May 2019
Intermediate to advanced
452 pages
12h 16m
English
Content preview from Hands-On GPU Computing with Python
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Understanding how Anaconda works with CuPy and Numba
You must be familiar by now with the free and open source Anaconda distribution, as we have been using it for all our code examples so far. Let's further explore Anaconda and learn more about its features, especially in terms of accelerated computing. Accelerated computing in Anaconda is extremely significant in the deployment for scientific computing with Python.
So far, we covered Python programming implementations inclusive of C/C++ syntax. But from now on, it is important that we focus more on a programming implementation only with pure Python syntax, a perspective that is highly significant for maintaining a seamless programming experience with Python, irrespective of the CPU or GPU ...
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