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- # ` cuda.core ` Release notes
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+ # ` cuda.core ` v0.1.1 Release notes
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- Released on Dec XX , 2024
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+ Released on Dec 20 , 2024
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## Hightlights
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- Add ` StridedMemoryView ` and ` @args_viewable_as_strided_memory ` that provide a concrete
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implementation of DLPack & CUDA Array Interface supports.
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- - Add ` Linker ` that can link one or multiple ` ObjectCode ` instances generated by ` Program ` s. Under
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- the hood, it uses either the nvJitLink or cuLink APIs depending on the CUDA version detected
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- in the current environment.
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- - Add a ` cuda.core.experimental.system ` module for querying system- or process- wide information.
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- - Support TCC devices with a default synchronous memory resource to avoid the use of memory pools
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+ - Add ` Linker ` that can link one or multiple ` ObjectCode ` instances generated by ` Program ` . Under
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+ the hood, it uses either the nvJitLink or driver (` cuLink* ` ) APIs depending on the CUDA version
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+ detected in the current environment.
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+ - Support ` pip install cuda-core ` . Please see the Installation Guide for further details.
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## New features
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+ - Add a ` cuda.core.experimental.system ` module for querying system- or process- wide information.
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- Add ` LaunchConfig.cluster ` to support thread block clusters on Hopper GPUs.
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## Enchancements
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- - Ensure "ltoir" is a valid code type to ` ObjectCode ` .
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- - Improve test coverage.
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+ - The internal handle held by ` ObjectCode ` is now lazily initialized upon first touch.
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+ - Support TCC devices with a default synchronous memory resource to avoid the use of memory pools.
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+ - Ensure ` "ltoir" ` is a valid code type to ` ObjectCode ` .
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+ - Document the ` __cuda_stream__ ` protocol.
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+ - Improve test coverage & documentation cross-references.
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- Enforce code formatting.
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## Bug fixes
@@ -35,4 +38,6 @@ Released on Dec XX, 2024
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not supported. This will be fixed in a future release.
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- Some ` LinkerOptions ` are only available when using a modern version of CUDA. When using CUDA <12,
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the backend is the cuLink api which supports only a subset of the options that nvjitlink does.
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- Further, some options aren't available on CUDA versions <12.6
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+ Further, some options aren't available on CUDA versions <12.6.
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+ - To use ` cuda.core ` with Python 3.13, it currently requires building ` cuda-python ` from source
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+ prior to ` pip install ` . This extra step will be fixed soon.
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