src/data/gradient_index.cc

      max_numeric_bins_per_feat{max_bins_per_feat},
      base_rowid{batch.base_rowid},
      isDense_{is_dense} {
-  CHECK_GE(n_threads, 1);


Is the n_threads >= 1 checked elseware ?

As long as the number of threads comes from the Context class, it should go through this check:

xgboost/src/common/threading_utils.cc

Line 120 in f5f1e65

n_threads = std::max(n_threads, 1);

razdoburdin · 2026-02-02T09:15:28Z

src/common/threading_utils.h

+  std::size_t blk_size = size / n_threads + (size % n_threads > 0);
+  ParallelFor(n_threads, n_threads, [&](auto tid) {
+    auto blk_beg = tid * blk_size;
+    if (blk_beg >= size) {


This check looks redundant. If (size == 0), blk_size == blk_beg == end == 0, so the (end == blk_beg) check shall work in this case.

It's not for size==0. Say size==1, but n_threads==8, then the block_size=1, the second block (thread) would have block_begin = 1 * 1 = 1, end would be end = 2 * 1 = 2, and block_begin != end.

Ah, I see.
May be just replace if (end == blk_beg) by if (end <= blk_beg)?

Thank you for the suggestion, done.

trivialfis · 2026-02-03T14:15:33Z

Haven't done this very often. I made sure the only commit here has @razdoburdin as the author, I hope squashing and merging the commit with github will retain the information.

trivialfis · 2026-02-03T17:15:04Z

No.. the author is switched.

trivialfis mentioned this pull request Jan 29, 2026

Optimization of data initialization for large sparce datasets #11390

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trivialfis requested a review from Copilot January 29, 2026 11:27

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Enable multi-thread for large data initialization.

9b02b0f

trivialfis force-pushed the cpu-opt-multi-thread-init branch from 4f6f74b to 9b02b0f Compare February 3, 2026 13:57

trivialfis merged commit ad79b37 into dmlc:master Feb 3, 2026
76 checks passed

trivialfis deleted the cpu-opt-multi-thread-init branch February 3, 2026 17:14

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trivialfis commented Jan 29, 2026

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trivialfis commented Jan 29, 2026 •

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