This is the release note of v5.0.0b4. See here for the complete list of solved issues and merged PRs.

Highlights

• CuPy starts supporting __cuda_array_interface__, which is the CUDA array interchange interface compatible with Numba>=0.39.0. It means you can now pass CuPy arrays to kernels JITed with Numba. The folowing is a simple example code borrowed from numba/numba#2860:

import cupy
from numba import cuda

@cuda.jit
def add(x, y, out):
    start = cuda.grid(1)
    stride = cuda.gridsize(1)
    for i in range(start, x.shape[0], stride):
        out[i] = x[i] + y[i]

a = cupy.arange(10)
b = a * 2
out = cupy.zeros_like(a)

print(out)  # => [0 0 0 0 0 0 0 0 0 0]

add[1, 32](a, b, out)

print(out)  # => [ 0  3  6  9 12 15 18 21 24 27]

• Improved performance.
• Implemented cumsum and cumprod to ndarray.
• Implemented cupy.allclose
• Enhanced cuDNN RNN functionality including FP16 support.

New Features

• Implement __cuda_array_interface__ (#1144, thanks @seibert!)
• Support FP16 and FP64 in cuDNN RNN related functions (#1471)
• Implement <t>tpttr and <t>trttp of cuBLAS (#1492)
• Add cumsum and cumprod to ndarray (#1500)
• Add cupyx.scipy.get_array_module (#1513)
• Implement cupy.allclose (#1522, thanks @tsurumeso!)
• Add mem_info to Device (#1538, thanks @larsoner!)

Enhancements

• Avoid keeping Device object in Memory and MemoryPointer (#946)
• Speed up ElementwiseKernel launch (#1318)
• Improve memory allocation performance (#1343)
• Fix styles for latest autopep8 (#1352)
• Use CScalar in elementwise and reduction (#1447)
• Define ndarray.__iter__ (#1449)
• Move cupy.sparse to cupyx.scipy.sparse (#1451)
• Support negative indices in array_split (#1454)
• Avoid collections.sequence (#1456)
• Avoid variable name l to follow pep8 (#1460)
• Simplify nonzero function (#1487)
• Use TensorCore for matmul with fp32 matrixes (#1493)
• Support nonzero for complex types (#1501)
• Change type checking rules of Fusion ufuncs (#1507)
• Fix minor issues on coding style (#1509)
• Fix errors in NumPy 1.15 (#1514)
• Use collections.abc to avoid DeprecationWarning in Python 3.7 (#1515)
• Support loop_prep in ufunc (#1537)
• Add _has_memory_hooks to avoid thread local dictionary operation (#1540)
• Add specialized CUDA kernel for fill function (#1541)
• Improve ndarray creation performance (#1542)
• Use xorshift128 to reduce global memory access (#1546)
• Add cdef and cpdef for better cythonize core.pyx (#1548)

Bug Fixes

• Fix errors on 0-sized inputs (#1459)
• Use cython.no_gc to avoid memory leak (#1463)
• Fix cupy.random.dirichlet to behave same as numpy.random.dirichlet (#1468)
• Fix indexing behavior when input is zero-sized array (#1503)
• Fix cupy.real and cupy.imag (#1504)
• Avoid compile error in old GCC (CentOS 6) (#1506)
• Fix thrust memory allocation problem (#1511)
• Fix dtype order of create_comparison (#1551)
• Raise error when trying to broadcast out_params in ElementwiseKernel (#1552)

Documentation

• Add upgrade guide for cupyx namespaces (#1467)
• Fix docstring about free_all_free (#1519)
• Update agnostic code tutorial (#1521, thanks @w-m!)

Tests

• Fix sparse test (#1452)
• Avoid hacking: Use the same test settings as Chainer (#1477)