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GPU Acceleration in Python

We'll step through the process of migrating code from native Python to Numba, and then to a CuPy Raw Kernel (CUDA C++). Basic workflow, best practices, lessons learned, and coding samples will be provided. NVIDIA Nsight Systems profilers will be used to demonstrate how minor optimizations can provide substantial performance benefits to custom developed code. The techniques discussed in this session can be used in any domain.
Recorded Feb 16 2021 59 mins
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Presented by
Matthew Nicely, Math Libraries Product Manager, NVIDIA
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  • GPU Acceleration in Python Recorded: Feb 16 2021 59 mins
    Matthew Nicely, Math Libraries Product Manager, NVIDIA
    We'll step through the process of migrating code from native Python to Numba, and then to a CuPy Raw Kernel (CUDA C++). Basic workflow, best practices, lessons learned, and coding samples will be provided. NVIDIA Nsight Systems profilers will be used to demonstrate how minor optimizations can provide substantial performance benefits to custom developed code. The techniques discussed in this session can be used in any domain.
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  • Title: GPU Acceleration in Python
  • Live at: Feb 16 2021 5:00 pm
  • Presented by: Matthew Nicely, Math Libraries Product Manager, NVIDIA
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