kmaehashi

5 ms·

1.
by kmaehashi 2mo ago
Preferred Networks | Tokyo or Remote in Japan | Full-time | https://www.preferred.jp/en Preferred Networks is an AI company based in Tokyo working across the stack, from AI chips and computing infrastructure to LLMs and pro
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by kmaehashi 3mo ago
Preferred Networks | Tokyo or Remote in Japan | Full-time | https://www.preferred.jp/en Preferred Networks is an AI company based in Tokyo working across the stack, from AI chips and computing infrastructure to LLMs and pro
3.
by kmaehashi 5mo ago
Preferred Networks | Tokyo or Remote in Japan | Full-time | https://www.preferred.jp/en Preferred Networks is an AI company based in Tokyo working across the stack, from AI chips and computing infrastructure to LLMs and pro
4.
by kmaehashi 2y ago
CuPy isn't semi-abandoned as well, obviously :)
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by kmaehashi 2y ago
As a maintainer of CuPy and also as a user of several GPU-powered Python libraries, I empathize with the frustrations and difficulties here. Indeed, one thing CuPy values is to make the installation step as easy and universal as possible. W
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by kmaehashi 2y ago
NumPy has a mechanism to dispatch execution to CuPy: https://numpy.org/neps/nep-0018-array-function-protocol.html Just prepare the input on NumPy or CuPy, and then you can just feed it to NumPy APIs. NumPy functions wi
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by kmaehashi 2y ago
cuDF is a CuPy-based library providing drop-in replacement for Pandas: https://rapids.ai/
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by kmaehashi 2y ago
Actually all CUDA Toolkit libs are already available through the conda-forge channel: https://anaconda.org/conda-forge/cuda-cudart , https://anaconda.org/conda-forge/libcublas , etc.
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by kmaehashi 2y ago
CuPy tensors (or `ndarray`) provide the same semantics as NumPy. In-place operations are permitted.
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by kmaehashi 2y ago
For those interested in the NumPy/SciPy API coverage in CuPy, here is the comparison table: https://docs.cupy.dev/en/latest/reference/comparison.html
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by kmaehashi 2y ago
An excellent example of Array API usage can be found in scikit-learn. Estimators written in NumPy are now operable on various backends courtesy of Array API compatible libraries such as CuPy and PyTorch. https://scikit-learn.org&