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Caching for pycuda kernels? #388

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daurer opened this issue Feb 15, 2022 · 2 comments
Open

Caching for pycuda kernels? #388

daurer opened this issue Feb 15, 2022 · 2 comments
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0.9 High-performance for entire framework GPU acceleration

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daurer commented Feb 15, 2022

It currently takes up to a minute for the JIT compilation of all the kernels, this is often longer than the actual reconstruction time.

  • Investigate where the time is lost (compilation vs. mem alloc)
  • Maybe we can cache the compiled kernels somewhere (e.g. home folder, recons folder)
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daurer commented Jan 17, 2023

use ENV to overwrite default CACHE_DIR to user defined location and skip cleaning up of compiled kernels

@daurer daurer self-assigned this Jan 24, 2023
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daurer commented Feb 1, 2024

With the CuPy engines, the JIT is significantly faster and no problem really going forward if we transition towards mostly using CuPy engines for HPC

Maybe we can close this issue?

@daurer daurer added 0.9 High-performance for entire framework and removed 0.8 labels Feb 1, 2024
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