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September 18-19, 2024
San Francisco, California
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Note: The schedule is subject to change.

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Thursday September 19, 2024 5:05pm - 5:15pm PDT
PyTorch/XLA recently launched the new PyTorch/XLA SPMD feature as a first-step to automate ML workloads parallelization using GSPMD. It turns out that the performance largely depends on the quality of sharding hints provided by the user – and it requires a correct and deep understanding of model architectures and much expertise to come up with optimal sharding hints. To address this problem, we propose to integrate PyTorch/XLA SPMD with XLA's auto sharding service that allows the XLA compiler to shard and optimize the whole model without any user input.
Speakers
avatar for Yeounoh Chung

Yeounoh Chung

Software Engineer, Google
SystemsResearch@Google
Thursday September 19, 2024 5:05pm - 5:15pm PDT
Room A

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