May 2019
Intermediate to advanced
452 pages
12h 16m
English
Content preview from Hands-On GPU Computing with Python
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PyCUDA
Programming on Python with PyCUDA requires you to have knowledge of basic CUDA-C programming skills in order to harness NVIDIA GPU devices. PyCUDA provides the following benefits:
- It is easier to write correct, leak, and crash-free code. PyCUDA knows about dependencies too, so (for example) it won't detach from a context before all memory allocated in it is also freed.
- Abstractions such as pycuda.driver.SourceModule and pycuda.gpuarray.GPUArray make CUDA programming even more convenient than with NVIDIA's C-based runtime.
- PyCUDA puts the full power of CUDA's driver API at your disposal, if you wish. This also includes code for interoperability with OpenGL.
- All CUDA errors are automatically translated into Python exceptions.
- PyCUDA's ...
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