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GTC ON-DEMAND

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Abstract:
Python language is a programming language with an increasing adoption by development community due to its fast learning curve, flexibility and ease to use and integrate with other technologies. Due to its level of abstraction, it is possible to use the same Python code on different platforms like X86, RISC and ARM. The python development community is growing fast and many community members are interested on how to start moving to GPU accelerated programming but don't know how to start and what is needed. We'll go through the steps and adoption path to start developing python solutions taking advantage of GPU acceleration, including some details, advantages and challenges for the strongest and more popular python3 modules to be used with GPUs: scikit-cuda, PyCUDA, Numba, cudamat and cupy. Some code samples and programs execution statistics will be shown as a performance analysis exercising as well.
Python language is a programming language with an increasing adoption by development community due to its fast learning curve, flexibility and ease to use and integrate with other technologies. Due to its level of abstraction, it is possible to use the same Python code on different platforms like X86, RISC and ARM. The python development community is growing fast and many community members are interested on how to start moving to GPU accelerated programming but don't know how to start and what is needed. We'll go through the steps and adoption path to start developing python solutions taking advantage of GPU acceleration, including some details, advantages and challenges for the strongest and more popular python3 modules to be used with GPUs: scikit-cuda, PyCUDA, Numba, cudamat and cupy. Some code samples and programs execution statistics will be shown as a performance analysis exercising as well.  Back
 
Topics:
HPC and AI, Tools & Libraries, Programming Languages
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8214
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