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CUDA graph trees

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Manage episode 408615350 series 2921809
Indhold leveret af PyTorch, Edward Yang, and Team PyTorch. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af PyTorch, Edward Yang, and Team PyTorch eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.
CUDA graph trees are the internal implementation of CUDA graphs used in PT2 when you say mode="reduce-overhead". Their primary innovation is that they allow the reuse of memory across multiple CUDA graphs, as long as they form a tree structure of potential paths you can go down with the CUDA graph. This greatly reduced the memory usage of CUDA graphs in PT2. There are some operational implications to using CUDA graphs which are described in the podcast.
  continue reading

82 episoder

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CUDA graph trees

PyTorch Developer Podcast

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Manage episode 408615350 series 2921809
Indhold leveret af PyTorch, Edward Yang, and Team PyTorch. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af PyTorch, Edward Yang, and Team PyTorch eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.
CUDA graph trees are the internal implementation of CUDA graphs used in PT2 when you say mode="reduce-overhead". Their primary innovation is that they allow the reuse of memory across multiple CUDA graphs, as long as they form a tree structure of potential paths you can go down with the CUDA graph. This greatly reduced the memory usage of CUDA graphs in PT2. There are some operational implications to using CUDA graphs which are described in the podcast.
  continue reading

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