November 2018
Intermediate to advanced
310 pages
7h 54m
English
Content preview from Hands-On GPU Programming with Python and CUDA
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To get the most out of this book
This is actually quite a technical subject. To this end, we will have to make a few assumptions regarding the reader's programming background. To this end, we will assume the following:
- You have an intermediate level of programming experience in Python.
- You are familiar with standard Python scientific packages, such as NumPy, SciPy, and Matplotlib.
- You have an intermediate ability in any C-based programming language (C, C++, Java, Rust, Go, and so on).
- You understand the concept of dynamic memory allocation in C (particularly how to use the C malloc and free functions.)
GPU programming is mostly applicable to fields that are very scientific or mathematical in nature, so many (if not most) of the examples ...
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