Cupy

This is the release note of v10.0.0b2. See [here](https://github.com/cupy/cupy/pulls?q=is%3Apr+is%3Aclosed+milestone%3Av10.0.0b2) for the complete list of solved issues and merged PRs.

We are running a [Gitter chat](https://gitter.im/cupy/community) for general discussions and quick questions. Feel free to join the channel to talk with developers and users!

Highlights

Support for CUDA Python (5638)

CuPy is one of the first libraries providing support for the newly released [CUDA Python bindings](https://github.com/NVIDIA/cuda-python). To try it, install cuda-python manually and set the `CUPY_USE_CUDA_PYTHON=1` environment variable when building CuPy as written in the [documentation](https://docs.cupy.dev/en/latest/reference/environment.html#envvar-CUPY_USE_CUDA_PYTHON).

This is the release note of v10.0.0b1. See [here](https://github.com/cupy/cupy/pulls?q=is%3Apr+is%3Aclosed+milestone%3Av10.0.0b1) for the complete list of solved issues and merged PRs.

We are running a [Gitter chat](https://gitter.im/cupy/community) for general discussions and quick questions. Feel free to join the channel to talk with developers and users!

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.

Google Summer of Code

CuPy is participating in Google Summer of Code under the [NumFOCUS](https://numfocus.org/programs/google-summer-code) organization.

Our student povinsahu1909 is working hard to add support for sparse linear algebra solvers and increasing the compatibility of the new random number generation API.

Compile with SASS (CUBIN) for CUDA versions >= 11.1 (5097)

Changes NVRTC compile process to produce SASS (CUBIN files) instead of PTX so that kernels compiled with a new CUDA Toolkit version can be run with earlier CUDA Drivers. Check the [CUDA Compatibility Guide](https://docs.nvidia.com/deploy/cuda-compatibility/index.html) and [NVRTC Documentation](https://docs.nvidia.com/cuda/nvrtc/index.html#nvrtc-library-versioning) for detailed information.

Changes without compatibility

Support the new DLPack exchange protocol (5306)

By adopting the new [DLPack exchange protocol](https://data-apis.org/array-api/latest/design_topics/data_interchange.html) proposed in the Python array API standard, `cupy.fromDlpack` has been deprecated in favor of `cupy.from_dlpack`.

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

New Features

- Texture memory 2D/3D affine transformations (5171)
- Support the new DLPack exchange protocol (5306)
- Add cupyx.scipy.sparse.linalg.lsmr (5331)
- JIT: Support all atomic intrinsics (5387)
- Expose `_GUFunc` through `cupyx` (5408)
- Add geometric distribution to new Generator (5443)
- Support Numba-like `jit.gridsize()` syntax in CuPy JIT (5461)
- Support Numba-like `jit.laneid()` and `jit.warpsize` syntax in CuPy JIT (5462)
- Add cupyx.scipy.sparse.linalg.cgs (5524)
- Add hypergeometric distribution to new Generator (5560)

Enhancements

- Compile with SASS for CUDA versions >= 11.1 (5097)
- Support NCCL v2.9.9 (5268)
- Support CUDA 11.4 and `compute_86` (5434)
- Update NumPy/SciPy pinning in `setup.py` (5453)
- Make `matrix_power` support stacked matrices (5458)
- Support hipSPARSE and fix streams not set in some generic APIs in cuSPARSE (5472)
- Add `cudaDeviceDisablePeerAccess` wrapper (5495)
- Support cuDNN v8.2.2 (5516)
- Support NCCL v2.10.3: library installer and document (5521)

Bug Fixes

- JIT: Fix supported dtype of `atomic_add` on HIP (5383)
- Fix cupy.nanmedian's axis parameter to accept a sequence other than a tuple (5389)
- Fix astype from boolean (5410)
- Fix compatibility issues of `ndarray.view` (5428)
- Fix `types` attribute of ufunc (5448)
- Fix new DLPack protocol error messages and tests (5449)
- `texture_memory` option in `affine_transform` not supported by HIP (5464)
- Fix `linalg.lstsq` for empty matrix (5467)
- Fix reshape (5470)
- Fix random generator output not being raveled (5478)
- Fix random `integers` (5479)
- Fix availability tests in cuSOLVER and cuSPARSE (5492)
- Add missing hipSPARSE include to builder (5515)
- prune cuFFT static lib by major cc ver (5531)
- Fix casts from bool in ufunc inputs (5539)
- Access `cudaMemoryType` in the pointer attributes and fix for HIP (5544)
- Fix casts in ufunc outputs (5550)
- Code fix for {cu, roc}SOLVER (5558)
- Fix CUDA API call on module initialization (5561)
- Fix the RTC call path for HIP (5569)
- Fix broadcast error messages (5579)

Code Fixes

- Do not call `cudnnGetVersion` on import (5326)
- JIT: Fix `__call__()` for built-in functions (5361)
- Add HIP symbol redefinitions (5362)
- Remove the data member `use_32bit_indexing` from `CArray` (5376)
- Use `dtype.name` instead `dtype.char` (5444)
- Try to use `-I` in hipRTC (5486)
- Hide modules from public APIs (5522)
- consistent kernel names (5551)
- Use the new macro `__HIP_PLATFORM_AMD__` at build time (5554)

Documentation

- Add upgrade guide for v10 (5278)
- Update tag lines in package description and docs index (5399)
- Fix typo in `apply_along_axis` (5432)
- Fix indent of `Returns` section (5433)
- Update `user_guide/basic.rst` device agnostic section (5435)
- Support CUDA 11.4 on documents (5447)
- Update install guide with new NumPy/SciPy versions (5454)
- Use `from_dlpack` instead of fromDlpack (5488)
- Use Sphinx 4.1.0 (5489)
- Bump ReadTheDocs configuration to version 2 (5491)
- Fix docs of eigh and eigvalsh (5494)
- Add a lingering doc page for `fromDlpack()` (5509)
- Document `scipy.fft` backend usage (5514)
- Replaced the links for NumPy docs as per issue 3418 (5548)
- Use Sphinx's `envvar` construct (5570)
- Fix intersphinx for SciPy 1.7.1 docs (5587)

Installation

- Fix `license_file` option in `setup.cfg` (5406)
- Import numpy before Cython (5482)

Tests

- Add tests for num_to_num's optional parameters (5337)
- Add script for ROCm CI on Jenkins (5378)
- Skip unwrap tests for `numpy<1.21` (5384)
- Enable strict xfail in pytest (5407)
- Remove xfail in windows jitify test (5409)
- Fix preloading slow tests (5440)
- Add script for CUDA 11.4 CI on FlexCI (5457)
- Increase memory for CUDA 11.4 tests (5477)
- Fix DLPack test for ROCm/HIP (5485)
- Fix "Revert test decorators order" (5498)
- Fix some tests for HIP (5501)
- Fix FlexCI Linux tests (5505)
- Add CUDA 11.4 for FlexCI helper script (5528)
- Increase timeout for CUDA 11.4 tests (5575)
- Update tests to install all requirements and add PATH (5576)
- Add Cython to `all` requirements (5577)

Others

- Notify conflict by mergify (5371)
- Fix mergify to only comment when pull-request is open (5439)
- Fix mergify condition (5513)
- Add auto notify bot for `hip` label (5538)
- Use `pull_request_target` instead for auto notify bot (5541)
- Fix auto notify bot for issues (5546)
- Disable Mergify's auto-merge (5556)
- Bump version to v10.0.0b1 (5595)
- Fix signal tests for scipy 1.7.0 (5368)
- Fix `numpy.unwrap` for NumPy 1.21 (5385)
- Fix signaltools `medfilt` for `scipy>=1.7.0` (5386)
- Fix deprecated `numpy.typeDict` utilization (5388)

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

12rambau grlee77 leofang maxim-belkin Palash-Vishnani povinsahu1909 the-lay

This is the release note of v10.0.0a2. See [here](https://github.com/cupy/cupy/pulls?q=is%3Apr+is%3Aclosed+milestone%3Av10.0.0a2) for the complete list of solved issues and merged PRs.

We are running a [Gitter chat](https://gitter.im/cupy/community) for general discussions and quick questions. Feel free to join the channel to talk with developers and users!

Highlights

* CuPy now supports CUDA 11.3 (`cupy-cuda113`) and AMD ROCm 4.2 (`cupy-rocm-4-2`) and binary wheels are now available on PyPI.
* The following Python syntax and new APIs can now be used in JIT target functions.
- Calling `len`, `min`, `max` Python built-ins.
- `len(arr)`: Equivalent to `arr.shape[0]`.
- `min(scalar1, scalar2, ...)`: Returns the minimum value of the inputs.
- `max(scalar1, scalar2, ...)`: Returns the maximum value of the inputs.
- Accessing `.ndim`, `.size` attributes of `ndarray`.
- Unpacking nested tuples.
- `(x, y), z = ...`
- `jit.grid()` API, similar to [`numba.cuda.grid`](https://numba.pydata.org/numba-doc/latest/cuda-reference/kernel.html#numba.cuda.grid).
- `x, y, z = cupyx.jit.grid(3)` (`x` is equal to `threadIdx.x + blockIdx.x * blockDim.x`.)
- Warp shuffle and sync functions.
- `cupyx.jit.shfl_down_sync(mask, var, val_id)` (`__shfl_down_sync(mask, var, val_id)`)
* `cupyx.scipy.sparse.{coo,csr,csc}_matrix` now provides the `reshape` method.

Changes without compatibility

Drop CUDA 9.2 & NCCL 2.4 Support (5214)

CUDA 9.2 and NCCL 2.4 are no longer supported in CuPy v10.

Changes in Stream behavior (5251)

The same `cupy.cuda.Stream` instance can now safely be shared between multiple threads. To achieve this, CuPy v10 will not destroy the stream (i.e., call ``cudaStreamDestroy``) if the stream is the current stream of any thread.

Known Issues

* `cupy-cuda111` wheels only support CUDA 11.1.1 and will not work with CUDA 11.1.0 (5313).
* `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

New Features

- Add reshape method for COO, CSR and CSC matrices (5301)
- Support `len`, `min`, `max`, `.ndim`, `.size` in jit (5319)
- Support nested tuple unpack in CuPy JIT (5332)
- Support Numba-like `jit.grid()` syntax in CuPy JIT (5334)
- Support warp shuffle and sync functions in CuPy JIT (5335)

Enhancements

- Do not use handles unless requested in `cupy.show_config()` (5073)
- Fix to allow sharing a Stream instance between threads (5251)
- Adding GUFunc order, dtype and casting kwarg support (5260)
- Support `nan`, `posinf`, `neginf` in `cupy.nan_to_num` (5295)
- Use independent version of hipFFT for ROCm 4.1 and later (5318)
- Support cuTENSOR v1.3.1 (5338)
- Support cuDNN v8.2.1 (5357)

Performance Improvements

- Make cuTENSOR available in `cupy.einsum` (5203)

Bug Fixes

- Fix `check_availablity` for `cupy.cusolver` (5207)
- Fix `MemoryAsync` to keep a weakref to stream (5264)
- Fix cuFFT callback for `sm_61` etc (5304)
- Fix cuDNN preloading (5327)
- Fix large arrays assignment (5330)
- Ensure source array is C-contiguous before copying to `CUDAArray` (5342)
- Increase test coverage for Generalized Universal Functions (5344)
- Remove unnecessary print (5374)

Code Fixes

- Fix cub repository url (5236)
- Code and comment fixes for stream (5243)
- Use `cdef` instead of `cpdef` where appropriate (5274)

Documentation

- Fix `matmul` docstring (5174)
- Update list of wheels in README (5267)
- Add user guide for FFT (5272)
- Bump CuPy version in docs (5277)
- Add user guide for streams & events (5283)
- Fix deadlink to tutorial and reorder in README (5287)
- Document `ExternalStream` (5305)
- Add ROCm 4.2 support to install docs (5354)
- `user_guide/basic.rst`: various improvements (5356)

Installation

- Drop support for CUDA 9.2 & NCCL 2.4 (5214)
- Add upper restrictions to NumPy/SciPy versions (5225)
- Exclude Cython 3 from `setup_requires` (5273)

Tests

- Fix threading memory pool tests (5263)
- Temporarily remove the async pool test from `TestAllocator` (5308)
- Fix Windows CI kernel cache (5310)
- Tentatively skip unstable `MemoryPoolAsync` tests (5350)
- Xfail random generator tests for HIP (5355)
- Tentatively pin to SciPy 1.6 in Windows CI (5366)

Contributors

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

anaruse eternalphane leofang maxim-belkin povinsahu1909

This is the release note of v10.0.0a1. See [here](https://github.com/cupy/cupy/pulls?q=is%3Apr+is%3Aclosed+milestone%3v10.0.0a1) for the complete list of solved issues and merged PRs.

We are running a [Gitter chat](https://gitter.im/cupy/community) for general discussions and quick questions. Feel free to join the channel to talk with developers and users!

Highlights

CUDA 11.0 and 11.1 wheels not available yet in PyPI (4971)

In the meantime, they can be downloaded from the Assets section below. See 4971 for the detailed instructions.

Changes without compatibility

Current stream is now managed per device (5172)

CuPy now automatically manages the stream switching when changing a device, so the user is not responsible for changing the stream anymore.

This pull-request also includes a bug fix for 5143. An existing code mixing `with stream:` blocks and `stream.use()` may get different results as the stream set via `use()` API will not be reactivated when exiting a stream context.

py
s1 = cupy.cuda.Stream()
s2 = cupy.cuda.Stream()
s3 = cupy.cuda.Stream()
with s1:
s2.use()
with s3:
pass
cupy.cuda.get_current_stream() -> CuPy v10 returns `s1` instead of `s2`.


Make `cupy.cuda.Device` context manager interface thread safe (5083)

The use of a single `cupy.cuda.Device` context manager object with multiple threads was leading to incorrect behavior when restoring the previous device since the first versions of CuPy. Now the correct device is restored back so user code relying on this incorrect behavior might need to be updated.

Deprecate `cupyx.allow_synchronize` and `cupyx.DeviceSynchronized` APIs (5226)

These APIs used for detecting when synchronization to a device was happening have been deprecated since they don’t provide reliable behavior.

Changes

Note: many of these PRs are backported to the v9 series and available since the release.

New Features

- CUDA 11.2: Add `MemoryAsyncPool` to support `malloc_async` (4592)
- Add APIs for creating NumPy arrays backed by pinned memory (4870)
- Support cuSPARSELt (4883)
- Add gamma distributions to random API (4905)
- Add `random` for uniform [0, 1) generation (4906)
- Add `poisson` distribution to random API (4927)
- Add SciPy compatible connected_components (4940)
- Support shared memory in CuPy JIT (4950)
- Add cupyx.scipy.sparse.kronsum() (4968)
- Add `hfft2`, `ihfft2`, `hfftn`, and `ihfftn` to `cupyx.scipy.fft` (4996)
- CuPy JIT: Print kernel code (5017)
- Add `cupyx.jit.atomic_add` (5169)
- CUDA 11.2/11.3: Support `MemoryAsyncPool` statistics and limits (5177)

Enhancements

- Ability to pass structured data types by value as kernel parameters (4829)
- Move the NVTX module to `cupy_backends.cuda.libs` (4930)
- Disable CUB SpMV on CUDA 11.x (4949)
- CuPy JIT: Readable compile error messages (4991)
- Fix JIT test failures on ROCm (4998)
- Mark `cupyx.jit.rawkernel` as experimental (5005)
- HIP: add `-ftz=true` (5007)
- Give gufunc a name (5013)
- CuPy JIT: Use C++-like typing rule in 'cuda' mode (5028)
- Add PCI Bus ID to show_config (5037)
- Print cuSPARSELt version in `show_config` (5054)
- Support custom getsource option in CuPy JIT (5071)
- Make `cupy.cuda.Device` context manager interface thread safe (5083)
- Add a new argument `out` to `cupy.asnumpy()` (5155)
- Support cuSPARSELt v0.1.0 (5158)
- Per device stream (5172)
- cuTENSOR v1.3.0 for library installer (5192)
- Add `sum_labels` to `cupyx.scipy.ndimage.measure` (5200)
- Support NCCL v2.9.8 (5201)
- Fix thrust compilation for ROCm 4.2.0 (5209)
- Add NVCC path and Python version to `show_config` (5215)
- Add CUDA 11.3 headers (5218)
- Add libraries for CUDA 11.3 (5219)
- Remove `syncdetect` APIs (5226)

Bug Fixes

- Use `THRUST_OPTIONAL_CPP11_CONSTEXPR` (5002)
- Use async memcpy in `ndarray.copy` (5004)
- Fix DLPack `lanes` (5045)
- Disable cuFFT plan cache on CUDA 11.1 (5046)
- Support PTDS in CuPy memory pool (5072)
- CuPy JIT: Fix range type (5077)
- Fix `poisson` to support lam array (5087)
- Adjust PATH when preloading to load cuDNN v8 correctly on Windows (5103)
- Bugfix for typing rule of CuPy JIT (5125)
- Fix TypeError in `svds` (5140)
- Properly handle non-contiguous RHS in `cupyx.scipy.sparse.linalg.spsolve` (5168)
- Fix integer `scatter_add` failure on Windows (5173)
- `MemoryAsyncPool`: Use the "current" mempool instead of the "default" one (5191)
- Fix `matmul` for input with relaxed strides (5205)
- Add `check_availability` for cuTensor routines (5206)
- Fix windows `constexpr` (5233)
- Remove duplicated subtraction in `cupy.random.Generator.integers` (5247)

Code Fixes

- Rename `cupy.core` submodule to `cupy._core` (3820)
- Fix some internal `cpdef` functions to `cdef` in `_kernel.pyx` (5084)
- Remove `cupy.cupy` (5121)
- Cosmetic change in cuSPARSELt stub header (5149)
- Cosmetic changes of CuPy JIT implementation (5152)

Documentation

- Follow the latest NumPy/SciPy docs style (4945)
- Fix docs: cupy-cuda112 now on PyPI (4957)
- Update installation guide for Conda-Forge (4985)
- CuPy JIT documentation (5012)
- Document `cupyx.time.repeat` (5015)
- Document `cupy.cuda.runtime.getDeviceProperties` (5016)
- More documentation on the supported backends (5019)
- Add links to Anaconda, Gitter, StackOverflow (5020)
- Improve the documentation on interoperability (5023)
- Document `CFunctionAllocator` and `ManagedMemory` (5025)
- Fix code block in installation guide (5033)
- Improve comments for memory and stream API usage (5060)
- Point to the correct numpy random docs (5088)
- Add user guide (5093)
- Add ROCm limitations to docs (5107)
- Reorganize API reference pages (5108)
- Revise ROCm doc (5122)
- Fix docs of `scatter_add` (5129)
- Mention baseline API change in upgrade guide (5131)
- Fix ROCm wheel install steps (5133)
- Fix docstring in `coo.py` (5139)
- Fix docs in `stream.pyx` (5144)
- cuDNN v8.2 on documentation (5148)
- Mention PTDS in ROCm Limitation (5159)
- Use Sphinx 4 (5188)
- cuTENSOR v1.3 on documentation (5196)
- Fix cuSPARSELt not covered in docs (5221)
- Add `cupyx.scipy.ndimage.sum_labels` to docs (5223)
- Improve README (5254)
- Update logo image (5255)
- Tentatively remove CUDA 11.3 from support list (5256)

Installation

- Fix Windows dll loading for Conda (4974)
- Add warnings for duplicate installation (5032)
- cuDNN v8.2.0 for library installer (5146)
- Bump version to v10.0.0a1 (5269)

Examples

- Fix cuSPARSELt example not to use internal function (4995)
- Update examples for current version of CuPy (4999)

Tests

- Refactor random tests (4907)
- Tentatively pin CI to ROCm 4.0.1 (4961)
- Fix `cutensor` import in the test (4965)
- Make `install_tests` runnable without depending on current path (4969)
- Avoid using `pip install -e` on Windows CI for performance (4970)
- Update known base branches in flexCI config (4973)
- Update list of known branches (4982)
- Fix `TestStream` cleanup (5042)
- Mark some memory tests as `testing.slow` (5061)
- Fix stream usage on D2D copy test under HIP (5091)
- Xfail tests for random distribution generator under HIP/ROCm (5096)
- Adjust testing tolerance for `hfftn` for HIP/ROCm (5099)
- Use current device in tests (5127)
- Fix for updated FlexCI base image (5164)
- Relax tolerance of `cupyx.jit.atomic_add` test (5186)
- Test build for ROCm 4.0 and latest (5224)
- Fix mergify configuration (5248)

Others

- Use bot mode in automatic backport (5051)

Contributors

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

anaruse beingaryan eternalphane grlee77 insertinterestingnamehere keckj leofang povinsahu1909 UmashankarTriforce

This is the release note of v9.6.0. See [here](https://github.com/cupy/cupy/pulls?q=is%3Apr+is%3Aclosed+milestone%3Av9.6.0) for the complete list of solved issues and merged PRs.

We are running a [Gitter chat](https://gitter.im/cupy/community) for general discussions and quick questions. Feel free to join the channel to talk with developers and users!

Announcements

Final release for v9.x series

This is expected to be the last release of the CuPy v9 series. Please start trying your workflow with CuPy v10.0.0rc1 and [let us know](https://github.com/cupy/cupy/issues) if you have any feedback!

This is the release note of v9.5.0. See [here](https://github.com/cupy/cupy/pulls?q=is%3Apr+is%3Aclosed+milestone%3Av9.5.0) for the complete list of solved issues and merged PRs.

We are running a [Gitter chat](https://gitter.im/cupy/community) for general discussions and quick questions. Feel free to join the channel to talk with developers and users!

Announcements

Removal of Alpha/Beta/RC Wheels from PyPI

* As per the discussion in 5671, we stopped uploading pre-release binary wheels to PyPI for the health of the ecosystem. Pre-release wheels can now be downloaded from the recently introduced custom index (e.g., `pip install cupy-cudaXXX -f https://pip.cupy.dev/pre`) . Note that the [sdist package](https://pypi.org/project/cupy/) is available in PyPI for all versions.

* Outdated (v8.0.0rc1 or earlier) pre-release binaries have been removed from PyPI. See 5667 for details.

Changes

Enhancements

- Support cuDNN 8.2.4 (5744)
- Support NCCL 2.11.4 (5747)
- Fix `cupyx.optimize` to save file when no optimization ran (5760)

Bug Fixes

- Fix spline filter with large array (5686)
- Fix exception for indexing with multiple ellipses (5739)
- Fix docstring for fallback modules (5742)
- Include `stdexcept` in hip headers (5777)
- Fixed typo in error message in sparse.csr_matrix (5788)
- Fix `MAX_NDIM` and add guards/tests (5798)
- Disable spmm on Windows CUDA 10.2 (5805)

Documentation

- Fix random docstring (5708)
- Remove `--pre` from ROCm source build instructions (5782)
- Use custom index for pre-release wheels (5793)

Installation

- Add maintainers in `setup.py` (5758)
- Bump version to v9.5.0 (5808)

Tests

- Update `test_eigenvalue.py` (5643)
- Improve performance of `TestSplineFilter1dLargeArray` (5694)
- Stop inheriting `unittest.TestCase` for performance (5710)
- `TestSplineFilter1dLargeArray` marked slow and reduced memory usage (5729)
- Make testing helpers support non-methods (5731)
- Make test parameter names static (5733)
- Update pip and setuptools in Windows CI (5738)
- Improve FlexCI output (5796)
- Fix error message comparison (5806)

Others

- Add workflow to test/build/push docker images on pull-request/release (5752)

Contributors

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

christinahedges emcastillo kmaehashi leofang takagi toslunar