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
84 lines
2.8 KiB
ReStructuredText
84 lines
2.8 KiB
ReStructuredText
.. _libcudacxx-ptx:
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PTX API
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========
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The ``cuda::ptx`` namespace contains functions that map one-to-one to
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`PTX instructions <https://docs.nvidia.com/cuda/parallel-thread-execution/index.html>`__.
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These can be used for maximal control of the generated code, or to
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experiment with new hardware features before a high-level C++ API is
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available.
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.. toctree::
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:maxdepth: 1
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ptx/examples
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ptx/instructions
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ptx/pragmas
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Versions and compatibility
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---------------------------
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The ``cuda/ptx`` header is intended to present a stable API within one major
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version of the CTK on a best effort basis. This means that:
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- All functions are marked static inline.
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- The type of a function parameter can be changed to be more generic if
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that means that code that called the original version can still be
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compiled.
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- Good exposure of the PTX should be high priority. If, at a new major
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version, we face a difficult choice between breaking
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backward-compatibility and an improvement of the PTX exposure, we
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will tend to the latter option more easily than in other parts of
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libcu++.
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The API does not guarantee stability of template parameters. The order and
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number of template parameters may change. Use arguments to driver overload
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resolution as in the code below to ensure forward-compatibility:
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.. code:: cuda
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// Use arguments to drive overload resolution:
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cuda::ptx::mbarrier_arrive_expect_tx(cuda::ptx::sem_release, cuda::ptx::scope_cta, cuda::ptx::space_shared, &bar, 1);
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// Specifying templates directly is not forward-compatible, as order and number
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// of template parameters may change in a minor release:
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cuda::ptx::mbarrier_arrive_expect_tx<cuda::ptx::sem_release_t>(
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cuda::ptx::sem_release, cuda::ptx::scope_cta, cuda::ptx::space_shared, &bar, 1
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);
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**PTX ISA version and compute capability.** Each binding notes under
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which PTX ISA version and SM version it may be used. Example:
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.. code:: cuda
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// mbarrier.arrive.shared::cta.b64 state, [addr]; // 1. PTX ISA 70, SM_80
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__device__ inline uint64_t mbarrier_arrive(
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cuda::ptx::sem_release_t sem,
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cuda::ptx::scope_cta_t scope,
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cuda::ptx::space_shared_t space,
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uint64_t* addr);
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To check if the current compiler is recent enough, use:
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.. code:: cuda
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#if __cccl_ptx_isa >= 700
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cuda::ptx::mbarrier_arrive(cuda::ptx::sem_release, cuda::ptx::scope_cta, cuda::ptx::space_shared, &bar, 1);
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#endif
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Ensure that you only call the function when compiling for a recent
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enough compute capability (SM version), like this:
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.. code:: cuda
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NV_IF_TARGET(NV_PROVIDES_SM_80,(
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cuda::ptx::mbarrier_arrive(cuda::ptx::sem_release, cuda::ptx::scope_cta, cuda::ptx::space_shared, &bar, 1);
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));
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For more information on which compilers correspond to which PTX ISA, see
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the `PTX ISA release notes <https://docs.nvidia.com/cuda/parallel-thread-execution/index.html#release-notes>`__.
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