feat(cccl): integrate missing CCCL directories — python/, ci/, .agent/, docs/, test/
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
This commit is contained in:
27
cccl_upstream/python/cuda_cccl/cuda/cccl/__init__.py
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27
cccl_upstream/python/cuda_cccl/cuda/cccl/__init__.py
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"""
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CUDA Core Library (CCCL) Python Package
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"""
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import importlib.metadata
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try:
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__version__ = importlib.metadata.version("cuda-cccl")
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except Exception:
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__version__ = "0.0.0"
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from .headers.include_paths import get_include_paths
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# cuda.bindings is required, but instead of being listed as a required dependency,
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# it is installed via an extra (e.g., [cu12] or [cu13]).
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#
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# One of the first things we should do is check that it is available, and raise
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# a helpful error message if it is not.
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try:
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import cuda.bindings as _cuda_bindings # type: ignore
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except ImportError:
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raise ImportError(
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"cuda.bindings is not installed. Please install the appropriate extra cuda-cccl[cu12] or cuda-cccl[cu13]."
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) from None
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del _cuda_bindings
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__all__ = ["get_include_paths", "__version__"]
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# Copyright (c) 2025, NVIDIA CORPORATION & AFFILIATES. ALL RIGHTS RESERVED.
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#
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# SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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"""
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CUDA version detection utilities shared across the cccl package.
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"""
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from typing import Optional
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import cuda.bindings
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def detect_cuda_version() -> Optional[int]:
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cuda_version = cuda.bindings.__version__
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return int(cuda_version.split(".")[0])
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def get_recommended_extra(cuda_version: Optional[int]) -> str:
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"""Get the recommended pip extra for the detected CUDA version."""
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if cuda_version == 13:
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return "cu13"
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else:
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return "cu12"
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# Copyright (c) 2025, NVIDIA CORPORATION & AFFILIATES. ALL RIGHTS RESERVED.
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#
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# SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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from .include_paths import get_include_paths
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__all__ = ["__version__", "get_include_paths"]
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# Intentionally empty
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# Copyright (c) 2025, NVIDIA CORPORATION & AFFILIATES. ALL RIGHTS RESERVED.
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#
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# SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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import sys
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from dataclasses import dataclass
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from functools import lru_cache
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from importlib.resources import as_file, files
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from pathlib import Path
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from typing import Optional
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# type: ignore[import-not-found]
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from cuda.pathfinder import find_nvidia_header_directory
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@dataclass
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class IncludePaths:
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cuda: Optional[Path]
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libcudacxx: Optional[Path]
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cub: Optional[Path]
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thrust: Optional[Path]
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def as_tuple(self):
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# Note: higher-level ... lower-level order:
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return (self.thrust, self.cub, self.libcudacxx, self.cuda)
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@lru_cache()
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def get_include_paths(probe_file: str = "cub/version.cuh") -> IncludePaths:
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cuda_incl = find_nvidia_header_directory("cudart")
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if cuda_incl is None:
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raise RuntimeError("Unable to locate CUDA include directory.")
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with as_file(files("cuda.cccl.headers.include")) as f:
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cccl_incl = Path(f)
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probe_file_path = Path(probe_file)
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if not (cccl_incl / probe_file_path).exists():
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for sp in sys.path:
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cccl_incl = Path(sp).resolve() / "cuda" / "cccl" / "headers" / "include"
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if (cccl_incl / probe_file_path).exists():
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break
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else:
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raise RuntimeError("Unable to locate CCCL include directory.")
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return IncludePaths(
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cuda=cuda_incl,
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libcudacxx=cccl_incl,
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cub=cccl_incl,
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thrust=cccl_incl,
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)
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# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. ALL RIGHTS RESERVED.
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#
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# SPDX-License -Identifier: Apache-2.0 WITH LLVM-exception
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from . import experimental
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__all__ = [
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"experimental",
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]
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# Copyright (c) 2025, NVIDIA CORPORATION.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# alias for backwards compatibility
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from warnings import warn
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from cuda.compute import * # noqa: F403
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warn(
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"The module cuda.cccl.parallel.experimental is deprecated. Use cuda.compute instead.",
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FutureWarning,
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)
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0
cccl_upstream/python/cuda_cccl/cuda/cccl/py.typed
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0
cccl_upstream/python/cuda_cccl/cuda/cccl/py.typed
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