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Hands-On GPU Programming with Python and CUDA
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Build real-world applications with Python 2.7, CUDA 9, and CUDA 10. We suggest the use of Python 2.7 over Python 3.x, since Python 2.7 has stable support across all the libraries we use in this book.
- Expand your background in GPU programming—PyCUDA, scikit-cuda, and Nsight
- Effectively use CUDA libraries such as cuBLAS, cuFFT, and cuSolver
- Apply GPU programming to modern data science applications
Hands-On GPU Programming with Python and CUDA hits the ground running: you’ll start by learning ...
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