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
90 lines
2.3 KiB
TOML
90 lines
2.3 KiB
TOML
# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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#
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# SPDX-License-Identifier: Apache-2.0
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[workspace]
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channels = ["conda-forge"]
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platforms = ["linux-64"]
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channel-priority = "disabled"
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# CUDA 13.1 system requirement
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[feature.cu13.system-requirements]
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cuda = "13"
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[feature.cu13.dependencies]
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cuda-version = "13.1.*"
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# Python benchmark dependencies
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[feature.bench.dependencies]
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python = "3.13.*"
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numpy = "*"
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cupy = "*"
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pytest-benchmark = "*"
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pyyaml = "*"
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pre-commit = "*"
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[feature.bench.pypi-dependencies]
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cuda-bench = ">=0.2.0"
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# C++ benchmark build dependencies
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[feature.cpp-bench.dependencies]
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cmake = "*"
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ninja = "*"
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cxx-compiler = "*"
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fmt = "*"
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cuda-cudart-dev = "*"
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[feature.cpp-bench.target.linux-64.dependencies]
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cuda-crt-dev_linux-64 = "*"
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cuda-driver-dev_linux-64 = "*"
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[feature.cpp-bench.target.linux-64.activation.env]
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CUDA_HOME = "$CONDA_PREFIX/targets/x86_64-linux"
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# Important: cuda-cccl installation variants
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# Released version from PyPI
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[feature.cccl-wheel.pypi-dependencies]
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cuda-cccl = { version = ">=0.1.0", extras = ["cu13"] }
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# Local source build (editable install from repo)
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# Needs nvcc, compilers, and CUDA dev libraries for scikit-build-core to build cuda-cccl
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[feature.cccl-source.dependencies]
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cuda-nvcc = "*"
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cuda-nvrtc-dev = "*"
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libnvjitlink-dev = "*"
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cuda-cudart-dev = "*"
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cuda-driver-dev = "*"
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c-compiler = "*"
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cxx-compiler = "*"
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[feature.cccl-source.pypi-dependencies]
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cuda-cccl = { path = "../..", editable = true, extras = ["cu13"] }
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# Environments
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[environments]
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wheel = { features = ["cu13", "bench", "cpp-bench", "cccl-wheel"] }
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source = { features = ["cu13", "bench", "cpp-bench", "cccl-source"] }
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# Tasks
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[tasks.bench]
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cmd = ["python", "run_benchmarks.py", "--py"]
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description = "Run Python cuda.compute benchmarks"
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[tasks.bench-quick]
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cmd = ["python", "run_benchmarks.py", "--py", "--quick"]
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description = "Run Python benchmarks with reduced parameter set"
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[tasks.bench-cpp]
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cmd = ["python", "run_benchmarks.py", "--cpp"]
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description = "Run C++ CUB benchmarks"
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[tasks.bench-all]
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cmd = ["python", "run_benchmarks.py"]
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description = "Run both Python and C++ benchmarks"
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[tasks.pre-commit]
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cmd = ["pre-commit", "run", "--all-files"]
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cwd = "../../../.."
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description = "Run pre-commit checks on the entire repo"
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