8 Advanced parallelization - Deep Learning with JAX

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Descrição

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
Intro to JAX for Machine Learning, by Khang Pham
8 Advanced parallelization - Deep Learning with JAX
Efficiently Scale LLM Training Across a Large GPU Cluster with
8 Advanced parallelization - Deep Learning with JAX
Lecture 2: Development Infrastructure & Tooling - The Full Stack
8 Advanced parallelization - Deep Learning with JAX
Tutorial 2 (JAX): Introduction to JAX+Flax — UvA DL Notebooks v1.2
8 Advanced parallelization - Deep Learning with JAX
Learn JAX in 2023: Part 2 - grad, jit, vmap, and pmap
8 Advanced parallelization - Deep Learning with JAX
Learn JAX in 2023: Part 2 - grad, jit, vmap, and pmap
8 Advanced parallelization - Deep Learning with JAX
Build a Transformer in JAX from scratch
8 Advanced parallelization - Deep Learning with JAX
8 Advanced parallelization - Deep Learning with JAX
8 Advanced parallelization - Deep Learning with JAX
Compiler Technologies in Deep Learning Co-Design: A Survey
8 Advanced parallelization - Deep Learning with JAX
High-Performance LLM Training at 1000 GPU Scale With Alpa & Ray
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