
layout: blog_detail
title: "PyTorch Trace Analysis for the Masses"
author: Anupam Bhatnagar, Xizhou Feng,  Brian Coutinho, Yifan Liu, Sung-Han Lin, Louis Feng, and Yuzhen Huang

We are excited to announce the public release of Holistic Trace Analysis (HTA), an open source performance analysis and visualization Python library for PyTorch users. HTA takes as input Kineto traces collected by the PyTorch profiler, which are complex and challenging to interpret, and up-levels the performance information contained in these traces. It was initially developed internally at Meta to understand and debug performance problems for large-scale distributed training jobs on GPUs. The multidisciplinary team has made a number of enhancements to HTA’s features and scaled them to support state-of-the-art ML workloads.