Specialize __is_extended_floating_point for FP8 types #3470

bernhardmgruber · 2025-01-22T08:45:46Z

No description provided.

bernhardmgruber · 2025-01-22T08:46:27Z

libcudacxx/include/cuda/std/__type_traits/is_extended_floating_point.h

+struct __is_extended_floating_point<__nv_fp8_e5m2> : true_type
+{};
+
+#  ifndef _CCCL_NO_INLINE_VARIABLES


I left those checks in case I need to backport this changeset.

github-actions · 2025-01-22T15:35:09Z

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👃 Inspect Changes

Modifications in project?

	Project
	CCCL Infrastructure
+/-	libcu++
	CUB
	Thrust
	CUDA Experimental
	python
	CCCL C Parallel Library
	Catch2Helper

Modifications in project or dependencies?

	Project
	CCCL Infrastructure
+/-	libcu++
+/-	CUB
+/-	Thrust
+/-	CUDA Experimental
+/-	python
+/-	CCCL C Parallel Library
+/-	Catch2Helper

🏃‍ Runner counts (total jobs: 135)

#	Runner
92	`linux-amd64-cpu16`
17	`linux-amd64-gpu-v100-latest-1`
15	`windows-amd64-cpu16`
10	`linux-arm64-cpu16`
1	`linux-amd64-gpu-h100-latest-1-testing`

Also ensure that we actually can enable FP8 due to FP16 and BF16 requirements Co-authored-by: Michael Schellenberger Costa <[email protected]>

@shwina

update docs update docs add `memcmp`, `memmove` and `memchr` implementations implement tests Use cuda::std::min/max in Thrust (NVIDIA#3364) Implement `cuda::std::numeric_limits` for `__half` and `__nv_bfloat16` (NVIDIA#3361) * implement `cuda::std::numeric_limits` for `__half` and `__nv_bfloat16` Cleanup util_arch (NVIDIA#2773) Deprecate thrust::null_type (NVIDIA#3367) Deprecate cub::DeviceSpmv (NVIDIA#3320) Fixes: NVIDIA#896 Improves `DeviceSegmentedSort` test run time for large number of items and segments (NVIDIA#3246) * fixes segment offset generation * switches to analytical verification * switches to analytical verification for pairs * fixes spelling * adds tests for large number of segments * fixes narrowing conversion in tests * addresses review comments * fixes includes Compile basic infra test with C++17 (NVIDIA#3377) Adds support for large number of items and large number of segments to `DeviceSegmentedSort` (NVIDIA#3308) * fixes segment offset generation * switches to analytical verification * switches to analytical verification for pairs * addresses review comments * introduces segment offset type * adds tests for large number of segments * adds support for large number of segments * drops segment offset type * fixes thrust namespace * removes about-to-be-deprecated cub iterators * no exec specifier on defaulted ctor * fixes gcc7 linker error * uses local_segment_index_t throughout * determine offset type based on type returned by segment iterator begin/end iterators * minor style improvements Exit with error when RAPIDS CI fails. (NVIDIA#3385) cuda.parallel: Support structured types as algorithm inputs (NVIDIA#3218) * Introduce gpu_struct decorator and typing * Enable `reduce` to accept arrays of structs as inputs * Add test for reducing arrays-of-struct * Update documentation * Use a numpy array rather than ctypes object * Change zeros -> empty for output array and temp storage * Add a TODO for typing GpuStruct * Documentation udpates * Remove test_reduce_struct_type from test_reduce.py * Revert to `to_cccl_value()` accepting ndarray + GpuStruct * Bump copyrights --------- Co-authored-by: Ashwin Srinath <[email protected]> Deprecate thrust::async (NVIDIA#3324) Fixes: NVIDIA#100 Review/Deprecate CUB `util.ptx` for CCCL 2.x (NVIDIA#3342) Fix broken `_CCCL_BUILTIN_ASSUME` macro (NVIDIA#3314) * add compiler-specific path * fix device code path * add _CCC_ASSUME Deprecate thrust::numeric_limits (NVIDIA#3366) Replace `typedef` with `using` in libcu++ (NVIDIA#3368) Deprecate thrust::optional (NVIDIA#3307) Fixes: NVIDIA#3306 Upgrade to Catch2 3.8 (NVIDIA#3310) Fixes: NVIDIA#1724 refactor `<cuda/std/cstdint>` (NVIDIA#3325) Co-authored-by: Bernhard Manfred Gruber <[email protected]> Update CODEOWNERS (NVIDIA#3331) * Update CODEOWNERS * Update CODEOWNERS * Update CODEOWNERS * [pre-commit.ci] auto code formatting --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Fix sign-compare warning (NVIDIA#3408) Implement more cmath functions to be usable on host and device (NVIDIA#3382) * Implement more cmath functions to be usable on host and device * Implement math roots functions * Implement exponential functions Redefine and deprecate thrust::remove_cvref (NVIDIA#3394) * Redefine and deprecate thrust::remove_cvref Co-authored-by: Michael Schellenberger Costa <[email protected]> Fix assert definition for NVHPC due to constexpr issues (NVIDIA#3418) NVHPC cannot decide at compile time where the code would run so _CCCL_ASSERT within a constexpr function breaks it. Fix this by always using the host definition which should also work on device. Fixes NVIDIA#3411 Extend CUB reduce benchmarks (NVIDIA#3401) * Rename max.cu to custom.cu, since it uses a custom operator * Extend types covered my min.cu to all fundamental types * Add some notes on how to collect tuning parameters Fixes: NVIDIA#3283 Update upload-pages-artifact to v3 (NVIDIA#3423) * Update upload-pages-artifact to v3 * Empty commit --------- Co-authored-by: Ashwin Srinath <[email protected]> Replace and deprecate thrust::cuda_cub::terminate (NVIDIA#3421) `std::linalg` accessors and `transposed_layout` (NVIDIA#2962) Add round up/down to multiple (NVIDIA#3234) [FEA]: Introduce Python module with CCCL headers (NVIDIA#3201) * Add cccl/python/cuda_cccl directory and use from cuda_parallel, cuda_cooperative * Run `copy_cccl_headers_to_aude_include()` before `setup()` * Create python/cuda_cccl/cuda/_include/__init__.py, then simply import cuda._include to find the include path. * Add cuda.cccl._version exactly as for cuda.cooperative and cuda.parallel * Bug fix: cuda/_include only exists after shutil.copytree() ran. * Use `f"cuda-cccl @ file://{cccl_path}/python/cuda_cccl"` in setup.py * Remove CustomBuildCommand, CustomWheelBuild in cuda_parallel/setup.py (they are equivalent to the default functions) * Replace := operator (needs Python 3.8+) * Fix oversights: remove `pip3 install ./cuda_cccl` lines from README.md * Restore original README.md: `pip3 install -e` now works on first pass. * cuda_cccl/README.md: FOR INTERNAL USE ONLY * Remove `$pymajor.$pyminor.` prefix in cuda_cccl _version.py (as suggested under NVIDIA#3201 (comment)) Command used: ci/update_version.sh 2 8 0 * Modernize pyproject.toml, setup.py Trigger for this change: * NVIDIA#3201 (comment) * NVIDIA#3201 (comment) * Install CCCL headers under cuda.cccl.include Trigger for this change: * NVIDIA#3201 (comment) Unexpected accidental discovery: cuda.cooperative unit tests pass without CCCL headers entirely. * Factor out cuda_cccl/cuda/cccl/include_paths.py * Reuse cuda_cccl/cuda/cccl/include_paths.py from cuda_cooperative * Add missing Copyright notice. * Add missing __init__.py (cuda.cccl) * Add `"cuda.cccl"` to `autodoc.mock_imports` * Move cuda.cccl.include_paths into function where it is used. (Attempt to resolve Build and Verify Docs failure.) * Add # TODO: move this to a module-level import * Modernize cuda_cooperative/pyproject.toml, setup.py * Convert cuda_cooperative to use hatchling as build backend. * Revert "Convert cuda_cooperative to use hatchling as build backend." This reverts commit 61637d6. * Move numpy from [build-system] requires -> [project] dependencies * Move pyproject.toml [project] dependencies -> setup.py install_requires, to be able to use CCCL_PATH * Remove copy_license() and use license_files=["../../LICENSE"] instead. * Further modernize cuda_cccl/setup.py to use pathlib * Trivial simplifications in cuda_cccl/pyproject.toml * Further simplify cuda_cccl/pyproject.toml, setup.py: remove inconsequential code * Make cuda_cooperative/pyproject.toml more similar to cuda_cccl/pyproject.toml * Add taplo-pre-commit to .pre-commit-config.yaml * taplo-pre-commit auto-fixes * Use pathlib in cuda_cooperative/setup.py * CCCL_PYTHON_PATH in cuda_cooperative/setup.py * Modernize cuda_parallel/pyproject.toml, setup.py * Use pathlib in cuda_parallel/setup.py * Add `# TOML lint & format` comment. * Replace MANIFEST.in with `[tool.setuptools.package-data]` section in pyproject.toml * Use pathlib in cuda/cccl/include_paths.py * pre-commit autoupdate (EXCEPT clang-format, which was manually restored) * Fixes after git merge main * Resolve warning: AttributeError: '_Reduce' object has no attribute 'build_result' ``` =========================================================================== warnings summary =========================================================================== tests/test_reduce.py::test_reduce_non_contiguous /home/coder/cccl/python/devenv/lib/python3.12/site-packages/_pytest/unraisableexception.py:85: PytestUnraisableExceptionWarning: Exception ignored in: <function _Reduce.__del__ at 0x7bf123139080> Traceback (most recent call last): File "/home/coder/cccl/python/cuda_parallel/cuda/parallel/experimental/algorithms/reduce.py", line 132, in __del__ bindings.cccl_device_reduce_cleanup(ctypes.byref(self.build_result)) ^^^^^^^^^^^^^^^^^ AttributeError: '_Reduce' object has no attribute 'build_result' warnings.warn(pytest.PytestUnraisableExceptionWarning(msg)) -- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html ============================================================= 1 passed, 93 deselected, 1 warning in 0.44s ============================================================== ``` * Move `copy_cccl_headers_to_cuda_cccl_include()` functionality to `class CustomBuildPy` * Introduce cuda_cooperative/constraints.txt * Also add cuda_parallel/constraints.txt * Add `--constraint constraints.txt` in ci/test_python.sh * Update Copyright dates * Switch to https://github.com/ComPWA/taplo-pre-commit (the other repo has been archived by the owner on Jul 1, 2024) For completeness: The other repo took a long time to install into the pre-commit cache; so long it lead to timeouts in the CCCL CI. * Remove unused cuda_parallel jinja2 dependency (noticed by chance). * Remove constraints.txt files, advertise running `pip install cuda-cccl` first instead. * Make cuda_cooperative, cuda_parallel testing completely independent. * Run only test_python.sh [skip-rapids][skip-matx][skip-docs][skip-vdc] * Try using another runner (because V100 runners seem to be stuck) [skip-rapids][skip-matx][skip-docs][skip-vdc] * Fix sign-compare warning (NVIDIA#3408) [skip-rapids][skip-matx][skip-docs][skip-vdc] * Revert "Try using another runner (because V100 runners seem to be stuck) [skip-rapids][skip-matx][skip-docs][skip-vdc]" This reverts commit ea33a21. Error message: NVIDIA#3201 (comment) * Try using A100 runner (because V100 runners still seem to be stuck) [skip-rapids][skip-matx][skip-docs][skip-vdc] * Also show cuda-cooperative site-packages, cuda-parallel site-packages (after pip install) [skip-rapids][skip-matx][skip-docs][skip-vdc] * Try using l4 runner (because V100 runners still seem to be stuck) [skip-rapids][skip-matx][skip-docs][skip-vdc] * Restore original ci/matrix.yaml [skip-rapids] * Use for loop in test_python.sh to avoid code duplication. * Run only test_python.sh [skip-rapids][skip-matx][skip-docs][skip-vdc][skip pre-commit.ci] * Comment out taplo-lint in pre-commit config [skip-rapids][skip-matx][skip-docs][skip-vdc] * Revert "Run only test_python.sh [skip-rapids][skip-matx][skip-docs][skip-vdc][skip pre-commit.ci]" This reverts commit ec206fd. * Implement suggestion by @shwina (NVIDIA#3201 (review)) * Address feedback by @leofang --------- Co-authored-by: Bernhard Manfred Gruber <[email protected]> cuda.parallel: Add optional stream argument to reduce_into() (NVIDIA#3348) * Add optional stream argument to reduce_into() * Add tests to check for reduce_into() stream behavior * Move protocol related utils to separate file and rework __cuda_stream__ error messages * Fix synchronization issue in stream test and add one more invalid stream test case * Rename cuda stream validation function after removing leading underscore * Unpack values from __cuda_stream__ instead of indexing * Fix linting errors * Handle TypeError when unpacking invalid __cuda_stream__ return * Use stream to allocate cupy memory in new stream test Upgrade to actions/deploy-pages@v4 (from v2), as suggested by @leofang (NVIDIA#3434) Deprecate `cub::{min, max}` and replace internal uses with those from libcu++ (NVIDIA#3419) * Deprecate `cub::{min, max}` and replace internal uses with those from libcu++ Fixes NVIDIA#3404 Fix CI issues (NVIDIA#3443) Remove deprecated `cub::min` (NVIDIA#3450) * Remove deprecated `cuda::{min,max}` * Drop unused `thrust::remove_cvref` file Fix typo in builtin (NVIDIA#3451) Moves agents to `detail::<algorithm_name>` namespace (NVIDIA#3435) uses unsigned offset types in thrust's scan dispatch (NVIDIA#3436) Default transform_iterator's copy ctor (NVIDIA#3395) Fixes: NVIDIA#2393 Turn C++ dialect warning into error (NVIDIA#3453) Uses unsigned offset types in thrust's sort algorithm calling into `DispatchMergeSort` (NVIDIA#3437) * uses thrust's dynamic dispatch for merge_sort * [pre-commit.ci] auto code formatting --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Refactor allocator handling of contiguous_storage (NVIDIA#3050) Co-authored-by: Michael Schellenberger Costa <[email protected]> Drop thrust::detail::integer_traits (NVIDIA#3391) Add cuda::is_floating_point supporting half and bfloat (NVIDIA#3379) Co-authored-by: Michael Schellenberger Costa <[email protected]> Improve docs of std headers (NVIDIA#3416) Drop C++11 and C++14 support for all of cccl (NVIDIA#3417) * Drop C++11 and C++14 support for all of cccl --------- Co-authored-by: Bernhard Manfred Gruber <[email protected]> Deprecate a few CUB macros (NVIDIA#3456) Deprecate thrust universal iterator categories (NVIDIA#3461) Fix launch args order (NVIDIA#3465) Add `--extended-lambda` to the list of removed clangd flags (NVIDIA#3432) add `_CCCL_HAS_NVFP8` macro (NVIDIA#3429) Add `_CCCL_BUILTIN_PREFETCH` (NVIDIA#3433) Drop universal iterator categories (NVIDIA#3474) Ensure that headers in `<cuda/*>` can be build with a C++ only compiler (NVIDIA#3472) Specialize __is_extended_floating_point for FP8 types (NVIDIA#3470) Also ensure that we actually can enable FP8 due to FP16 and BF16 requirements Co-authored-by: Michael Schellenberger Costa <[email protected]> Moves CUB kernel entry points to a detail namespace (NVIDIA#3468) * moves emptykernel to detail ns * second batch * third batch * fourth batch * fixes cuda parallel * concatenates nested namespaces Deprecate block/warp algo specializations (NVIDIA#3455) Fixes: NVIDIA#3409 Refactor CUB's util_debug (NVIDIA#3345)

Also ensure that we actually can enable FP8 due to FP16 and BF16 requirements Co-authored-by: Michael Schellenberger Costa <[email protected]>

* add `_CCCL_HAS_NVFP8` macro (#3429) * Add cuda::is_floating_point supporting half and bfloat (#3379) Co-authored-by: Michael Schellenberger Costa <[email protected]> * Specialize __is_extended_floating_point for FP8 types (#3470) Also ensure that we actually can enable FP8 due to FP16 and BF16 requirements Co-authored-by: Michael Schellenberger Costa <[email protected]> --------- Co-authored-by: Federico Busato <[email protected]> Co-authored-by: Michael Schellenberger Costa <[email protected]>

Also ensure that we actually can enable FP8 due to FP16 and BF16 requirements Co-authored-by: Michael Schellenberger Costa <[email protected]>

Cleanup util_arch (NVIDIA#2773) Improves `DeviceSegmentedSort` test run time for large number of items and segments (NVIDIA#3246) * fixes segment offset generation * switches to analytical verification * switches to analytical verification for pairs * fixes spelling * adds tests for large number of segments * fixes narrowing conversion in tests * addresses review comments * fixes includes Adds support for large number of items and large number of segments to `DeviceSegmentedSort` (NVIDIA#3308) * fixes segment offset generation * switches to analytical verification * switches to analytical verification for pairs * addresses review comments * introduces segment offset type * adds tests for large number of segments * adds support for large number of segments * drops segment offset type * fixes thrust namespace * removes about-to-be-deprecated cub iterators * no exec specifier on defaulted ctor * fixes gcc7 linker error * uses local_segment_index_t throughout * determine offset type based on type returned by segment iterator begin/end iterators * minor style improvements cuda.parallel: Support structured types as algorithm inputs (NVIDIA#3218) * Introduce gpu_struct decorator and typing * Enable `reduce` to accept arrays of structs as inputs * Add test for reducing arrays-of-struct * Update documentation * Use a numpy array rather than ctypes object * Change zeros -> empty for output array and temp storage * Add a TODO for typing GpuStruct * Documentation udpates * Remove test_reduce_struct_type from test_reduce.py * Revert to `to_cccl_value()` accepting ndarray + GpuStruct * Bump copyrights --------- Co-authored-by: Ashwin Srinath <[email protected]> Deprecate thrust::async (NVIDIA#3324) Fixes: NVIDIA#100 Review/Deprecate CUB `util.ptx` for CCCL 2.x (NVIDIA#3342) Deprecate thrust::numeric_limits (NVIDIA#3366) Upgrade to Catch2 3.8 (NVIDIA#3310) Fixes: NVIDIA#1724 Fix sign-compare warning (NVIDIA#3408) Implement more cmath functions to be usable on host and device (NVIDIA#3382) * Implement more cmath functions to be usable on host and device * Implement math roots functions * Implement exponential functions Redefine and deprecate thrust::remove_cvref (NVIDIA#3394) * Redefine and deprecate thrust::remove_cvref Co-authored-by: Michael Schellenberger Costa <[email protected]> cuda.parallel: Add optional stream argument to reduce_into() (NVIDIA#3348) * Add optional stream argument to reduce_into() * Add tests to check for reduce_into() stream behavior * Move protocol related utils to separate file and rework __cuda_stream__ error messages * Fix synchronization issue in stream test and add one more invalid stream test case * Rename cuda stream validation function after removing leading underscore * Unpack values from __cuda_stream__ instead of indexing * Fix linting errors * Handle TypeError when unpacking invalid __cuda_stream__ return * Use stream to allocate cupy memory in new stream test Deprecate `cub::{min, max}` and replace internal uses with those from libcu++ (NVIDIA#3419) * Deprecate `cub::{min, max}` and replace internal uses with those from libcu++ Fixes NVIDIA#3404 Remove deprecated `cub::min` (NVIDIA#3450) * Remove deprecated `cuda::{min,max}` * Drop unused `thrust::remove_cvref` file Fix typo in builtin (NVIDIA#3451) Moves agents to `detail::<algorithm_name>` namespace (NVIDIA#3435) Drop thrust::detail::integer_traits (NVIDIA#3391) Add cuda::is_floating_point supporting half and bfloat (NVIDIA#3379) Co-authored-by: Michael Schellenberger Costa <[email protected]> add `_CCCL_HAS_NVFP8` macro (NVIDIA#3429) Specialize __is_extended_floating_point for FP8 types (NVIDIA#3470) Also ensure that we actually can enable FP8 due to FP16 and BF16 requirements Co-authored-by: Michael Schellenberger Costa <[email protected]> Moves CUB kernel entry points to a detail namespace (NVIDIA#3468) * moves emptykernel to detail ns * second batch * third batch * fourth batch * fixes cuda parallel * concatenates nested namespaces Deprecate block/warp algo specializations (NVIDIA#3455) Fixes: NVIDIA#3409 fix documentation

Also ensure that we actually can enable FP8 due to FP16 and BF16 requirements Co-authored-by: Michael Schellenberger Costa <[email protected]>

bernhardmgruber requested a review from a team as a code owner January 22, 2025 08:45

bernhardmgruber requested a review from fbusato January 22, 2025 08:45

bernhardmgruber commented Jan 22, 2025

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bernhardmgruber changed the title ~~Specialize __is_extended_floating_point_v for FP8 types~~ Specialize __is_extended_floating_point for FP8 types Jan 22, 2025

bernhardmgruber force-pushed the ext_fp branch from 2900d3f to d0fca75 Compare January 22, 2025 08:49

Specialize __is_extended_floating_point_v for FP8 types

387e032

bernhardmgruber force-pushed the ext_fp branch from d0fca75 to 387e032 Compare January 22, 2025 08:50

miscco approved these changes Jan 22, 2025

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miscco added 2 commits January 22, 2025 10:18

Properly check for the function like macro

5d1fc21

Ensure that we actually can enable FP8 due to FP16 and BF16 requirements

508abe3

miscco mentioned this pull request Jan 22, 2025

add _CCCL_HAS_NVFP8 macro #3429

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Fix missed definition

d53f497

bernhardmgruber enabled auto-merge (squash) January 22, 2025 15:17

bernhardmgruber mentioned this pull request Jan 22, 2025

Specialize cuda::std::numeric_limits for FP8 types #3478

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bernhardmgruber merged commit 030fcd7 into NVIDIA:main Jan 22, 2025
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bernhardmgruber mentioned this pull request Jan 22, 2025

Add cuda::is_floating_point support for FP8 types #3464

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Add cuda::is_floating_point support for FP8 types #3464

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bernhardmgruber deleted the ext_fp branch January 22, 2025 15:46

bernhardmgruber mentioned this pull request Jan 22, 2025

Backport to 2.8: some FP8 support #3479

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Specialize __is_extended_floating_point for FP8 types #3470

Specialize __is_extended_floating_point for FP8 types #3470

bernhardmgruber commented Jan 22, 2025

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github-actions bot commented Jan 22, 2025

🟩 cub: Pass: 100%/38 | Total: 1d 02h | Avg: 42m 01s | Max: 59m 13s | Hits: 321%/3540

🟩 libcudacxx: Pass: 100%/37 | Total: 14h 58m | Avg: 24m 17s | Max: 1h 04m | Hits: 411%/10166

🟩 thrust: Pass: 100%/37 | Total: 19h 14m | Avg: 31m 12s | Max: 1h 28m | Hits: 325%/9180

🟩 cudax: Pass: 100%/20 | Total: 1h 45m | Avg: 5m 17s | Max: 17m 01s | Hits: 388%/522

🟩 cccl_c_parallel: Pass: 100%/2 | Total: 11m 54s | Avg: 5m 57s | Max: 9m 46s

🟩 python: Pass: 100%/1 | Total: 42m 14s | Avg: 42m 14s | Max: 42m 14s

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🏃‍ Runner counts (total jobs: 135)

Specialize __is_extended_floating_point for FP8 types #3470

Specialize __is_extended_floating_point for FP8 types #3470

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github-actions bot commented Jan 22, 2025

🟩 cub: Pass: 100%/38 | Total: 1d 02h | Avg: 42m 01s | Max: 59m 13s | Hits: 321%/3540

🟩 libcudacxx: Pass: 100%/37 | Total: 14h 58m | Avg: 24m 17s | Max: 1h 04m | Hits: 411%/10166

🟩 thrust: Pass: 100%/37 | Total: 19h 14m | Avg: 31m 12s | Max: 1h 28m | Hits: 325%/9180

🟩 cudax: Pass: 100%/20 | Total: 1h 45m | Avg: 5m 17s | Max: 17m 01s | Hits: 388%/522

🟩 cccl_c_parallel: Pass: 100%/2 | Total: 11m 54s | Avg: 5m 57s | Max: 9m 46s

🟩 python: Pass: 100%/1 | Total: 42m 14s | Avg: 42m 14s | Max: 42m 14s

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🏃‍ Runner counts (total jobs: 135)