McKee received her bachelor’s degree in Computer Science from Yale University, master’s from Princeton University, and doctorate from the University of Virginia. Her dissertation advisor was Bill Wulf, with whom she worked on memory systems architecture. Together they coined the now-common term the “memory wall” to describe a situation in which processors are always waiting on memory, and CPU performance is therefore entirely limited by memory performance.

Before graduate school, McKee worked for Digital Equipment Corporation and Microsoft Corporation. She has also held internships at Digital Equipment Corporation’s Systems Research Center (now HP Labs) and the former AT&T Bell Labs. McKee worked as a Post-Doctoral Research Associate in the University of Virginia Computer Science Department for a year after graduating (waiting for the chip to come back from fab) and as a Computer Architect at Intel’s Microcomputer Research Lab in Oregon for the next two years. During her time at Intel, she also taught at the Oregon Graduate Institute and Reed College. McKee was a Research Assistant Professor at the University of Utah’s School of Computing from 1998 to 2002, where she worked on the Impulse Adaptable Memory Controller project. She joined Cornell University’s Computer Systems Lab within the School of Electrical and Computer Engineering in 2002. She moved to the Department of Computer Science and Engineering at Chalmers University of Technology in 2008, and she became the C. Tycho Howle endowed chair within the Holcombe Department of Electrical and Computer Engineering at Clemson University in 2018. She spent the 2017 calendar year on sabbatical at Rambus Labs in Sunnyvale, CA.

Her research has historically focused mainly on analyzing application memory behavior and designing more efficient memory systems together with the software to exploit them. Achieving this broad objective requires developing new underpinnings for system understanding, and thus she and her students and collaborators have developed new approaches to performance analysis; built scalable tools for application analysis and system modeling; designed architectures to enable more comprehensive system introspection and analyses; designed efficient memory systems for HPC and embedded platforms; and automated memory optimizations for HPC applications.

Sandhya Dwarkadas is the Walter N. Munster Professor and Chair of Computer Science at the University of Virginia. Previously, she was the Albert Arendt Hopeman Professor of Engineering at the University of Rochester, where she was professor of computer science with a secondary appointment in electrical and computer engineering, and also served as department chair for 6 years. She received the 2020 Edmund A. Hajim Outstanding Faculty Award from the University of Rochester. She received her Bachelor’s degree from the Indian Institute of Technology, Madras, India, and her M.S. and Ph.D. from Rice University. She is a fellow of the ACM and IEEE. She was co-chair of the CRA-WP board and steering committee from 2019-2022 and has been on the CRA-WP board since 2010.
Her areas of research interest include parallel and distributed computing, computer architecture, and the interaction and interface between the compiler, runtime/operating system, and underlying architecture. She has made fundamental contributions to the design and implementation of shared memory both in hardware and in software, and to hardware and software energy- and resource-aware configurability.

Broadly speaking, I'm interested in computer architecture, particularly parallel systems. Prior work has included workload characterization of parallel applications and memory systems in traditional multiprocessor systems and GPUs and correctness in IoT systems.