Presenter

Andrew Tee is a Master’s student in Electrical Engineering in the Department of Electrical and Computer Engineering at the University of California, Riverside. His research interests include GPU microarchitecture, computer architecture, and high-performance computing. His current work focuses on performance characterization of modern GPU architectures, with emphasis on memory hierarchy, compute and memory partitioning, and instruction-level parallelism in SIMD units. His work experience spans the computing stack, from GPU microarchitecture research at Advanced Micro Devices, to firmware and embedded software development at Harman International and Range Energy, and application-level optimization at Keysight Technologies.