<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Systems on Harvard Systems Group</title><link>https://systems.seas.harvard.edu/tags/systems/</link><description>Recent content in Systems on Harvard Systems Group</description><generator>Hugo</generator><language>en</language><copyright>Copyright © 2026 The President and Fellows of Harvard College</copyright><lastBuildDate>Tue, 28 Jul 2026 11:00:00 -0400</lastBuildDate><atom:link href="https://systems.seas.harvard.edu/tags/systems/index.xml" rel="self" type="application/rss+xml"/><item><title>Why FIFO is (almost) all you need for cache eviction</title><link>https://systems.seas.harvard.edu/blog/fifo-is-all-you-need/</link><pubDate>Tue, 28 Jul 2026 11:00:00 -0400</pubDate><guid>https://systems.seas.harvard.edu/blog/fifo-is-all-you-need/</guid><description>&lt;p&gt;Cache eviction is usually presented as a ranking problem. LRU ranks objects by
recency. LFU ranks them by frequency. More advanced algorithms combine several
signals, adapt their parameters, and maintain increasingly sophisticated data
structures to decide which object is least valuable.&lt;/p&gt;</description></item><item><title>MorphServe: Making Model Precision Elastic for Bursty LLM Serving</title><link>https://systems.seas.harvard.edu/blog/make-model-precision-elastic/</link><pubDate>Mon, 27 Jul 2026 11:30:00 -0400</pubDate><guid>https://systems.seas.harvard.edu/blog/make-model-precision-elastic/</guid><description>&lt;p&gt;Most LLM servers treat a deployed model as fixed: its weights have one
precision, its KV cache has one memory budget, and both remain unchanged until
the process restarts.&lt;/p&gt;</description></item></channel></rss>