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SUMMARY:KSVD.jl: A case study in performance optimization. - Romeo Valenti
 n
DTSTART;TZID=Europe/Amsterdam:20240710T163000
DTEND;TZID=Europe/Amsterdam:20240710T164000
DTSTAMP:20260819T235154Z
UID:pretalx-juliacon2024-V8VGK9@pretalx.com
DESCRIPTION:We present `KSVD.jl`\, an extremely fast implementation of the
  K-SVD algorithm\, including extensive single-core optimizations\, shared-
 state multithreading\, pipelined GPU offloading\, and an optional distribu
 ted executor. With this implementation\, we are able to outperform existin
 g numpy-based implementations by ~100x and scale to datasets with millions
  of samples.
LOCATION:Function (4.1)
URL:https://pretalx.com/juliacon2024/talk/V8VGK9/
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