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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
47 lines
1.8 KiB
ReStructuredText
47 lines
1.8 KiB
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How to commit fixes to release branches (backport process)
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==========================================================
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This guide explains when and how to commit fixes to release branches.
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After a release branch is created and before a release tag is finalized,
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maintainers may need to apply fixes to that release branch.
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To keep ``main`` as the source of truth, each fix starts as a PR against
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``main``, then automation opens an equivalent *backport* PR against the
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relevant release branch.
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Backport Criteria
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-----------------
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Before starting a backport, use the questions below to decide if a change is worth backporting:
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- Does this fix a correctness bug (wrong result, UB, memory safety, data race, deadlock)?
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- Does this fix a crash?
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- Does this fix a regression?
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- Are users actively asking for this fix to be backported?
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- How likely are users to be affected by this? How many?
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- Is there a reasonable workaround?
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- How risky is this change?
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Examples *not* worth backporting:
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- Fixes to tests that do not impact the functionality of the library.
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- Fixes to infrastructure that does not impact the functionality of the library.
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Steps
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-----
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#. Create a PR with the fix against ``main`` via a PR following our :doc:`contributing guidelines </cccl/contributing>`.
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#. Add the label ``backport branch/X.Y.x`` to the PR.
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- If the PR is already merged, you can still trigger a backport by commenting
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``/backport branch/X.Y.x`` on the merged PR.
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#. After merge to ``main``, confirm automation opens a backport PR targeting
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``branch/X.Y.x``.
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#. Review the generated backport PR for correctness and resolve any conflicts.
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#. Ensure all CI checks have passed and merge the backport PR into the target
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release branch.
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- Only members of the GitHub team `cccl-release-owners <https://github.com/orgs/NVIDIA/teams/cccl-release-owners>` can merge PRs to release branches.
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