[{"data":1,"prerenderedAt":48},["ShallowReactive",2],{"rendered-post-b353fa5f":3},{"abbrlink":4,"title":5,"date":6,"categories":7,"tags":9,"excerpt":11,"htmlChunkEnds":12,"toc":14,"htmlGzip":47},"b353fa5f","论文阅读: Horovod: fast and easy distributed deep learning in TensorFlow","2023-09-17",[8],"懵逼的深度学习",[10],"分布式训练框架","摘要 最近忙实习去了，断更大半年。整理了一下论文，有十几篇没读，后面有时间慢慢更。 这篇论文主要工作是对 TensorFlow 框架 API 的重写，使用 ring-allreduce 和 broadcast 方法，进行数据并行。",[13],4396,[15,19,22,26,29,32,35,38,41,44],{"id":16,"text":17,"html":17,"level":18},"post-heading-摘要","摘要",2,{"id":20,"text":21,"html":21,"level":18},"post-heading-背景","背景",{"id":23,"text":24,"html":24,"level":25},"post-heading-tensorflow-不足","TensorFlow 不足",3,{"id":27,"text":28,"html":28,"level":25},"post-heading-leveraging-a-different-type-of-algorithm","Leveraging a different type of algorithm",{"id":30,"text":31,"html":31,"level":18},"post-heading-horovod","Horovod",{"id":33,"text":34,"html":34,"level":25},"post-heading-使用方法","使用方法",{"id":36,"text":37,"html":37,"level":25},"post-heading-horovod-timeline","Horovod Timeline",{"id":39,"text":40,"html":40,"level":25},"post-heading-tensor-fusion","Tensor Fusion",{"id":42,"text":43,"html":43,"level":18},"post-heading-horovod-benchmarks","Horovod 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