Productively Programming Accelerated Computing Systems
Rohan Yadav (Stanford University)
Colloquium
Tuesday, February 17, 2026, 3:30 pm
Gates Center (CSE2), G20 | Amazon Auditorium
Abstract
Modern accelerated computing systems are increasing in scale, becoming more specialized and diverse, and evolving more quickly. While these changes bring significant performance improvements, they also come with the challenges of productively developing software that targets complex and rapidly changing hardware. For software to keep up with modern hardware, programming systems must also evolve to provide new levels of abstraction, portability and composability. In this talk, I will focus on two pieces of work that advance programming systems along these axes.
First, I will discuss a connection between actor-based and task-based programming models, two popular classes of programming models for distributed and accelerated machines. Task-based models provide high-level abstractions over the underlying hardware that enable composability and portability, while actor-based models expose a lower-level interface that offers the best performance. I will show that these two families of programming models are duals of each other, and then leverage this duality to close the performance gap between the models by compiling task-based programs into efficient actor-based programs.
Second, I will discuss Twill, a system that automatically discovers optimal software pipelining (SWP) and warp specialization (WS) strategies for Tensor Core GPUs. Optimal strategies for SWP and WS continue to change across modern GPU generations and are currently derived through expert intuition and compiler heuristics. We show that these strategies are derivable from first-principles in a machine-parametrizable and heuristic-free manner, and re-discover strategies found by experts.
Bio
Rohan Yadav is a final-year computer science Ph.D. student at Stanford University, advised by Alex Aiken and Fredrik Kjolstad, as well as a part-time researcher at NVIDIA. He is generally interested in programming languages and computer systems, with a focus in systems for parallel and accelerated computing.
This talk will be streamed live on our YouTube channel. Link will be available on that page one hour prior to the event.