This is the release note of v9.3.0. See here for the complete list of solved issues and merged PRs.

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Highlights

CuPy now supports CUDA 11.4 (cupy-cuda114)

Along with the new CUDA toolkit version, support for NCCL 2.10.3 and cuDNN 8.2.2 libraries is added.

Compute capability 86 support for GPUs of the RTX 30X0 and AX000 series is also added.

Known Issues

• cupy-cuda102, cupy-cuda110 and cupy-cuda111 wheels are not available yet in PyPI. In the meantime, they can be downloaded from the Assets section below. See #4971 for detailed instructions.

Changes

Enhancements

• Support NCCL v2.9.9 (#5402)
• Update NumPy/SciPy pinning in setup.py (#5471)
• Support CUDA 11.4 and support compute_86 (#5519)
• Support cuDNN v8.2.2 (#5523)
• Make matrix_power support stacked matrices (#5525)
• Support NCCL v2.10.3: library installer and document (#5526)

Bug Fixes

• JIT: Fix supported dtype of atomic_add on HIP (#5405)
• Fix cupy.nanmedian's axis parameter to accept a sequence other than a tuple (#5416)
• Fix compatibility issues of ndarray.view (#5442)
• Fix types attribute of ufunc (#5455)
• Fix random integers (#5484)
• Fix random generator output not being raveled (#5487)
• Fix astype from boolean (#5490)
• Fix reshape (#5504)
• Fix linalg.lstsq for empty matrix (#5506)
• Add missing checks and _setStream() (#5507)
• Fix availability tests in cuSOLVER and cuSPARSE (#5534)
• prune cufft static lib by major cc ver (#5536)
• Fix casts from bool in ufunc inputs (#5549)
• Code fix for {cu, roc}SOLVER (#5566)
• Access cudaMemoryType in the pointer attributes and fix for HIP (#5571)
• Fix broadcast error messages (#5584)
• Fix casts in ufunc outputs (#5589)
• Fix broken build on CUDA 9.2 (#5598)

Code Fixes

• Remove the data member use_32bit_indexing from CArray (#5414)
• JIT: Fix __call__() for built-in functions (#5422)
• Do not call cudnnGetVersion on import (#5446)
• Add HIP symbol redefinitions (#5475)
• Try to use -I in hipRTC (#5502)
• Hide modules from public APIs (#5533)
• Use the new macro __HIP_PLATFORM_AMD__ at build time (#5565)

Documentation

• Update tag lines in package description and docs index (#5415)
• Fix typo in apply_along_axis (#5441)
• Fix indent of Returns section (#5452)
• Update user_guide/basic.rst device agnostic section (#5456)
• Update install guide with new NumPy/SciPy versions (#5465)
• Bump ReadTheDocs configuration to version 2 (#5497)
• Fix docs of eigh and eigvalsh (#5499)
• Use Sphinx 4.1.0 (#5500)
• Document scipy.fft backend usage (#5532)
• Support CUDA 11.4 on documents (#5535)
• Replaced the links for NumPy docs as per issue #3418 (#5553)
• Use Sphinx's envvar construct (#5586)
• Fix intersphinx for SciPy 1.7.1 docs (#5588)

Installation

• Fix license_file option in setup.cfg (#5411)
• Import numpy before Cython (#5483)

Examples

Tests

• Skip unwrap tests for numpy<1.21 (#5412)
• Remove xfail in windows jitify test (#5418)
• Enable strict xfail in pytest (#5423)
• Add missing DLPack test for complex numbers (#5425)
• Fix unwrap tests for v9 (#5426)
• Fix preloading slow tests (#5445)
• Add script for ROCm CI on Jenkins (#5468)
• Add script for CUDA 11.4 CI on FlexCI (#5473)
• Increase memory for CUDA 11.4 tests (#5480)
• Fix "Revert test decorators order" (#5518)
• Fix FlexCI Linux tests (#5520)
• Add CUDA 11.4 for FlexCI helper script (#5543)
• Fix scipy requirement in tests (#5563)
• Fix some tests for HIP (#5578)
• Update tests to install all requirements and add PATH (#5581)
• Add Cython to all requirements (#5582)

Others

• Notify conflict by mergify (#5419)
• Fix mergify to only comment when pull-request is open (#5510)
• Fix mergify condition (#5517)
• Add auto notify bot for hip label (#5540)
• Use pull_request_target instead for auto notify bot (#5542)
• Fix auto notify bot for issues (#5547)
• Disable Mergify's auto-merge (#5562)
• Bump version to v9.3.0 (#5596)
• Fix deprecated numpy.typeDict utilization (#5403)
• Fix signal tests for SciPy 1.7.0 (#5413)

Contributors

The CuPy Team would like to thank all those who contributed to this release!

@12rambau @leofang @maxim-belkin @Palash-Vishnani