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论文与代码阅读笔记
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论文与代码阅读笔记
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论文与代码阅读笔记 文章 29 标签 34 Home Archives Tags 论文与代码阅读笔记 搜索 Home Archives Tags 论文与代码阅读笔记 Resources for Machine Learning System 置顶 | 发表于 2021-03-02 | 更新于 2023-03-03 | 集群调度 • 分布式训练 • 机器学习系统 • 深度学习框架 总结机器学习系统领域的学习资源，以及值得关注和阅读的paper，主要涉及分布式深度学习、集群调度等。 每天一个没用的代码小技巧 置顶 | 发表于 2022-01-10 | 更新于 2023-07-12 一些小技巧、小方法的合集。每天一个小技巧，效率翻倍！ DistFlashAtten：面向长上下文大语言模型训练的内存高效的分布式注意力机制 发表于 2024-05-31 | 更新于 2024-06-09 本文介绍了一种名为DistFlashAttn的分布式内存高效注意力机制，它是为了优化长上下文大型语言模型（LLMs）的训练而设计的。文章提出了三种关键技术：token级别的工作负载平衡、交叠的键值通信，以及重计算梯度检查点算法。这些技术使得DistFlashAttn能够在多设备上高效地分发token块，同时保持内存高效注意力的I/O感知优势。 BPipe: 面向大语言模型训练的内存均衡的流水线并行 发表于 2023-09-25 | 更新于 2023-09-27 | 分布式训练 • 机器学习系统 • ICML • 大模型 流水线并行是在GPU集群中训练大型语言模型的关键技术。然而，流水线并行通常会导致内存不平衡问题，某些GPU的内存压力很大，而其他GPU则没有充分利用其内存。这种不平衡会影响训练性能。为了解决这种低效性，BPIPE在流水线并行中实现内存平衡。BPIPE在训练期间在GPU之间传输中间激活值，使所有GPU都能利用相当大小的内存。通过平衡内存利用率，BPIPE消除冗余重新计算或增加微批大小，从而提高GPT-3等大型语言模型的训练效率。 Lucid：一个可扩展、可解释的实用型深度学习作...
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