Cupy

This is the release note of v8.0.0rc1. See [here](https://github.com/cupy/cupy/milestone/78?closed=1) for the complete list of solved issues and merged PRs.

We are planning to release the final v8.0.0 on October 1st. Please start testing your workload with this release. See the [Upgrade Guide](https://docs.cupy.dev/en/v8.0.0rc1/upgrade.html#cupy-v8) for the list of possible breaking changes.

Highlights

* This release adds support for CUDA 11, NumPy 1.19, and SciPy 1.5.
* Several performance improvements when using cuTENSOR, sparse matrices indexing, matrix multiplication with CUDA 11 using TF32.
* Compatibility with `numpy.poly` is being increased thanks to our GSoC student Dahlia-Chehata!
* Added an interface (3126) to support using external memory allocators such as the PyTorch one (https://github.com/pytorch/pytorch/pull/33860).

Notes on Wheel Packages

* Update on 2020-09-23: `cupy-cuda110` package is now available on PyPI! ~CuPy for CUDA 11.0 (`cupy-cuda110`) wheel packages are currently available only for Windows. We are going to publish Linux wheels once we get [approval](https://github.com/pypa/pypi-support/issues/553) from the PyPI team. (Meanwhile, Linux wheels can be downloaded from the Assets section below (or `pip install cupy-cuda110 -f https://github.com/cupy/cupy/releases/tag/v8.0.0rc1`). Those wheels will be removed once we publish the package on PyPI.)~
* CuPy for CUDA 10.1 (`cupy-cuda101`), 10.2 (`cupy-cuda102`), and 11.0 (`cupy-cuda110`) packages are built with cuDNN v8 support but without bundled cuDNN shared libraries (see 3724 for the discussion). To use cuDNN features, You need to download cuDNN library using the following command: `python -m cupyx.tools.install_library --library cudnn --cuda X.X`.
It is also possible to install cuDNN v8.0.x via the system package manager (e.g., `apt install libcudnn8` or `yum install libcudnn8`) or manually install it and set `LD_LIBRARY_PATH` environment variables.


Changes without compatibility

Deprecate `cupy.sparse` package (3839, 3856)
CuPy's sparse matrix support was initially implemented in the `cupy.sparse` package. It was moved to the `cupyx.scipy.sparse` namespace in CuPy v5, while keeping the `cupy.sparse` one for backward compatibility.
Since there is no equivalent package in NumPy, it was decided that it will be deprecated and
eventually removed.

Deprecate `*_enabled` flags under `cupy.cuda` (3732)
Before it was possible to use `cupy.cuda.nccl_enabled` or similar to detect whether NCCL, cuTENSOR or other optional CUDA libraries are available to use. Now this pull-request introduced a per-module flag (`cupy.cuda.nccl.available`, `cupy.cuda.cutensor.available`) to obtain the same information.

Bump version in Docker images (3733)

The current base Docker images have been updated from Ubuntu 16.04, CUDA 9.2, and Python 3.5 to Ubuntu 18.04, CUDA 10.2, and Python 3.6.


New Features

- Add `cupy.ndim` (3060)
- Add `PythonFunctionAllocator` (3126)
- Compressed Sparse Inner Indexing (3486)
- Add `cupy.polyadd` (3548)
- Add `cupy.polymul` (3590)
- Add `cupy.polysub` (3593)
- Add most of `scipy.linalg.special_matrices` (3641)
- Add `scipy.signal` functions that are simple wrappers of `ndimage` functions (3645)
- Add `cupyx.scipy.ndimage.fourier_shift`, `fourier_gaussian`, `fourier_uniform` (3654)
- Add 2D Sparse Slicing (3657)
- Add 2D Sparse Slicing + Row Indexing (3658)
- Add 2D Sparse Slicing + Row & Column Indexing (3659)
- Add `cupy.roots` for Hermitian or symmetric matrix (3703)
- Add `cupy.polyval` (3725)
- Support `__cuda_array_interface__` in `cupy.poly1d` (3729)
- Implement library preloading for wheels (3731)
- Add `cupy.poly1d.__pow__` (3734)
- Add `scipy.signal.convolve` and `correlate` functions (3748)
- Add `trimcoef` (3793)

Enhancements

- Avoid disk I/O in compiler (3164)
- Add check for method in Randomstate seed (3282)
- Support negative `axis` in sparse `min`/`max`/`argmin`/`argmax` (3497)
- Mark `nonzero` parameters experimental in sparse `min`/`max` (3583)
- Add a `compile` method for `RawKernel` and `RawModule` (3644)
- Handle `__cuda_array_interface__` in `asnumpy` (3718)
- Use `cublasGemmEx` in `tensordot_core` when CUDA11 (3719)
- Deprecate `*_enabled` flags under `cupy.cuda` (3732)
- Fix handle types to `intptr_t` (3746)
- Support TF32 (3810)
- Deprecate `cupy.sparse` package (3839)
- Add `path` and `readonly` options to `cupyx.optimizing.optimize` (3845)
- Adding a workaround for even-length inputs to `scipy.signal.sepfir2d` (3750)
- Add multi-axis support to `cupy.flip` (3742)


Performance Improvements

- Speed up `cupy.vdot` (3678)
- Improve `cupy.cutensor` (3700)
- More improvement of `cupy.cutensor` (3744)
- Improve 2D sparse row slicing (3782)
- Improve median_filter, rank_filter and percentile_filter (3813)
- Improve CSR matrix `getrow`, `getcol` and some slicing (3851)

Bug Fixes

- Fix `float16` `ndarray` input in `histogram` with CUB (3617)
- Support order argument in `cupy.ones`, `cupy.full` and `cupy.eye` (3655)
- Work around a known CUB SpMV bug (3679)
- Fix broken message format (3691)
- Fix `can_use_device_segmented_reduce()` for incompatible axes (3740)
- Fix circular imports (3743)
- Skip FFT input checks for some CUDA >= 10.1 cases (3763)
- Fix CUDA 11 multi-GPU FFT bug (3775)
- Temporary fixes for cudnn v8 (3790)
- Fix `cupy.correlate` (3801)
- Copy input by default for C2R transform (3848)
- Fix `cupy.sparse.*` deprecation (3856)
- Fix cub not bundled in wheels (3879)
- Fix wheel not loading bundled cuDNN on Windows (3880)
- Add option to include wheel metadata (3881)
- Fix not to use `cupy.cuda.*` from CuPy codebase (3883)

Code Fixes

- Add `cupy_backends/cuda/libs/cutensor.pxd` (3595)
- Refactor `_make_decorator` in helper.py (3697)
- Refactor `cupy.poly1d` tests (3704)
- Remove unnecessary imports in `cupy._sorting` (3706)
- Rename `cupy.binary` submodule to `cupy._binary` (3707)
- Rename `cupy.creation` submodule to `cupy._creation` (3708)
- Rename `cupy.functional` submodule to `cupy._functional` (3710)
- Rename `cupy.indexing` submodule to `cupy._indexing` (3711)
- Remove unnecessary imports of `cupy.linalg` (3714)
- Rename `cupy.misc` submodule to `cupy._misc` (3726)
- Rename `cupy.padding` submodule to `cupy._padding` (3727)
- Rename submodules under `cupy.random` package (3772)
- Refactor logical routines from `core.pyx` (3804)
- Refactor binary-op routines from `core.pyx` (3816)
- Fix typo (3850)
- Resolve circular imports between `cupy` and `cupyx.scipy` (3854)

Documentation

- Correct format of docstrings in creation routines (3752)
- Update docs for v8 (3802)
- Fix a broken document (3807)
- Add `cupy-cuda110` package to README (3817)
- Fix documents to reflect `CUPY_ACCELERATORS` (3818)
- Support Optuna v2 (install docs) (3842)
- Add upgrade guide for v8 (3863)
- Fix broken link in the installation guide (3864)

Installation

- Bump version in Docker images (3733)
- Update `classifiers` in `setup.py` (3814)
- Install SciPy and Optuna to Docker image (3844)

Tests

- Fix wrong test file name (3722)
- Fix test to run without NCCL (3735)
- Avoid mutation of `os.environ` (3749)
- Relax tolerance in `TestArrayElementwiseOp::test_doubly_broadcasted_pow` (3758)
- More on using `unittest.mock` (3791)
- Fix test to run without cuDNN (3846)

Others

- Bump version to v8.0.0rc1 (3882)
- Make nvrtc `getPTX` use `bytes` instead of `unicode` (3237)
- Add hiprtc support (3238)
- Fix build and import errors for ROCm (3786)

Contributors

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

anaruse, cjnolet, coderforlife, Dahlia-Chehata, jakirkham, leofang, niteya-shah, pentschev

This is the release note of v8.0.0b5. See [here](https://github.com/cupy/cupy/milestone/76?closed=1) for the complete list of solved issues and merged PRs.

Highlights

CUB is now bundled with CuPy so that everyone can use it out-of-the-box (thanks leofang!). This release also introduces a mechanism to enable acceleration using different libraries, [`CUPY_ACCELERATORS` environment variable](https://docs.cupy.dev/en/latest/reference/environment.html). You can enable CUB and cuTENSOR by setting `export CUPY_ACCELERATORS=cub,cutensor`.

The new features include an implementation of the SciPy ndimage filters contributed by coderforlife and the introduction of the `cupy_backends` library, used to decouple the CUDA ecosystem APIs from CuPy itself.
Currently, `cupy_backends` is considered an undocumented API and it is subject to further refactoring. In the meantime, you can still continue to use [`cupy.cuda.*` APIs](https://docs.cupy.dev/en/latest/reference/cuda.html).

Changes without compatibility

Supported Platform (3670)

As announced previously, we dropped support for CUDA 8.0 and 9.1. We are also going to drop support for [NumPy 1.15](https://github.com/cupy/cupy/issues/3643) and [SciPy 1.2 or earlier](https://github.com/cupy/cupy/issues/3631) in the upcoming release.

CUB (2584, 3461, 3562)

CUB is now bundled in the source tree. As a consequence, gcc-6 or later is required for the CuPy v8 build. If you are building CuPy from source on systems with legacy gcc, follow the instructions below. *These steps are not necessary for general users using wheel packages.*


Ubuntu 16
$ sudo add-apt-repository ppa:ubuntu-toolchain-r/test
$ sudo apt-get update
$ sudo apt-get install g++-6
$ export NVCC="nvcc --compiler-bindir gcc-6"

CentOS 6 and 7:
$ sudo yum install centos-release-scl
$ sudo yum install devtoolset-7-gcc-c++
$ source /opt/rh/devtoolset-7/enable


CUB-related environment variables (`CUB_PATH`, `CUB_DISABLED`) are no longer effective. You need to enable CUB by setting `CUPY_ACCELERATORS=cub` environment variable to boost reduction kernels and several functions such as `min`, `max`, `sum`, and `scan`.

cuTENSOR (3592)

In response to the introduction of `CUPY_ACCELERATORS`, you need to explicitly specify the option `CUPY_ACCELERATORS=cutensor` to enable cuTENSOR.

Others

- Avoid early compilation when initializing a `RawModule` instance (3534)
- Remove `CHAINER_SEED` (3674)
- Remove `sum_duplicate` parameter in sparse `min`/`max`/`argmin`/`argmax` (3676)

New Features

- Support multistage reduction and indexing in `cupy.fuse` (2734, thanks xuzijian629!)
- Implementation of ndimage filters (3184, thanks coderforlife!)
- Add `cupy.convolve` (3371, thanks Dahlia-Chehata!)
- Move CUDA low-level API to `cupy_backends` namespace (3386)
- Add `choose_conv_method` (3464, thanks Dahlia-Chehata!)
- Add `cupy.poly1d` (3466, thanks Dahlia-Chehata!)
- Sparse mean (3487, thanks cjnolet!)
- Add support for `cusolverDn<t>syevj` and `cusolverDn<t>syevjBatched` (3488, thanks dmargala!)
- `ndimage` rank-based filters (3500, thanks coderforlife!)
- `ndimage` common linear filters (3505, thanks coderforlife!)
- Implement `flatiter.__iter__()` (3508)
- Implement `has_sorted_indices`, `has_canonical_format`, `sort(ed)_indices()` for sparse matrices (3509)
- Add multi-gpu support to time (3519)
- Add `cupy.correlate` (3525, thanks Dahlia-Chehata!)
- Add `cupyx.scipy.sparse.kron()` (3528)
- Support `ncclSend` / `ncclRecv` from NCCL 2.7 (3567)
- Add `cupyx.scipy.fft.next_fast_len` (3571)
- `ndimage` generic filters (3614, thanks coderforlife!)
- Support CSR matrix multiply (3647)
- Support CSR matrix division (3680)

Enhancements

- Build the `cupy.cuda.cub` module by default (2584)
- Expose cuda IPC runtime calls (3290)
- Merge `CUPY_CUB_BLOCK_REDUCTION_DISABLED` and `CUB_DISABLED` (3461)
- Support CUB histogram (3473)
- Support cuTENSOR 1.1 (3477)
- Added functionality to print nvcc and nvrtc output (3485, thanks mnicely!)
- Support `axis=None` in sparse `min`/`max` (3515)
- Small fixes for CUB block reduction kernels (3520)
- Avoid early compilation when initializing a RawModule instance (3534)
- Improve `_prepare_mask_indexing_single` (3539)
- Support batched slogdet with complex numbers (3551, thanks yoshipon!)
- Fix hip header files (3566)
- Remove `compute_30` when CUDA 11 (3578)
- Change `einsum` not to use cuTENSOR when accelerator is not set (3592)
- Update CUDA 11.0 FP16 header to production release version (11.0.2) (3668)
- Drop support for CUDA 8.0 and 9.1 (3670)
- Remove `CHAINER_SEED` (3674)

Performance Improvements

- Use cuTENSOR in `cupy.sum` (2939)
- Reduce `numpy.ndarray` creation in cuTENSOR operation preparation (3393)
- Improve scan operation (3540)
- Improve `_ArgInfo` init (3549)
- Fix small performance issue (3550)
- Improve `_fft_convolve` (3560)
- Reduce device synchronization in `poly1d` instantiation (3563, thanks Dahlia-Chehata!)
- Reuse FFT plan for `convolve`/`correlate` (3587)
- Improve efficiency of `cupy.fft.fftfreq` and `cupy.fft.rfftfreq` (3653, thanks grlee77!)

Bug Fixes

- Fix `cupyx.scipy.ndimage.sum` taking zero-dimensional input (3425)
- Use `CUSPARSE_VERSION` instead of `CUDA_VERSION` (3491)
- Fix sparse `min`/`max` to return sparse matrix (3536)
- Fix boolean indexing (3538)
- Support 0-size `ndarray` and fix possible error in `__del__` at `fft` (3543)
- Fix `cupy.percentile` type assignment in `asarray` (3570)
- Fix array creation for ndarray list of arrays of different dtypes (3605)
- Change sorting order of COO sparse matrix for cuSPARSE (3620)
- Add `__name__` to custom kernels (3626)
- Fix sparse `argmin`/`argmax` return shape (3639)
- Fix missing imports and `cupy.show_config` (3642)
- Fix sparse matrix related test failures on CUDA 11 (3649)
- Fix error message broken (3669)
- Remove `sum_duplicate` parameter in sparse `min`/`max`/`argmin`/`argmax` (3676)
- Fix broken imports for `cupy.cuda.*` (3685)
- Fix Windows build failure of cuSparse generic API (3690)
- Fix compile option on HIP environment (3604)

Code Fixes

- Use `.data()` for `std::vector` (3022)
- Add short comments for the internals (3475)
- Use absolute import (3496)
- Make type dispatcher from `cupy.cuda.cub` reusable (3546)
- Clean up CUB-related stuff (3562)
- Suppress compile warnings (3573)
- Remove unused descriptor definition (3594)

Documentation

- Add sample code for image resizing (3559, thanks pmixer!)
- Update documentation of `CUPY_ACCELERATORS` (3596)
- Update url and email (3608)
- Add a warning for `sum_duplicates` (3624)
- Remove Chainer related docs (3673)

Installation

- Add missing `cupy_cub.cu` in package data (3572)
- Fix rpath for wheel build (3689)

Tests

- Test against `scipy.fft` when available (3032)
- Add tests for `_cub_reduction` (3462)
- Add mock tests to ensure `cupy.cuda.cub` is used (3467)
- Fix to set `testing.slow` correctly (3501)
- Check NumPy compatibility in `flatiter` tests (3514)
- Fix `slogdet` tests to check dtypes of return values (3577)
- Fix negative value test in `test_helper` (3579)
- Deprecate `numpy_cupy_array_list_equal` (3582)
- Use `numpy_cupy_array_equal` instead of `numpy_cupy_array_list_equal` (3599)
- Checks return types in `testing.numpy_cupy_*` (3621)
- Add tests for sparse max with `axis=None` (3638)
- Parameterize sparse `min`/`max`/`argmin`/`argmax` tests (3656)
- Expose accelerator internal API to one level up (3664)

Others

- Fix to raise `ValueError` for invalid `order` (3498)
- Fix to raise `ValueError` for invalid clipmode (3499)
- Fix to raise `TypeError` for invalid subscripts in `einsum` (3502)
- Use builtins directly (3651, thanks larsoner!)
- Add link to Twitter account (3529)
- Update style checker version for Python 3.7 (3585)
- Bump version to v8.0.0b5 (3687)

This is the release note of v8.0.0b4. See [here](https://github.com/cupy/cupy/milestone/74?closed=1) for the complete list of solved issues and merged PRs.

Highlights

CuPy v8.0.0b4 focuses on performance improvements by adding a general CUB based reduction kernel contributed by leofang (3244). We also introduce support for the upcoming CUDA 11 (3405) although we don’t provide wheels for it yet. Last but not least, several new routines are added to improve the NumPy and SciPy functions coverage.

Changes without compatibility

Change the behavior of `dia_matrix.diagonal` to follow SciPy 1.5.0 specification. It does not raise `ValueError` for invalid values anymore. Now an empty array is returned instead. (3469)



New Features

- Add `cupy.shape` (3229)
- CUB-backed `_SimpleReductionKernel` (3244, thanks leofang!)
- Add `cupyx.scipy.ndimage` sum, mean, standard deviation and variance (3259, thanks niteya-shah!)
- Support C++ template code in `cupy.RawModule` (3319, thanks leofang!)
- Add `cupy.piecewise` (3329, thanks Dahlia-Chehata!)
- Add `cupy.trim_zeros` (3340, thanks Dahlia-Chehata!)
- Add `cupy.sort_complex` (3348, thanks Dahlia-Chehata!)
- Add `cupy.who` (3361)
- Support `cudaDeviceGetLimit` / `cudaDeviceSetLimit` (3387, thanks leofang!)
- Add `polycompanion` (3398, thanks Dahlia-Chehata!)
- Add wrappers for `cusolverDn<t>potrfBatched` and `cusolverDn<t>potrsBatched` (3399, thanks IvanYashchuk!)
- Add `polyvander` (3404, thanks Dahlia-Chehata!)
- Support CUDA 11.0 (3405)
- Add `cupy.shares_memory` (3432)
- Detect and show Thrust build version (3444, thanks leofang!)

Enhancements

- Refactor cuTENSOR handle initialization (2772)
- Deprecate `testing.numpy_cupy_raises` (3098)
- Align vector access with 3020 3022 (3228)
- Get arch per device and support CUDA 9.2+ (3366, thanks leofang!)
- Fix cuTENSOR routines to raise `ValueError` for invalid arguments (3374)
- Support `ignore_error` in kernel optimization (3410)
- Support boolean in `cupyx.scipy.ndimage` stats functions (3419)
- Raise `TypeError` in `cupy.ndarray.__array__` (3421)
- Make Optuna optional to allow import (3427)
- Implement `flatiter.copy()` (3442)

Performance Improvements

- Speed up CSR SpMV by orders of magnitude (3430, thanks leofang!)
- Index `CArray` using 32-bit indexes (3448)

Bug Fixes

- Assert that all the pointers are in the same device in `concatenate` (3285)
- Fix `_count_non_nan` datatype for windows (3350)
- Fix `cupyx.time.repeat` to accumulate duration after GPU synchronization (3375)
- Fix `PerfCaseResult` changing `_ts` (3400)
- Fix intermediate dtypes for float16 inputs in `cupyx.scipy.ndimage` stats functions (3402)
- Properly reset current stream in case null stream is destroyed (3423)
- Fix `cupy.power(0j, 0j)` (3449)
- Fix `TypeError` in parameterize test catching `CUDADriverError` (3451)
- Fix `scipy.dia_matrix.diagonal` for `scipy==1.5.0` (3469)

Code Fixes

- Fix array() for readability (2935)
- Remove unnecessary comparison in `cupy.linalg.svd` (3373)
- Fix initial values in `cupy._environment` (3413, thanks leofang!)
- Use `find_packages` in `setup.py` (3424)
- Refactor CUB-backed `_SimpleReductionKernel` (3443)

Documentation

- Add documentation for `cupyx.optimizing.optimize` (3397)
- Fix sphinx version for travis (3416)
- Document `cupy.fromfile` (3439, thanks jakirkham!)
- Fix typos in `cupy.linalg.det docstring` (3456, thanks grlee77!)
- Fix docstring of `tofile()` (3460, thanks leofang!)

Installation

- Add optuna and remove theano for doctest requirement (3446)

Tests

- Add tests for `cupy.cuda.cub` (2598, thanks leofang!)
- Remove chainercv CI configs (3055)
- Add a test to cover accepting large-size arrays via `__cuda_array_interface__` (3297, thanks leofang!)
- Add `__init__.py` to allow importing test packages (3395)
- Fix ChainerCV tests failing in master branch (3411)
- Test CUB SpMV (3428, thanks leofang!)
- Deprecate `testing.empty` (3438)
- Skip some `RawModule` tests for wrong condition (3453)
- Use `unittest.mock` (3468)

Others

- Bump version to v8.0.0b4 (3481)

This is the release note of v8.0.0b3. See [here](https://github.com/cupy/cupy/milestone/72?closed=1) for the complete list of solved issues and merged PRs.

As announced in [the previous release](https://github.com/cupy/cupy/releases/tag/v8.0.0b2), we are dropping support for CUDA 8.0 / 9.1 in v8 releases (#3301). Based on the feedback from users, we will continue to provide cuDNN support (3303).

Highlights

CuPy v8.0.0b3 introduces a mechanism for optimizing internal parameters when launching reduction kernels using [Optuna](https://optuna.org/). Depending on your GPU and the kernels you execute, you can take advantage of this feature and improve the performance of your codes by letting Optuna to automatically find the best parameters for your GPU.
To take advantage of this, call functions that perform reductions with the following:

python
with cupyx.optimizing.optimize(key=None):
cupy reduction function
y = cupy.sum(x)


CuPy is also taking part in GSoC 2020 and we keep adding new functions to improve our compatibility with NumPy.

New Features

- Optimize kernel launch parameters using Optuna (2731)
- Support cuSPARSE generic API (3242)
- Implement `flatiter.base` property (3250)
- Implement `flatiter.__len__()` special method (3251)
- Implement `flatiter.__next__()` special method (3252)
- Implement `putmask` function (3261, thanks rushabh-v!)
- Show versions of CUB and cuTENSOR on `cupy.show_config` (3271)
- Enable getting R2C/C2R FFT plans from `get_fft_plan()` (3293, thanks leofang!)
- Support surface memory in `RawKernel` (3294, thanks leofang!)
- Add `cupy.bartlett` (3307, thanks niteya-shah!)
- Add `mean` for sparse matrices (3333)
- Support `max_duration` argument in `cupyx.time.repeat` (3357)
- Support `OptimizeContext` serialization (3367)

Enhancements

- Support primitive complex scalar in `RawKernel` (2606)
- Fix the internal streams in multi-GPU Plan1d (3260, thanks leofang!)
- Support additional dtypes and axis sequences in cupy.median (3280, thanks grlee77!)
- Support multiple architectures in `CUPY_NVCC_GENERATE_CODE` (3330, thanks leofang!)
- Fix too small `max_total_time_per_trial` (3365)

Performance Improvements

- Rewrite `cupyx.scipy.ndimage.interpolation` using `ElementwiseKernel` (3166, thanks grlee77!)
- Improve `ElementwiseKernel` cpu time (3298)
- Performance improvements to `blackman`, `hanning` and `hamming` methods (3312, thanks niteya-shah!)
- Use local cache in `cupy.RawKernel` (3341, thanks leofang!)
- Reduce memory usage of `cupy.linalg.svd` (3347)

Bug Fixes

- Fix SciPy version check in `cupyx.scipy.fft` (3311, thanks grlee77!)
- Ensure runtime context on a per-device basis (3321, thanks leofang!)
- Fix `put` when using scalars (3328)
- Assign a work space to `ormqr` functions in `_solve` (3331)
- Fix `linalg.svd` for 0-sized matrices (3354)
- Fix wrong parameter names in kernel launch optimizers (3364)
- `cupy.around` behaves differently from NumPy for EVEN_NUMBER+0.5 (3335)

Code Fixes

- Add alias of shape type (3310)
- Use `shape_t` instead of `tuple` (3315)

Documentation

- Add PFN to the README (3276)
- Remove upper restrictions for numpy and scipy in doc build (3337)

Tests

- Add tests for optimizer for kernel launch parameters (3363)

Others

- Bump version to v8.0.0b3 (3376)

This is the release note of v8.0.0b2. See [here](https://github.com/cupy/cupy/milestone/70?closed=1) for the complete list of solved issues and merged PRs.

We are planning to drop support for CUDA 8.0 / 9.1 (3301) and cuDNN (3303) in future v8 releases. If you have any concerns, please feel free to leave a comment in these issues.


New Features

- Add notification support for `fallback_mode` (2279, thanks Piyush-555!)
- Support multi-GPU `cupy.cuda.cufft.Plan1d` (2644, thanks leofang!)
- Add `cupy.median` (3134, thanks Harshan01!)
- Add `cupy.flatiter` (3165)
- Add `cupy.gcd` and `cupy.lcm` (3190, thanks niteya-shah!)
- Support `cusolverDn<t>gesvdj` and `cusolverDn<t>gesvdaStridedBatched` (3192)
- Add `cupyx.scipy.ndimage.label` (3210)
- Add `cupyx.scipy.ndimage.grey_erosion` and `cupyx.scipy.ndimage.grey_dilation` (3216)
- Add `cupy.diag_indices` and `cupy.diag_indices_from` (3217, thanks rushabh-v!)
- Support `cusparse<t>csrgeam2` and `cusparse<t>csrgemm2` (3220)
- Add `minimum_filter`, `maximum_filter`, `grey_closing`, `grey_opening` to `scipy.ndimage` (3239)
- Support `cusolverDn<t>gesvdjBatched` (3247)
- Add `cupy.kaiser` (3268, thanks niteya-shah!)
- Support all dtypes in every sorting function in `cupy.cuda.thrust` (3286, thanks leofang!)

Enhancements

- Add R2C/C2R support to `cupy.cuda.cufft.PlanNd` (3102, thanks leofang!)
- Make `RawKernel` and `RawModule` aware of CUDA context (alt) (3201, thanks leofang!)
- Make `diff` return `AxisError` for an invalid axis (3231, thanks grlee77!)
- Improve the efficiency of `cupy.pad` for some simple cases (3281, thanks grlee77!)

- HIP
- Support `einsum` with complex in HIP (3203)
- Add complex support to HIP Blas (3206)

Performance Improvements

- Reduce list and tuple creation in `_kernel` and `reduction` (2702)
- Remove unnecessary `Arg` instantiation in `cuda/function.pyx` (3253)
- Improve `norm` (3278)

Bug Fixes

- Fix: n-dimensional FFTs must preserve array contiguity when copying a view (3034, thanks grlee77!)
- Use larger type to represent index range in `cupy.take` (3118)
- Fix byte buffer handling to support PyPy (3225)
- Fix `_reduce_dims` call in reduction (3262)
- Raise `IndexError` for R2C/C2R FFT with `axes=()` (3264, thanks leofang!)
- Code fix + bug fix for `cupy.cuda.thrust` (3291, thanks leofang!)

Code Fixes

- Remove `cupy/cuda/_environment.py` (3145, thanks leofang!)
- Fix `cupy.fill_diagonal` to implement with `cupy.flatiter` (3207)
- Remove unreachable code (3235)
- Refactor `__array_function__` (3236)
- Simplify `TestEigenvalue` (3288)

Documentation

- Small typo/spelling fixes (3243, thanks svlandeg!)
- Use Sphinx 2.x on Read the Docs (3272)

Tests

- Fix overfow in `matmul` test (2403)
- Add cuTENSOR test (3037)
- Rewrite some tests not use `numpy_cupy_raises` (3155)
- Rewrite tests not use `numpy_cupy_raises` (3256)

This is the release note of v8.0.0b1. See [here](https://github.com/cupy/cupy/milestone/68?closed=1) for the complete list of solved issues and merged PRs.

Known packaging issues:
* CuPy build fails when using CUDA 8.0 on Windows (3076). Due to this issue, `cupy-cuda80` wheel packages for Windows are unavailable for this version. Linux or CUDA 9.0+ users are unaffected.

Highlights

CuPy gets faster and more stable towards its v8.0.0 release. This version adds a handful of new routines, adds library wide performance improvements and corrects several bugs.

Changes without compatibility

- Removed `cupy.scatter_add`, which had been deprecated since CuPy v4. Use `cupyx.scatter_add` instead.


New Features

- Add `get_global()` to `cupy.RawModule` (2510, thanks leofang!)
- Support multi-GPU in `cupy.cuda.cufft.Plan1d` (2644, thanks leofang!)
- Add `hstack`, `vstack`, and `bmat` to `cupyx.scipy.sparse` (2665, thanks cjnolet!)
- Add `cupy.require` (3083, thanks niteya-shah!)
- Add `cupy.compress` (3103, thanks Harshan01!)
- Add `cupy.ravel_multi_index` (3104, thanks grlee77!)
- Add `cupy.extract` (3109, thanks Harshan01!)
- Add `cupy.bitwise_not` as alias to `invert` (3120, thanks Harshan01!)
- Add `cupy.argwhere` (3135, thanks rushabh-v!)
- Add `cupy.select` (3138, thanks niteya-shah!)
- Add `cupy.cuda.ExternalStream` (3141)
- Add `cupy.array_equal` (3189, thanks rushabh-v!)

Enhancements

- Add `ndarray` variants AND inplace support in `fallback_mode` (2391, thanks Piyush-555!)
- Support array-like start/stop and add `axis` argument to `linspace` (2461, thanks grlee77!)
- Add fp16 support of CUB (2600, thanks y1r!)
- Raise errors instead of assertion on array type checks (2795)
- Drop support for NumPy 1.15 or earlier (2938)
- Import `using_allocator` in `cupy.cuda` (2951, thanks jakirkham!)
- Remove `__future__` imports (2995)
- Support CUB `prod` (3067, thanks leofang!)
- Remove deprecated `cupy.scatter_add` (3074)
- Update `cupy.pad` to use `cupy.linspace` instead of `numpy.linspace` internally (3101, thanks grlee77!)
- Histogram update: support `range`, `weights` and `density` (3124, thanks grlee77!)
- Add support for `ord` = 2, -2, and 'nuc' in `cupy.linalg.norm` (3130, thanks rushabh-v!)
- Use `ElementwiseKernel` in `cupy.fill_diagonal` (3139)
- Allow `dia_matrix` creation from SciPy equivalent (3160, thanks jakirkham!)
- Add `labels` in the benchmark and add `kwargs` to `repeat` (3172, thanks rushabh-v!)
- Add `out` parameter to `cupy.concatenate` and `cupy.stack` (2983)
- Fix `reshape` to raise `ValueError` for order 'K' (3123)

Performance Improvements

- Improve cuDNN performance when using deterministic mode (1380)
- Improve performance of `cumsum` and `cumprod` (2907)
- Improve `ndimage` `convolve` and `correlate` (3179)
- Add check of `c_contiguous` when indexing `CArray` (3191)

Bug Fixes

- Fix an issue using non-existing attribute in cub.pyx (2985)
- Use `size_t nbytes` in `__cuda_array_interface__` (3009, thanks jakirkham!)
- Fix `fill_diagonal` (3011)
- Fix `cupy.random.multivariate_normal` (3018, thanks espg!)
- Use Python scalar as random seed (3054)
- Properly decrement total bytes in memory pool (3068)
- Fix condition to use slice copy in `ndarray.__setitem__` (3088)
- Fix compiler bug when building `cupy.cuda.cub` with CUDA < 9.2 (3089, thanks leofang!)
- Fix `cub_reduction` for `CUPY_CUB_MIN` and float16 arrays (3100)
- Use `time.process_time` instead of `time.clock` (3128, thanks rushabh-v!)
- Add support for 0 sized matrices in `svd` (3140, thanks rushabh-v!)
- Fix CUB-based `cupy.prod` for half precision (3148, thanks leofang!)
- Fix error type and message in `coo_matrix` (3150)
- Allow `MatDescriptor` to be pickle-able (3157, thanks jakirkham!)
- Fix `erfinv` & `erfcinv` in `cupyx.scipy.special` (3159, thanks leofang!)
- Remove some xfails in sorting tests (3167)
- Fix `Event.__del__` behavior on shutdown` (3176)
- Add the missing initialization value in the reduction test (3194, thanks leofang!)

Code Fixes

- Clean up `internal.pyx` (`get_contiguous_strides`) (1950)
- Remove custom `tempdir` context manager (3003)
- Use `intptr_t` instead of `size_t` for cuSPARSE and cuBLAS handles (3081, thanks Harshan01!)
- Use `intptr_t` for cuDNN handles (3082, thanks Harshan01!)
- Minor fix to `using_allocator` (3094)
- Remove `IndexOrValueError` (3096)
- Remove unused argument in `fill_diagonal` (3171)
- Silence sign comparison warning (cont'd) (3181, thanks leofang!)
- Avoid enum comparison (-Wenum-compare) (3182, thanks leofang!)
- Remove unused, deprecated fields from `cudaPointerAttributes` (3183, thanks leofang!)

Documentation

- Update installation guide for conda-forge (3052, thanks leofang!)
- Include `UnownedMemory` in the API docs (3086, thanks jakirkham!)
- Fix gencode example in the doc (3147, thanks leofang!)
- Document `convolve` and `correlate` (3161, thanks jakirkham!)

Examples

- Add mpi4py examples (3049, thanks leofang!)

Tests

- Added a compute capability check for testing grid sync (3051)
- Fix tolerance of fft tests (3056)
- Skip `irfft` tests for compute capability != 7 (3084)
- Rewrite tests not to use `numpy_cupy_raises` cupyx.* tests (3099)
- Rewrite manipulation tests not to use `numpy_cupy_raises` (3122)
- Remove python 2.7 builds (3162)

Others

- Add copyright notice for Random Kit (3107)
- Bump version to v8.0.0b1 (3204)