<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Parallelism on Rik Kisnah - Blog</title><link>https://www.rik-kisnah.ai/tags/parallelism/</link><description>Recent content in Parallelism on Rik Kisnah - Blog</description><generator>Hugo</generator><language>en</language><lastBuildDate>Tue, 15 Sep 2020 09:00:00 -0700</lastBuildDate><atom:link href="https://www.rik-kisnah.ai/tags/parallelism/feed.xml" rel="self" type="application/rss+xml"/><item><title>Data, Model, and Pipeline Parallelism</title><link>https://www.rik-kisnah.ai/teach/gpu-ai/data-model-and-pipeline-parallelism/</link><pubDate>Tue, 15 Sep 2020 09:00:00 -0700</pubDate><guid>https://www.rik-kisnah.ai/teach/gpu-ai/data-model-and-pipeline-parallelism/</guid><description>Three ways to split a job that is too big for one GPU. Split the data, split the model&amp;rsquo;s layers across machines, or split each layer across machines. Each one puts a different kind of traffic on the network, and that decides your cluster design.</description></item></channel></rss>