**Abstract**: Fast-paced changes across the computing stack are creating opportunities for innovation by bridging software, architecture, and VLSI. Although cross-cutting research is challenging, an interdisciplinary approach can expose key insights that would otherwise be hidden by abstractions. In this talk, I will demonstrate a cross-stack approach to improve the efficiency of task-based parallel runtimes, which underpin the parallelization of state-of-the-art graph analytics and machine learning frameworks. Shifting the focus downward, I will discuss a cross-stack approach that addresses key circuit-level challenges in integrated voltage regulation. To finish the talk, I will discuss my future plans to apply a cross-stack research approach to fog computing for the Internet of Things, as well as to the problem of rapid ASIC design based on tilable hardware design techniques including GALS and chiplets.

**Bio**: Christopher Torng is a Ph.D. student at Cornell University in the School of Electrical and Computer Engineering, where he also received his B.S. degree. He builds specialized architectures that tie together software with the underlying devices. His activities have resulted in a selection as a Rising Star in Computer Architecture (2018) by Georgia Tech and an IEEE MICRO Top Pick from Hot Chips (2018) with coverage in EE Times. He has also been involved in six tapeouts supporting his research, and he was the project or university lead for three chips. In his spare time, Chris enjoys figure skating on the ice.