Core idea is think about backward pass into two flows, one to compute grad wrt to parameters, and one to compute grad wrt to output of last layer, 
schedule so that you are always working instead of waiting (bubble).

Read full paper: https://arxiv.org/abs/2401.10241

Tags: Systems and Performance, Deep Learning, Machine Learning

Core idea is think about backward pass into two flows, one to compute grad wrt to parameters, and one to compute grad wrt to output of last layer, schedule so that you are always working instead of waiting (bubble). Read full paper: https://arxiv.org/abs/2401.10241 Tags: Systems and Performance, Deep Learning, Machine Learning

Zero Bubble Pipeline Parallelism

Byte-Sized Breakthroughs offers concise audio summaries of recent AI research papers. Each episode breaks down a single paper in areas like machine learning, computer vision, or natural language processing, making it easier to stay current with AI advancements.

The podcast covers topics such as large language models, mechanistic interpretability, and in-context learning. Episodes feature clear explanations of complex concepts, designed for efficient listening.

Ideal for researchers, engineers, and AI enthusiasts with limited time, Byte-Sized Breakthroughs provides a starting point for exploring cutting-edge AI research. While offering overviews, listeners are encouraged to refer to original papers for comprehensive understanding.

Curated by Arjun Srivastava, an engineer in the field, this podcast transforms spare moments into opportunities for learning about the latest in AI. Note: The voices you hear are not real people, but the content is carefully curated and reviewed.

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Byte-Sized Breakthroughs offers concise audio summaries of recent AI research papers. Each episode breaks down a single paper in areas like machine learning, computer vision, or natural language processing, making it easier to stay current with AI advancements. The podcast covers topics such as large language models, mechanistic interpretability, and in-context learning. Episodes feature clear explanations of complex concepts, designed for efficient listening. Ideal for researchers, engineers, and AI enthusiasts with limited time, Byte-Sized Breakthroughs provides a starting point for exploring cutting-edge AI research. While offering overviews, listeners are encouraged to refer to original papers for comprehensive understanding. Curated by Arjun Srivastava, an engineer in the field, this podcast transforms spare moments into opportunities for learning about the latest in AI. Note: The voices you hear are not real people, but the content is carefully curated and reviewed.

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Zero Bubble Pipeline Parallelism

Zero Bubble Pipeline Parallelism