PyTorch: Matrix Math Gets a Speed Boost

Today's PyTorch development brings exciting performance improvements with a new Triton matrix multiplication template that delivers 10% faster performance on AMD GPUs. The team also made infrastructure upgrades for better CI support and applied smart optimizations to reduce unnecessary object copying throughout the codebase.

Duration: PT4M13S

Episode overview

This episode is a short developer briefing from PyTorch.

It explains recent repository work in plain language.

  • Show: PyTorch
  • Published: 2026-03-23T10:01:13Z
  • Audio duration: PT4M13S

Transcript excerpt

This excerpt keeps the crawler page concise. Listen to the episode or use the RSS feed for the full update.

Hey everyone, and welcome back to another episode of the PyTorch podcast! I'm your host, and it's March 23rd, 2026. Grab your favorite morning beverage because we've got some really exciting developments to dive into today.

You know what I love about today's activity? It's one of those days where the PyTorch team is firing on all cylinders - we're seeing performance improvements, infrastructure upgrades, and those delightful little optimizations that make everything just a bit snappier. No merged pull requests today, but we've got 23…

Let's start with the star of the show - Corbin Robeck just landed something pretty special. They've added a new non-TMA persistent matrix multiplication Triton template specifically for max-autotune. Now, if you're thinking "what does that mean for me?" - here's the beautiful part: this change is delivering around…

What makes this particularly elegant is that it brings persistent-kernel-style matrix multiplication to platforms that don't have TMA support. It's like the team looked at AMD GPU users and said, "Hey, you deserve that same performance boost too." The testing happened on an AMD 350 machine, and those performance…

Speaking of infrastructure…

Now…

Nearby episodes from PyTorch

  1. Fixes, Reverts, and Moving Forward
  2. The Infrastructure Acceleration Edition
  3. Lanczos Interpolation Breakthrough
  4. Stream Management Mastery & RNG Fixes
  5. Under the Hood Improvements and Future-Proofing
  6. Complex Math Gets Smarter & Build Improvements
  7. Memory Optimization Revolution
  8. Testing Gets Smarter and Graphs Go Universal