Hands-On GPU Programming with Python and CUDA: Explore high-performance parallel computing with CUDA-P2P
Build GPU-accelerated high performing applications with Python 2.7, CUDA 9, and open source libraries such as PyCUDA and scikit-cuda. We recommend the use of Python 2.7 as this version has stable support across all libraries used in this book.

Hands-On GPU Programming with Python and CUDA: Explore high-performance parallel computing with CUDA-P2P
English | Nov 2018 | ISBN-13: 978-1788993913 | 310 Pages | True (PDF, EPUB, MOBI) + Code | 40.67 MB
NITROFLARE – RAPIDGATOR – NTi

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