Supercharge ML performance on xPUs with the new XProf profiler and Cloud Diagnostics XProf library

Are you spending more time debugging ML model performance than you are building? You're not alone. In today's fast-paced AI landscape, optimizing models is a complex challenge, from navigating new model architectures to dealing with the ever-changing hardware and software stacks. Even at Google, where we optimize models for products like Gemini, Search, and YouTube, we've faced these exact challenges.

That's why we're providing a key tool to the community from our internal toolbox: XProf, our core ML profiler. In this post, we'll show you how to use this powerful tool and the new Cloud Diagnostics XProf library to easily identify model bottlenecks, find hidden opportunities for optimization, and get back to what you do best: innovating.

Updated XProf

A few years ago, we released a fork of our XProf tool as open source called "TensorFlow profiler", accessible through TensorBoard as “tensorboard_plugin_profile”, which many ...