9 Data analysis using GPU computing
This chapter covers
- Using GPU architectures to improve many data analysis algorithms
- Using Numba to convert Python code to efficient GPU low-level code
- Writing highly parallel GPU code to work on matrices
- Using GPU-native data analysis libraries from Python
Graphics processing units (GPUs) were originally designed to make graphics applications more efficient: drawing and animation software, computer-aided design, and, of course, games!
At some point, it became clear that GPUs could not only do graphics processing but could also be used to do all kinds of computing, hence the appearance of general-purpose computing on graphics processing units (GPGPUs). GPUs are attractive because they have substantially more ...
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