Hopefully the previous articles covering linear layout concepts and examples facilitate building a solid understanding of the core generic layer powering various Triton code generation lowering and optimizations. Now let’s turn our focus to those bespoke layouts, which we still consistently interact with when working on Triton compiler internals. Additionally, developers can directly program layouts with Gluon now; writing those bespoke layouts is generally more intuitive than linear layouts.

The previous blog post talked about Triton linear layout concepts, aiming to provide some underlying motivations and an intuitive understanding. As a companion, in this one I’d like to touch on linear layout internals and follow up with some concrete examples to show its usage in action and make it even more comprehensible. Following the same vein, common languages and explanations are preferred instead of mathematical terms and interpretations.

Layout is a core concept in Triton for representing and optimizing distribution mappings from source problems to the target hardware compute and memory hierarchy. In this blog post I will talk about linear layout in Triton, the new unifying mechanism over existing bespoke layouts for different purposes. The aim is to provide motivation and an intuitive understanding of linear layout; I will rely on examples and illustrations instead of theories and proofs.

Triton provides an elegant solution to program GPU kernels in Python, positioning itself as a critical component in the modern AI software stack. To deliver performance and portability, it leverages a compiler, the capability of which determines the potential. Hacking the compiler internals is not a simple task. Here are some tips hopefully useful to folks. I’ll try to keep this blog post updated periodically.

Time flies—almost 9 years have passed since I joined Google. Now the time has come for me to leave and move on. While here, I’m super lucky to mostly work on open source projects that I can publicly talk about. So at the end of my tenure with Google, I’d like to reflect and summarize the incredible journey, which I am super grateful for and thoroughly enjoyed, before I forget some details.