2a7ca101d7
Sparse-checkout from NVIDIA/cccl main branch to complete cccl_upstream: Added: - python/cuda_cccl/ (226 files) — Python bindings for device-level algorithms Critical for muh toolchain: cuda.compute.reduce_into, scan, radix_sort, etc. Includes 204 .py files with full test coverage for all 27 algorithms - ci/ (163 files) — Build/test infrastructure build_cub.sh, test_cub.sh, build_and_test_targets.sh, matrix.yaml Directly maps to our [INFRA-CI] and [INFRA-BUILD] items - .agent/skills/ (7 files) — NVIDIA's own agent skills for CCCL cccl-style/SKILL.md, cccl-test/SKILL.md, sass-diff/SKILL.md - docs/ (491 files) — Official CCCL documentation CI references, CMake guides, Python compute docs, libcudacxx PTX docs - test/ (12 files) — Top-level integration tests (cuda_smoke, stdpar) - Root configs: .clang-format, .clang-tidy, CONTRIBUTING.md, pyproject.toml - CLAUDE.md symlink → AGENTS.md (NVIDIA's standard) cccl_upstream now mirrors full NVIDIA/cccl structure: Before: 42M (cub + thrust + libcudacxx + cudax + c + examples + benchmarks) After: 53M (+python +ci +docs +.agent +test +configs) This completes the CCCL base needed for: - [muh-bench] items: ci/util/build_and_test_targets.sh for targeted builds - [CCCL-verify] items: python/cuda_cccl/tests/ as reference implementations - [CCCL-test] items: ci/test_cub.sh, ci/test_thrust.sh - Agent workflow: .agent/skills/ for consistent style and test patterns
25 lines
675 B
ReStructuredText
25 lines
675 B
ReStructuredText
.. _cub-developer-guide-thread-level:
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Thread-level
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*************
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In contrast to algorithms at the warp/block/device layer,
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single threaded functionality like ``cub::ThreadReduce``
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is typically implemented as a sequential function and rarely exposed to the user.
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.. code-block:: c++
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template <
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int LENGTH,
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typename T,
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typename ReductionOp,
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typename PrefixT,
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typename AccumT = detail::accumulator_t<ReductionOp, PrefixT, T>>
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__device__ __forceinline__ AccumT ThreadReduce(
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T (&input)[LENGTH],
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ReductionOp reduction_op,
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PrefixT prefix)
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{
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return ...;
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}
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