Andrew Lukefahr, University of Michigan, CS Colloquium Speaker
The School of Informatics and Computing (SoIC) Computer Science (CS) Colloquium Series
Speaker: Andrew Lukefahr, University of Michigan
Where: Lindley Hall, Rm. 102
Abstract: We demand a lot from our smartphones. We want our websites rendered in milliseconds, always-on connectivity, and multi-day battery life. To meet these challenges, today's phones incorporate a heterogeneous mix of high-performance and energy-efficient processor cores. Together these cores have the potential to deliver high performance when needed while still maximizing battery life.
Unfortunately, migrating applications between these cores is computationally expensive, often requiring tens of thousands of cycles. Due to this overhead, designers avoid migrating to energy-efficient cores while the phone is in use, missing opportunities to utilize these cores and reducing battery life. However, even high-performance applications show fine-grained phases of low performance. This talk focuses on building a single "composite" core that attempts to push the notion of heterogeneity into the core itself. This enables a Composite Core to quickly transition between high-performance and energy-efficient modes without impacting performance, and allows it to capture and exploit fine-grained phases to maximize energy efficiency.
The dream of the Internet-of-Things (IoT) world is computation so passive and pervasive that it fades into the background of every life. For this dream to become reality, IoT devices must be able to survive indefinitely powered only by energy harvested from their surroundings. This makes reliable, energy-efficient computation the design constraint for these systems. I will briefly discuss some of the challenges and opportunities for designing architectures and systems that can provide meaningful computation in this energy constrained world.
Biography: Andrew Lukefahr is currently a Lecturer in Computer Science and Engineering at the University of Michigan, where he completed his PhD in 2016. His research focuses on maximizing energy efficiency in computation. His thesis work was focused on next-generation heterogeneous core architectures for mobile devices, resulting in multiple publications and patents. His research interests include energy-efficient computing, architectures for mobile/embedded systems, and neural-inspired computation.