This is the release note of v11.0.0b1. See here for the complete list of solved issues and merged PRs.

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Notice (2022-04-05)

We have identified that this release contains a regression that prevents CuPy from working in older CUDA GPUs (Maxwell or earlier). We are planning to fix this issue in the next pre-release. See #6615 for the details.

Highlights

Increase coverage of cupyx.scipy.special APIs (#6461, #6582, #6571)

A series of scipy.special routines have been added to cupyx with optimized CUDA raw kernel implementations. loggamma, multigammaln, fast Hankel transformations and several other utility special functions are added in these series of PRs by @grlee77 and @khushi-411.

Support for CUDA 11.6

Full support for CUDA 11.6 has been added as of this release. Binary packages can be installed with the following commnad: pip install --pre cupy-cuda116 -f https://pip.cupy.dev/pre

Support for ROCm 5.0

Full support for ROCm 5.0 has been added as of this release. Binary packages can be installed with the following commnad: pip install --pre cupy-rocm-5-0 -f https://pip.cupy.dev/pre

Changes without compatibility

Use CUB by default (#6549)

CUB support in CuPy is now enabled by default. This results in faster general reductions and routines such as sum, argmax, argmin having increased performance. Notice that CUB may introduce some non-deterministic behavior and this can be disabled by setting the CUPY_ACCELERATORS="" environment variable.

Drop support for ROCm 4.0 (#6420)

CuPy v11 will drop support for ROCm 4.0. We recommend users to use ROCm 4.3 or 5.0 instead.

Changes

New Features

• Add cupyx.scipy.special statistical distributions (#6461)
• Add cupy.real_if_close API (#6475)
• Add cupyx.scipy.special loggamma, multigammaln and fast Hankel transforms (#6528)
• Add cupyx.scipy.special.{i0e, i1e} (#6571)

Enhancements

• Update cupy.array_api (#6486)
• Fix for supporting ROCm 5.0 (#6524)
• Use CUB by default (#6549)
• Fix cupy.copyto to take NumPy array scalars (#6584)
• Implement ndarray.ravel(order="K") (#6585)
• Make einsum accept subscripts in numpy int (#6506)

Performance Improvements

• Support cusparseSpGEMM() (#6511)
• eigsh: Prefer gemv over gemm (#6570)
• Performance improvement of cupy.in1d (#6583)

Bug Fixes

• Fix cupy.fill to properly take zero-dim cupy.ndarray (#6481)
• Fix error message in vectorize (#6499)
• Fix cupy.cumsum on ROCm 5.0 (#6520)
• Fix coo_matrix.diagonal (#6522)
• Fix array creation shape (#6545)
• Fix out args parser of ufunc (#6546)
• Fix may_share_memory algorithm (#6560)
• Avoid using the same kernel from different devices in JIT (#6575)
• Fix cupy.full and cupy.full_like to make unsafe casting (#6587)
• Fix device context management in MemoryAsyncPool (#6590)

Code Fixes

• mypy: array_api (#6438)
• Minor fixes on uarray backend support (#6526)

Documentation

• Fix documents for CUDA 11.6 (#6405)
• Remove description about issues from contribution guide (#6497)
• Documentation update for ROCm 5.0 (#6530)

Installation

• Skip appending --compiler-bindir if cl.exe is already on PATH (#6510)
• Bump version to v11.0.0b1 (#6601)

Tests

• Add FlexCI projects for Windows (#5889)
• Run cupy-benchmark on CI (#6417)
• Disable CentOS 8 test (#6492)
• Fix Dockerfile broken for array-api tests (#6508)
• CI: Trigger push event of FlexCI via GitHub Actions (#6538)
• Skip async_malloc tests on unsupported device (#6541)
• Fix flaky test_inverse_indices_shape (#6551)
• Trigger CUDA 11.6 Windows CI when push/pull-request (#6553)
• CI: Fix event name in dispatcher (#6555)
• CI: Fix rule name in dispatcher (#6556)

Contributors

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

@anaruse @asi1024 @emcastillo @grlee77 @khushi-411 @kmaehashi @leofang @Onkar627 @peterbell10 @pri1311 @Smit-create @takagi @toslunar @tushxr16