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PyPI · #3443 most downloaded on PyPI
CuPy: NumPy & SciPy for GPU
Last release 1 months ago
20 Aug 2026
Ships fairly regularly
a new release about every 3 months
Nearly every release is documented
notes for 19 of 19 stable releases
1 version withdrawn
withdrawn after publishing
4 years old
20 releases · first in 2023
One column per quarter.
Replace deprecated HIP API calls with their non-deprecated equivalents
This release for the CuPy v14 series introduces new features, enhancements, and bug fixes.
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We are happy to present to you the new sparse array classes, following SciPy counterparts for CPU. We encourage users to migrate from sparse matrices to sparse arrays following SciPy’s migration guide. New user code should stick to sparse arrays.
In this release, the supported formats include COO, CSR, CSC, and DIA. All formats support 2D and COO/CSR additionally support 1D. Both 32-bit and 64-bit indexing are supported. See our sparse array documentation for more information.
CuPy now offers experimental support for CUDA 13.4 Developer Preview on RTX Spark. Building CuPy from source on WoA (Windows on Arm) is now possible. Experimental WoA wheels will be uploaded to PyPI in a few days after the release are available on PyPI (uploaded on 2026-09-01).
As part of tighter coupling with NVIDIA CUDA Python platform, CuPy has begun the integration with nvmath-python, NVIDIA Math Libraries for the Python Ecosystem. CuPy can now be built from source against nvmath-python v1.0+ with the environment variable CUPY_USE_CUDA_PYTHON=1 to access CUDA math libraries. nvmath-python will become a default dependency in a future CuPy release.
In addition to the Linux wheels provided in v14.1, CuPy v14.2 now offers Python 3.14t wheels for Windows.
See here for the complete list of merged PRs.
cumulative_sum and cumulative_prod (Array API) (#10200)__device__ instead of __global__ (#10071)delete incompatibilities with NumPy (#10010).gitattributes for generated files (#10206)The CuPy Team would like to thank all those who contributed to this release!
@acosmicflamingo @asi1024 @DanielCohenn @dufp2002 @eriknw @gdaisukesuzuki @gpinkert @isVoid @jcrist @kmaehashi @leofang @mfep @seberg @somtri @steppi @thakoreh @ViSaReVe @yangcal
This hotfix release removes an unexpected dependency on pytest in the v14.1.0 release.
This hotfix release removes an unexpected dependency on pytest in the v14.1.0 release.
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See here for the complete list of merged PRs.
pytest dependency in cupy.testing (and test) (#9968)The CuPy Team would like to thank all those who contributed to this release!
Deprecate sparse matrix APIs removed in SciPy 1.14
This release for the CuPy v14 series introduces new features, enhancements, and bug fixes.
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CuPy now supports large sparse matrices, allowing 64-bit sized dimensions and number of nonzero elements. Similar to SciPy, creation functions will automatically choose the larger index dtype for the sparsity pattern. The added functionality mostly uses newly wrapped cuSPARSE calls.
CuPy 14.1 now releases free-threaded Python 3.14t Linux wheels and includes a number of thread-safety fixes. As threading issues can be intermittent, please report any issues you encounter. A known limitation is that some threaded CUDA graph-capture calls may fail when using threads.
CuPy now supports structured dtypes with fields in kernels. This enables previously missing features such as comparisons and casts/copies. Because CUDA requires a larger alignment in some cases, CuPy now includes the make_aligned_dtype helper to create structured dtypes with larger alignments than guaranteed by NumPy’s align=True.
CuPy now caches template kernels instantiated using name_expressions with RawModule. This avoids recompilation in cases where CuPy was previously unable to use the on-disk cache.
Users can now set the environment variable CUPY_NVRTC_USE_PCH=1 to use NVRTC’s precompiled headers (PCH) with CUDA 12.8+. This can drastically speed up compilation of multiple kernels and should be especially useful when the on-disk cache is cold or not used.
CuPy now supports CUDA 13.2 and NCCL 2.29.
CuPy now supports cupy.byteswap, cupy.isdtype, cupy.matrix_transpose, cupy.linalg.matmul and the cupyx.scipy.linalg.sparse.bicgstab (BIConjugate Gradient STABilized) solver. cupy.repeat was sped up and extended to allow a CuPy array of repeats.
See here for the complete list of merged PRs.
ndarray.byteswap() (#9868)cupyx.scipy.sparse (#9914)name_expressions (#9912)cupy.linalg.matmul, cupy.linalg.matrix_transpose and cupy.matrix_transpose (#9929)CUPY_NVRTC_USE_PCH=1 and use it for tests (#9783)cupyx.scipy.ndimage interpolation functions (zoom, shift, rotate, affine_transform, map_coordinates) (#9808)mdspan and mT (#9789)--device-as-default-execution-space for hip (#9819).real and broadcast (#9865)cutensor bindings threadsafe (and some small fixes) (#9870)cupyx.scipy.ndimage.interpolation (#9893)scipy.linalg.* comparison table (#9744)FutureWarning (#9778)test_assumed_runtime_version for Windows + CUDA >=13.0 (#9786)CUPY_TEST_GPU_LIMIT more reliable. (#9882)test_assumed_runtime_version (#9903)The CuPy Team would like to thank all those who contributed to this release!
@astroboylrx @Bhuvan1527 @eriknw @ev-br @gdaisukesuzuki @gpinkert @grlee77 @ikrommyd @jberg5 @jeremyfirst22 @kmaehashi @larsoner @leofang @ManuCorrea @marco-pas @mdhaber @megha-darda @seberg
This is a hot-fix release that addresses several issues reported after the v14.0.0 release.
This is a hot-fix release that addresses several issues reported after the v14.0.0 release.
Note
Check out our blog post for the key highlights and major changes in CuPy v14!
See here for the complete list of merged PRs.
cupy_backends.cuda.libs not raising AttributeError (#9724)The CuPy Team would like to thank all those who contributed to this release!
DEP: Deprecate jitify=True support (and jitify=False)
CuPy v14 is our first major update in two years, bringing significant enhancements to the ecosystem, including NumPy v2 semantics, improved installation via CUDA Pip Wheels, bfloat16 and structured dtypes, and expanded platform support.
Note
Check out our blog post for the key highlights and major changes in CuPy v14!
The following part of the release note only covers the changes since the last pre-release (v14.0.0rc1).
See here for the complete list of merged PRs.
%gpu_timeit IPython magic (#9572)cuda::std::mdspan on host/device (#9639)ml_dtypes.bfloat16 support (#9659)cupy.random.choice (#9619)cp.from_dlpack with ml_dtypes.bfloat16 Optionally (#9675)setJITCallback (#9692)broadcast_arrays, meshgrid return a tuple not list (#9599)CScalar handling and ready it for arbitrary dtypes (#9546)ctk extras (#9553)self from ndarray docstring signature (#9618)cupy_tests/core_tests runs for pytest-run-parallel (#9583)TestChoiceReplaceFalse check (#9633)/test logic (#9638)The CuPy Team would like to thank all those who contributed to this release!
@asi1024 @EarlMilktea @ev-br @gpinkert @Harishjitu @isVoid @kmaehashi @leofang @megha-darda @seberg @aman-coder03 @yangcal @yujiteshima
This is the release note of v13.6.0. See here for the complete list of solved issues and merged PRs.
This is the release note of v13.6.0. See here for the complete list of solved issues and merged PRs.
🌏 We just launched our LinkedIn page. Follow us for the latest news and updates!
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This release adds support for CUDA 13.x. Binary packages are available on PyPI: pip install cupy-cuda13x.
cupyx.scipy.special functions for SciPy 1.16 (#9246)UnboundLocalError when blocking=True (#9282)solve_triangular (as xfail) (#9245)linux.cuda{128,129} CIs (#9261)test_zscore_empty (#9270)The CuPy Team would like to thank all those who contributed to this release!
@asi1024 @brycelelbach @Ellecee @emcastillo @kmaehashi @robertmaynard
This is the release note of v13.5.1. This is a hot-fix release to address an issue related to the buffer protocol support for UMP added in v13.5.0 ( #
This is the release note of v13.5.1. This is a hot-fix release to address an issue related to the buffer protocol support for UMP added in v13.5.0 (#9223). See here for the complete list of solved issues and merged PRs.
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🙌 Help us sustain the project by sponsoring CuPy!
The CuPy Team would like to thank all those who contributed to this release!
Update cutensornet accelerator based on cuquantum-python 25.03 deprecation
Note
2025-07-11: We have marked this release as "yanked" on PyPI to prevent new installations due to unexpected regressions. The hot-fix release v13.5.1 is available.
This is the release note of v13.5.0. See here for the complete list of solved issues and merged PRs.
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nvidia-nccl-cu12). In addition, Arm (aarch64) wheels are now built with NCCL support enabled.We are going to finalize the following RFC issues.
cupyx.tools.install_library in CuPy v14 (#9204){to,from}Dlpack & Update the Interoperability page (#9061)cupyx.scipy.stats.zscore for SciPy 1.15 (#9024)toDlpack() default to the old unversioned one (#9007)cupy.inf in fusion2 (#9043)cupyx.scipy.linalg.expm (#9144)get_typename to emit thrust::complex (#9054)gc.collect() in MemoryHook test code to avoid free hook to happen (#9093)np.sum has numerical change in NumPy 2.3 (#9169)cp.empty(None) to raise TypeError (#9174)cupy.win.cuda129 CI (#9214)cupy.win.cuda129 CI (#9217)pre-commit hooks (#9156)The CuPy Team would like to thank all those who contributed to this release!
@asi1024 @Azusachan @EarlMilktea @ev-br @jakirkham @kmaehashi @leofang @MattTheCuber @rongou @seberg @yangcal
This is the release note of v13.4.1. This is a hot-fix release addressing several issues including DLPack compatibility with existing user code. See h
This is the release note of v13.4.1. This is a hot-fix release addressing several issues including DLPack compatibility with existing user code. See here for the complete list of solved issues and merged PRs.
💬 Join the Matrix chat to talk with developers and users and ask quick questions!
🙌 Help us sustain the project by sponsoring CuPy!
toDlpack() default to the old unversioned one (#9011)cupy.inf in fusion2 (#9044)The CuPy Team would like to thank all those who contributed to this release!
@asi1024 @kmaehashi @seberg
Raise VisibleDeprecationWarning for wavelet functions
This is the release note of v13.4.0. See here for the complete list of solved issues and merged PRs.
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CuPy now supports CUDA 12.8 and the latest NVIDIA Blackwell architecture.
CuPy can now be built with AMD ROCm 6.x.
Binary packages for Python 3.13 are now available.
To provide support for Python 3.13, CuPy codebase has been updated for Cython 3. To build CuPy from source, Cython 3.0 or later is now required instead of Cython 0.29.x.
cupyx.signal.mvdr (#8872)NCCL_ERROR_REMOTE_ERROR to the set of errors from NCCL (#8667)numpy.ComplexWarning with cupy.exceptions.ComplexWarning (#8678)pairwise_distance to cuvs (#8897)CUPY_CACHE_KEY in hash keys (#8946)cupyx.scipy.distance: initialize output array with empty instead of zeros (#8981)cupyx.scipy.spatial.distance.cdist remove explicit zeroing of user-provided output array (#8990)sparse.linalg.{cg, cgs, gmres} tests for scipy>=1.14 (#8551)cupyx.scipy.sparse tests for SciPy 1.14 (#8552)cupy.percentile for NumPy 2.x (#8752)fft.fht following bug fix in SciPy 1.15 (#8891)cupyx.scipy.linalg.kron (#8902)special.sph_harm to ignore DeprecationWarning (#8906)*_like array creation (#8605)hipPointerGetAttributes returns error when pointer is unregistered in ROCm 5.7 (#8609)HIP_VERSION unit (#8619)platform.machine() instead of platform.processor() (#8673)/bigobj on Windows build (#8967)cupyx.scipy.spatial.distance's cdist for RAPIDS 24.12 compatibility (#8975).A attribute to .toarray() method (#8814)_cretate_frame_tree (#8944)bytes copy of CUPY_CACHE_KEY (#8947)fft.rst (#8617)pre-commit (#8650)cupy.array_api removal (#8751)test_firls atol (#8522)special.logsumexp test for empty input (#8555)cupy.scipy.stats.entropy tessts for SciPy 1.14 dtype rule change (#8556)setuptools==73.0.1 (#8569)ValueError (#8625)testing.with_requires to skip broken tests (#8627)scipy is not installed (#8637)OverflowError in TestCopytoFromScalar for NumPy v2 (#8643)test_hilbert for NumPy 2.0 (#8746)flake8 with ruff (#8859)testing.shaped_linspace (#8900)signal.cont2discrete tests (#8901)np.longlong dtype (#8972)locals dict to exec (#8985)pre-commit hooks (#8910)The CuPy Team would like to thank all those who contributed to this release!
@99991 @andfoy <!-- @AnonymousPlayer2000 --> @asi1024 @Azusachan @bernhardmgruber @Berrysoft @chainer-ci @cjnolet @dagardner-nv @EarlMilktea @eltociear @ev-br @grlee77 @HollowMan6 @jakirkham @jemiryguo @kmaehashi @leofang @littlewu2508 @mohitreddy1996 @mroeschke @seberg @takagi
This is the release note of v13.3.0. See here for the complete list of solved issues and merged PRs.
This is the release note of v13.3.0. See here for the complete list of solved issues and merged PRs.
💬 Join the Matrix chat to talk with developers and users and ask quick questions!
🙌 Help us sustain the project by sponsoring CuPy!
The CCCL library bundled with CuPy has been updated to eliminate the Jitify preprocess phase. Users will no longer see the one-time performance warning (Jitify is performing a one-time only warm-up to populate the persistent cache, this may take a few seconds and will be improved in a future release...) unless explicitly requesting the use of Jitify (e.g., cupy.RawModule(..., jitify=True)).
This release provides better interoperability with NumPy 2.0.
CuPy is now tested with CUDA 12.5 and 12.6.
The CuPy team is discussing the possibility of removing NumPy fallback feature in CuPy v14. Feel free to join the discussion in https://github.com/cupy/cupy/issues/8497 if you have any comments or use-cases using this feature.
pkg_resources (#8496)cupyx.scipy.linalg.{tri,tril,triu} from uarray (reverted in #8516) (#8506).toarray() instead of .A attribute (#8517)make_interp_spline (#8390)np.compat.integer_types (#8413)ndarray.get() not honoring current stream when layout is not contiguous (#8418)compiler.py to avoid the popup of the nvcc.exe console (#8438)RandomState.seed() for NumPy 2 compatibility (#8439)KeyErrors from importlib_metadata (#8465)mode=None -> mode="constant" (#8495)cupyx.scipy.linalg.{tri,tril,triu} from uarray (#8516)_eigen.py (#8383)coping -> copying (#8427)(cupyx.)scipy.sparse.*_matrix classes class methods (#8458)NPY errors - fix exception imports and asfarray usage in test code (#8471)The CuPy Team would like to thank all those who contributed to this release!
@andfoy @arkdong @asi1024 @bmerry @EarlMilktea @emcastillo @hmaarrfk @jakirkham @johnnynunez @kmaehashi @leofang @monzelr @seberg @swelborn @takagi @YanivDorGalron
cupyx: cleanup use of deprecated NumPy functionality (NumPy 2.0 compatibility)
This is the release note of v13.2.0. See here for the complete list of solved issues and merged PRs.
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CuPy can now be imported under NumPy 2.0.
CuPy now loads NCCL shared library at the time of import cupy.cuda.nccl, instead of import cupy. This improves NCCL compatibility on mixed-library environments.
The CuPy Team would like to thank all those who contributed to this release! @asi1024 @cclauss @ev-br @grlee77 @kmaehashi @leofang @macrocosme @romerojosh @takagi
Deprecate cupyx.scipy wavelet functions
This is the release note of v13.1.0. See here for the complete list of solved issues and merged PRs.
💬 Join the Matrix chat to talk with developers and users and ask quick questions!
🙌 Help us sustain the project by sponsoring CuPy!
CuPy now supports CUDA 12.3 and 12.4. Binary packages are available for Linux (x86_64/aarch64) and Windows as cupy-cuda12x.
This release fixes the regression in CuPy v13.0.0 that part of CuPy functions were not functioning under pre-Volta platforms (compute capability < 7.0) such as NVIDIA Tesla P100 or GeForce GTX 1080.
cupyx.signal.{complex_cepstrum,real_cepstrum,inverse_complex_cepstrum,minimum_phase} (#8096)cupyx.signal.{firfilter,firfilter_zi,firfilter2} (#8107)cupyx.signal.freq_shift (#8131)cupyx.signal.channelize_poly (#8148)cupyx.signal.ca_cfar (#8167)numpy.float_ and numpy.complex_ (#8181)expm(complex matrix) (#8214)scp.signal.{medfilt,medfilt2d} to raise ValueError for complex64 inputs (#8084)boxcox_llf for SciPy 1.12 changes (#8132)cupyx.scipy wavelet functions (#8139)_nccl_comm.py (#8112)-arch in the compiler options unconditionally (#8161)cupy.show_config() without CUDA (#8192)min/max initial values (#8266)cupyx.scipy.special.betainc for invalid inputs (#8098)vectorstength tests (#8145)cupy.show_config() pass without CUDA installed (#8195)The CuPy Team would like to thank all those who contributed to this release!
@andfoy @asi1024 @emcastillo @ev-br @jemiryguo @kmaehashi @leofang @takagi
See the [Upgrade Guide](https://docs.cupy.dev/en/latest/upgrade.html#cupy-v13) for the list of possible breaking changes in v13.
This is the release note of v13.0.0. See here for the complete list of solved issues and merged PRs.
This release note only covers changes made since the v13.0.0rc1 release. Check out our blog for highlights of the v13 release!
See the Upgrade Guide for the list of possible breaking changes in v13.
💬 Join the Matrix chat to talk with developers and users and ask quick questions!
🙌 Help us sustain the project by sponsoring CuPy!
For all changes in v13, please refer to the release notes of the pre-releases (alpha1, beta1, rc1).
cupyx.signal.pulse_compression from cuSignal's non SciPy-compat API (#8039)cupyx.signal.convolve1d3o from cuSignal's non SciPy-compat API (#8067)cupyx.signal.{pulse_doppler, cfar_alpha} (#8069)cupyx.signal.convolve1d2o (#8113)cupyx.signal.radartools private (#8053)csrmatrix.__pow__ to raise ValueError for non-int other (#8085)lfilter_zi and sosfilt_zi when any IIR coefficient is zero (#8036)argmax/argmin for large reduction axis (#8041)cupyx.scipy.fft.{dst,dstn} in type 2/3 (#8082)from-import (#8114)convolve1d3o (#8100)radartools (#8106)CUDA_PATH warning in Conda installation (#8076)signal.vectorstrength xfail tests (#8083)scipy.linalg not to raise DeprecationWarning for zero-size inputs (#8086)scipy.special.{btdtr,btdtri} are deprecated since SciPy (#8094)@andfoy @asi1024 @emcastillo @hauntsaninja @kmaehashi @takagi
The CuPy Team would like to thank all those who contributed to this release!
See the [Upgrade Guide](https://docs.cupy.dev/en/latest/upgrade.html#cupy-v13) for the list of possible breaking changes in v13.
This is the release note of v12.3.0. See here for the complete list of solved issues and merged PRs.
This is the last planned release for the CuPy v12 series. Please start testing your workload with the v13 release candidate to get ready for the final v13 release. To install: pip install -U --pre cupy-cuda11x -f https://pip.cupy.dev/pre. See the Upgrade Guide for the list of possible breaking changes in v13.
💬 Join the Matrix chat to talk with developers and users and ask quick questions!
🙌 Help us sustain the project by sponsoring CuPy!
Binary packages are now available for Python 3.12.
NINF, PINF, Inf,... usages (#7805)numpy.find_common_type (#7810)scipy.linalg.{tri/tril/triu} are deprecated in SciPy 1.11.0 (#7902)signal.medfilt complex error type for SciPy>=1.11 (#7909)TestSpmatrix on SciPy 1.11 or later (#7918)product, cumproduct, alltrue and sometrue for deprecation (#7936)round_ tests (#7937)cupyx.cusolver (#7819)-U to pre-release installation command (#7806)test_parameterize_pytest_impl test for pytest 7.4.3 (#7968)TestLOBPCG.test_maxit_None CUDA 12.2 CI failure (#8007)The CuPy Team would like to thank all those who contributed to this release!
@asi1024 @emcastillo @kmaehashi @leofang @mtsokol @mvnvidia
Ignore pkg_resources deprecation warning on import
This is the release note of v12.2.0. See here for the complete list of solved issues and merged PRs.
We are running a Gitter chat for general discussions and quick questions. Feel free to join the channel to talk with developers and users!
CuPy now supports CUDA 12.2. Note that there is a known issue on CUDA 12.2 for Windows. See #7776 for details.
As a part of our effort to make CuPy sustainable, we have enrolled in GitHub Sponsors to accept donations. Help us to support CuPy’s development and contribute to ease the required infrastructure costs due to the need of GPU enabled CI platforms and resources to build binary packages.
As a NumFOCUS Sponsored Project, funds sponsored through the GitHub Sponsors are collected and disbursed via NumFOCUS, a 501(c)(3) public charity in the United States, which acts as the fiscal sponsor for the project.
cupy-wheel PackageDue to the recent specification change in Pip 23.1, it became difficult for cupy-wheel to ensure detecting the CUDA version installed correctly. As discussed in RFC #7628, we have decided to remove this package in CuPy v13. To allow existing projects using cupy-wheel to continue to work, the package remains available for v12 releases.
aweights type not checked in cupy.cov (#7717)cython-lint (#7612)asarray (#7695)cupyx.distributed.NCCLBackend.all_gather comment (#7765)cupy-wheel package installation fails with pip 23.1+ (#7624)restore-keys not working (#7614)round_ tests (#7642)pkg_resources deprecation warning on import (#7656)TestLOBPCG::test_maxit_None in CUDA 12.1.1 & cuSOVLER 11.4.5 (#7670)test_fht not to feed cupy.ndarray to scipy.fft.fhtoffset (#7728)The CuPy Team would like to thank all those who contributed to this release!
@12rambau @asi1024 @emcastillo @jnke2016 @kmaehashi @leofang @pelmers @pri1311 @RandomY-2 @takagi
This is the release note of v12.1.0. See here for the complete list of solved issues and merged PRs.
This is the release note of v12.1.0. See here for the complete list of solved issues and merged PRs.
We are running a Gitter chat for general discussions and quick questions. Feel free to join the channel to talk with developers and users!
array_api.take function (#7513)-Xfatbin=-compress-all (#7505)_depends.json not included in wheel (#7584)The CuPy Team would like to thank all those who contributed to this release!
@andfoy @arogozhnikov @asi1024 @kmaehashi @leofang @seberg @takagi
This is the release note of v12.0.0. See here for the complete list of solved issues and merged PRs.
This is the release note of v12.0.0. See here for the complete list of solved issues and merged PRs.
This release note only covers changes made since the v12.0.0rc1 release. Check out our blog for highlights of the v12 release!
We are running a Gitter chat for general discussions and quick questions. Feel free to join the channel to talk with developers and users!
CuPy now supports CUDA 12.1 and cuDNN 8.8. Binary packages are available for Linux (x86_64/aarch64) and Windows as cupy-cuda12x.
$ pip install cupy-cuda12x
Binary packages for aarch64 (Jetson and Arm servers) can now be installed from PyPI.
$ pip install cupy-cuda102
$ pip install cupy-cuda11x
$ pip install cupy-cuda12x
~Note: At the time of the release, Arm wheel of cupy-cuda11x for Python 3.8 (cupy_cuda11x-12.0.0-cp38-cp38-manylinux2014_aarch64.whl) is not available on PyPI. We are working on resolving this issue. Meanwhile, this wheel can be installed from the CuPy index. $ pip install cupy-cuda11x -f https://pip.cupy.dev/aarch64~ This issue was resolved on 2023-04-03.
For all changes in v12, please refer to the release notes of the pre-releases (alpha1, alpha2, beta1, beta2, beta3, rc1).
type_test to type_testing (#7461)scipy.interpolate module (#7450)xfail for invh (#7485)The CuPy Team would like to thank all those who contributed to this release!
@AdrianAbeyta @asi1024 @emcastillo @kmaehashi @seberg
See the [Upgrade Guide](https://docs.cupy.dev/en/latest/upgrade.html#cupy-v12) for the list of possible breaking changes in v12.
This is the release note of v11.6.0. See here for the complete list of solved issues and merged PRs.
This is the last planned release for CuPy v11 series. Please start testing your workload with the v12 release candidate to get ready for the final v12 release. To install:pip install -U --pre cupy-cuda11x -f https://pip.cupy.dev/pre. See the Upgrade Guide for the list of possible breaking changes in v12.
We are running a Gitter chat for general discussions and quick questions. Feel free to join the channel to talk with developers and users!
This release fixes a critical performance regression in CUDA 12.0 that the on-disk kernel cache is ineffective, causing kernels to be recompiled for each python process. Users with CUDA 12.0 are strongly suggested to upgrade to this release.
runtime.getDeviceProperties (#7353)cupy.cuda.profiler.initialize deprecated as it is removed in CUDA 12 (#7379)arange() to raise TypeError in boolean case (#7407)cupyx.scipy.sparse.eigsh (#7361)TestRoundHalfway (#7362)nanargmin/max tests (#7381)fillvalue overflow in cupyx.scipy.signal test (#7401)The CuPy Team would like to thank all those who contributed to this release!
@asi1024 @emcastillo @kmaehashi @leofang @RisaKirisu
Lazy load dtypes deprecated in NumPy 1.24
This is the release note of v11.5.0. See here for the complete list of solved issues and merged PRs.
We are running a Gitter chat for general discussions and quick questions. Feel free to join the channel to talk with developers and users!
CuPy now supports CUDA 12.0 and NVIDIA's latest H100 GPU. Binary packages are available for Linux (x86_64/aarch64) and Windows.
$ pip install cupy-cuda12x
For aarch64:
$ pip install cupy-cuda12x -f https://pip.cupy.dev/aarch64
Note that cuDNN support is unavailable at this time as cuDNN for CUDA 12 has not yet been released.
cupy-cuda12x to cupy-wheel (#7327)array_api (#7321)broadcast_to (#7291)The CuPy Team would like to thank all those who contributed to this release!
@anaruse @hubertlu-tw @kmaehashi @leofang @takagi
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