Speaker: Olivia Hsu, Stanford University Date: Thursday, March 20 Time: 12:30pm EST Location: CS 105 Host: Brian Kernighan Event page: https://www.cs.princeton.edu/events/language-silicon-programming-systems-spa... Register for live-stream online here: https://princeton.zoom.us/webinar/register/WN_j-QIWzFvR1mwBO3qOP9atg Title: From Language to Silicon: Programming Systems for Sparse Accelerators Abstract: In this era of specialization, modern hardware development focuses on domain-specific accelerator design due to the plateau in technology scaling combined with a continual need for performance. However, domain-specific programming systems for these accelerators require extreme engineering effort, and their complexity has largely caused them to lag behind. Fundamentally, the widespread usability, proliferation, and democratization of domain-specific accelerators hinge on their programming systems, especially when targeting new domains. This talk presents research on accelerator programming systems for the emerging domain of sparse computation. The first system, the Sparse Abstract Machine (SAM), introduces a unified abstract machine model and compiler abstraction for sparse dataflow accelerators. SAM defines a novel streaming representation and abstract dataflow interfaces that serve as an abstraction to decouple sparse accelerator implementations from their programs, similar to a stable ISA but for dataflow. The second system, Mosaic, introduces modular and portable compilation solutions that can leverage heterogeneous sparse accelerators and high-performance systems within the same system. These systems are a first step towards usable and programmable heterogeneous hardware acceleration for all. I will conclude by discussing the next steps to reach this goal, which include programming systems for accelerators in other domains and interoperation between accelerators across domains. Bio: Olivia Hsu is a final-year Ph.D. candidate at Stanford University in the Department of Computer Science, advised by Professors Kunle Olukotun and Fredrik Kjolstad. She received her B.S. in Electrical Engineering and Computer Science (EECS) at UC Berkeley. Her broad research interests include computer architecture, computer and programming systems, compilers, programming languages, and digital circuits/VLSI. Olivia is a 2024 Rising Star in EECS and an NSF Graduate Research Fellow, and her research won a distinguished paper award at PLDI 2023. To learn more about her work, please visit her website at https://cs.stanford.edu/~owhsu.