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Python wrapper for Nvidia CUDA

Project description

PyCUDA lets you access Nvidia’s CUDA parallel computation API from Python. Several wrappers of the CUDA API already exist-so what’s so special about PyCUDA?

https://badge.fury.io/py/pycuda.png
  • Object cleanup tied to lifetime of objects. This idiom, often called RAII in C++, makes it much 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.
  • Convenience. Abstractions like pycuda.driver.SourceModule and pycuda.gpuarray.GPUArray make CUDA programming even more convenient than with Nvidia’s C-based runtime.
  • Completeness. PyCUDA puts the full power of CUDA’s driver API at your disposal, if you wish. It also includes code for interoperability with OpenGL.
  • Automatic Error Checking. All CUDA errors are automatically translated into Python exceptions.
  • Speed. PyCUDA’s base layer is written in C++, so all the niceties above are virtually free.
  • Helpful Documentation and a Wiki.

Relatedly, like-minded computing goodness for OpenCL is provided by PyCUDA’s sister project PyOpenCL.

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This version
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2017.1.1

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2017.1

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2016.1.2

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2016.1.1

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2016.1

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2015.1.3

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2015.1.2

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2015.1.1

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2015.1

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2014.1

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2013.1.1

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2013.1

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2012.1

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2011.2.2

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2011.2.1

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2011.2

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2011.1.2

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2011.1.1

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2011.1

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0.94.2

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0.94.1

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0.94

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0.94rc

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0.93.1rc2

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0.93.1rc1

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0.93

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0.93rc4

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0.93rc3

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0.93rc2

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0.93rc1

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0.92

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0.92rc

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0.91.1

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0.91

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0.91rc3

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0.91rc

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0.90.2

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0.90.1

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0.90

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