David H. Albonesi
Electrical and Computer Engineering
Professor David Albonesi joined the Computer Systems Laboratory in 2004 after serving on the faculty of the University of Rochester. His current research interests include adaptive and reconfigurable multi- core and processor architectures, power- and reliability-aware computing, and energy-efficient smart buildings. In addition to his academic experience, he has ten years of industry experience as a technical manager, computer architect, and chip designer at IBM and Prime Computer.
Dr. Albonesi is a Fellow of the IEEE, and has received the National Science Foundation CAREER Award, three IBM Faculty Awards, three IEEE Micro Top Picks paper awards, and the Michael Tien ’72, Ralph S. Watts ’72, and Ruth and Joel Spira Excellence in Teaching Awards. He serves on the Editorial Board of IEEE Computer, and was Editor-in-Chief of IEEE Micro from 2007-10. Professor Albonesi was General co-Chair of the 42nd International Symposium on Microarchitecture and Program Chair of the 42nd International Symposium on Computer Architecture. He is a graduate field member of ECE and CS, and teaches courses ranging from freshman-level introductory computing to advanced graduate topics in computer systems.
His MOOC, The Computing Technology Inside Your Smartphone, first launched on edX in Spring 2015 and ran for a second time in Summer 2016.
Computer Architecture, Smart Buildings
- 2017.“DeepRecon: Dynamically Reconfigurable Architecture for Accelerating Deep Neural Networks.” International Joint Conference on Neural Networks. .
- 2017.“Toolbox for Exploration of Energy-Efficient Event Processors for Human-Computer Interaction.” International Symposium on Performance Analysis of Systems and Software. .
- 2017.“Dynamic GPGPU Power Management Using Adaptive Model Predictive Control.” 23rd International Symposium on High Performance Computer Architecture. .
- 2013.“Flicker: A Dynamically Adaptive Architecture for the Dark Silicon Era.” Paper presented at International Symposium on Computer Architecture, June. .
- 2016.“Fractured Arithmetic Accelerator for Training Deep Neural Networks.” Paper presented at Workshop on Hardware and Algorithms for On-chip Learning, International Conference on Computer-Aided Design, November. .
Selected Awards and Honors
- Fiona Ip Li ’78 and Donald Li ’75 Excellence in Teaching Award 2021
- Ralph Watts ’72 Excellence in Teaching Award 2015
- Ruth and Joel Spira Award for Excellence in Teaching2014
- Michael Tien ’72 Excellence in Teaching Award2011
- Fellow of IEEE(IEEE)2011
- IEEE Computer Society Golden Core Award2011
- B.S.(Electrical Engineering),University of Massachusetts-Amherst,1982
- M.S.(Electrical Engineering),Syracuse University,1986
- Ph.D.(Computer Engineering),University of Massachusetts-Amherst,1996