Zhiru Zhang (Cornell University)
Filling in the Missing Pieces Toward Autonomous Accelerator Design [slides]
Abstract
We are living through a fundamental shift in computing, where performance and efficiency gains increasingly come from specialized accelerators tailored to hot domains such as AI. Yet as accelerator-centric computing proliferates, it continues to build on a longstanding disconnect between how these systems are designed and how they are programmed. This divide slows hardware innovation, complicates the software stack, and makes accelerators much harder to evolve than the rapidly changing applications they are meant to serve.
While increasingly powerful coding agents can help mitigate some of these challenges, many key pieces are still missing to truly close this gap. In this talk, I will present some of our recent research on abstractions that unify accelerator design and programming, agentic compiler construction, and differentiable hardware synthesis, and discuss how these directions may help move us toward more autonomous accelerator design.
Bio
Zhiru Zhang is a Professor in the School of ECE at Cornell University. His current research investigates new algorithms, design methodologies, and automation tools for heterogeneous computing. Dr. Zhang is an IEEE Fellow and has been honored with the Intel Outstanding Researcher Award, AWS AI Amazon Research Award, Facebook Research Award, Google Faculty Research Award, DAC Under-40 Innovators Award, DARPA Young Faculty Award, IEEE CEDA Ernest S. Kuh Early Career Award, and NSF CAREER Award. He has also received 10+ best paper awards from premier conferences and journals in computer systems and EDA. Prior to joining Cornell, he co-founded AutoESL, a high-level synthesis start-up later acquired by Xilinx (now part of AMD). AutoESL's HLS tool evolved into Vivado HLS (now Vitis HLS), which is widely used for designing FPGA-based hardware accelerators.