Alvin R. Lebeck

Lebeck

Professor of Computer Science

Computer Systems Engineering with a focus on computer architecture, nano-scale systems, memory system, energy efficient computing, and multiprocessors.

Appointments and Affiliations

  • Professor of Computer Science
  • Professor in the Department of Electrical and Computer Engineering

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 at Madison, 1995
  • M.S. University of Wisconsin at Madison, 1991
  • B.S. University of Wisconsin at Madison, 1989

Research Interests

Hello web surfers, welcome to my corner of the internet.  I carry out research and teach in the broad area of computer systems, especially in computer architecture. My research spans from atoms to applications. Below is a bit more about my 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.

Memory Systems 
General aspects of memory hierarchies such as cache design, prefetching, latency tolerance, etc.

Architectures for Emerging Technologies  
DNA self-assembled systems, self-organizing systems, defect-tolerance, nanophotonics.  Although my active research in this area is winding down, I do have a company (Phitonex) that is commercializing some of the technology in the life science space.  I continue to be interested in new computational paradigms enabled by new technologies.

Energy Efficient Computing 
Processor and memory design, operating system support.

Check out Computer Architecture Today the ACM SIGARCH Blog (I was the founding editor).

If you are in the life sciences you may interested in Phitonex, a company based on our years of research on DNA nanostructures and fluorescence.

Awards, Honors, and Distinctions

  • 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 310: Introduction to Operating Systems
  • COMPSCI 590: Advanced Topics in Computer Science
  • ECE 353: Introduction to Operating Systems
  • ECE 552: Advanced Computer Architecture I
  • ECE 590: Advanced Topics in Electrical and Computer Engineering

Representative Publications

  • Zhang, X; Mukherjee, S; Lebeck, A, A Case for Quantifying Statistical Robustness of Specialized Probabilistic AI Accelerators, 2019 Ibm Ieee Cas/Eds – Ai Compute Symposium (2019) [abs].
  • Witchel, E; Lebeck, A, Message from the Program Chairs, International Conference on Architectural Support for Programming Languages and Operating Systems Asplos (2019), pp. IV-V [abs].
  • Misra, PA; Borge, MF; Goiri, I; Lebeck, AR; Zwaenepoel, W; Bianchini, R, Managing tail latency in datacenter-scale file systems under production constraints, Proceedings of the 14th Eurosys Conference 2019 (2019) [10.1145/3302424.3303973] [abs].
  • Bashizade, R; Li, Y; Lebeck, AR, Adaptive simultaneous multi-tenancy for GPUs, Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol 11332 LNCS (2019), pp. 83-106 [10.1007/978-3-030-10632-4_5] [abs].
  • Zhang, X; Bashizade, R; LaBoda, C; Dwyer, C; Lebeck, AR, Architecting a stochastic computing unit with molecular optical devices, Proceedings International Symposium on Computer Architecture (2018), pp. 301-314 [10.1109/ISCA.2018.00034] [abs].