Alvin R. Lebeck
Professor of Computer Science
My research is in the general area of computer architecture. However, I have interests in nearly all computer systems related topics, spanning from atoms to applications.
Appointments and Affiliations
- Professor of Computer Science
- Professor in the Department of Electrical and Computer Engineering
- Core Faculty in Innovation & Entrepreneurship
Contact Information
- Office Location: D308 Lev Sci Res Ctr, Durham, NC 27708
- Office Phone: (919) 660-6551
- Email Address: alvy@cs.duke.edu
- Websites:
Education
- Ph.D. University of Wisconsin - Madison, 1995
- M.S. University of Wisconsin - Madison, 1991
- B.S. University of Wisconsin - Madison, 1989
Research Interests
Accelerating Statistical Machine Learning
Novel computer architectures targeted at machine learning problems that rely on Markov Chain Monte Carlo techniques and probabilistic computing in general.
Multicore/multiprocessor and Distributed Systems (including data centers)
Cache coherence protocols, memory consistency, runtime systems to expose and exploit parallelism. I also explore the use of new hardware technology in data centers.
Architectures for Emerging Technologies
Computational paradigms enabled by new technologies.
Memory Systems
General aspects of memory hierarchies such as cache design, prefetching, latency tolerance, etc.
Energy Efficient Computing
Processor and memory design, operating system support.
Awards, Honors, and Distinctions
- Alan D. Berenbaum Distinguished Service Award. ACM SIGARCH. 2020
- Fellow. IEEE. 2017
- Honorable Mention, IEEE MICRO Top Picks from Computer Architecture Conferences . IEEE MICRO. 2017
- Best Paper. 6th International Workshop on Network on Chip Architectures. 2013
- IEEE MICRO Top Picks from Computer Architecture Conferences . IEEE. 2010
- IEEE MICRO Top Picks from Computer Architecture Conferences . IEEE MICRO. 2009
- Best Paper. 31st Annual ACM/IEEE International Symposium on Microarchitecture. 1998
- NSF CAREER. National Science Foundation. 1997
- Outstanding Graduate Student Researcher. Department of Computer Sciences, University of Wisconsin at Madison. 1995
Courses Taught
- COMPSCI 210D: Introduction to Computer Systems
- COMPSCI 250D: Computer Architecture
- COMPSCI 310: Introduction to Operating Systems
- COMPSCI 390: Topics in Computer Science
- COMPSCI 590: Advanced Topics in Computer Science
- ECE 250D: Computer Architecture
- ECE 353: Introduction to Operating Systems
- ECE 552: Advanced Computer Architecture I
- ECE 652: Advanced Computer Architecture II
In the News
- Thermo Fisher Scientific Acquires Programmable Dye Platform Pioneer Phitonex (Dec 31, 2020)
- Phitonex Pushes the Envelope of Immunology Research with 40 Color Flow Cytometry Experiment (Apr 14, 2020)
- Phitonex Announces $2M Seed Funding (Oct 10, 2019)
Representative Publications
- Zhang, X; Bashizade, R; Wang, Y; Mukherjee, S; Lebeck, AR, Statistical robustness of Markov chain Monte Carlo accelerators, International Conference on Architectural Support for Programming Languages and Operating Systems Asplos (2021), pp. 959-974 [10.1145/3445814.3446697] [abs].
- Bashizade, R; Zhang, X; Mukherjee, S; Lebeck, AR, Accelerating Markov Random Field Inference with Uncertainty Quantification., Corr, vol abs/2108.00570 (2021) [abs].
- Zeng, H; Ellis, CS; Lebeck, AR; Vahdat, A, Currentcy: A unifying abstraction for expressing energy management policies, Proceedings of the General Track: 2003 Usenix Annual Technical Conference (2020), pp. 43-56 [abs].
- Misra, PA; Radhakrishnan, S; Chase, JS; Gehrke, J; Lebeck, AR, Lightweight Inter-transaction Caching with Precise Clocks and Dynamic Self-invalidation., Corr, vol abs/2003.04150 (2020) [abs].
- Zhang, X; Bashizade, R; Wang, Y; Lyu, C; Mukherjee, S; Lebeck, AR, Beyond Application End-Point Results: Quantifying Statistical Robustness of MCMC Accelerators., Corr, vol abs/2003.04223 (2020) [abs].