8 Advanced parallelization - Deep Learning with JAX

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Using easy-to-revise parallelism with xmap() · Compiling and automatically partitioning functions with pjit() · Using tensor sharding to achieve parallelization with XLA · Running code in multi-host configurations
8 Advanced parallelization - Deep Learning with JAX
Learning local equivariant representations for large-scale
8 Advanced parallelization - Deep Learning with JAX
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8 Advanced parallelization - Deep Learning with JAX
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8 Advanced parallelization - Deep Learning with JAX
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8 Advanced parallelization - Deep Learning with JAX
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8 Advanced parallelization - Deep Learning with JAX
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8 Advanced parallelization - Deep Learning with JAX
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8 Advanced parallelization - Deep Learning with JAX
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8 Advanced parallelization - Deep Learning with JAX
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8 Advanced parallelization - Deep Learning with JAX
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8 Advanced parallelization - Deep Learning with JAX
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8 Advanced parallelization - Deep Learning with JAX
Lecture 2: Development Infrastructure & Tooling - The Full Stack
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