<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Performance Modeling | Mingkai Zheng's Homepage</title><link>https://zhengmk.github.io/tag/performance-modeling/</link><atom:link href="https://zhengmk.github.io/tag/performance-modeling/index.xml" rel="self" type="application/rss+xml"/><description>Performance Modeling</description><generator>Wowchemy (https://wowchemy.com)</generator><language>en-us</language><lastBuildDate>Wed, 17 Dec 2025 00:00:00 +0000</lastBuildDate><image><url>https://zhengmk.github.io/media/icon_hu0158c3d4eaa2a6b730ca31a67c18838d_142122_512x512_fill_lanczos_center_2.png</url><title>Performance Modeling</title><link>https://zhengmk.github.io/tag/performance-modeling/</link></image><item><title>Efficient Fine-Grained GPU Performance Modeling for Distributed Deep Learning of LLM</title><link>https://zhengmk.github.io/publication/efficient-fine-grained-gpu-performance-modeling-for-distributed-deep-learning-of-llm/</link><pubDate>Wed, 17 Dec 2025 00:00:00 +0000</pubDate><guid>https://zhengmk.github.io/publication/efficient-fine-grained-gpu-performance-modeling-for-distributed-deep-learning-of-llm/</guid><description/></item></channel></rss>