Princeton University

School of Engineering & Applied Science

David Wentzlaff

Associate Professor of Electrical Engineering

Room: B228 Engineering Quadrangle
Phone: 609-258-7781
Webpage: Wentzlaff Lab:


  • Ph.D., Massachusetts Institute of Technology, 2012
  • M.S., Electrical Engineering and Computer Science, Massachusetts Institute of Technology, 2002
  • B.S., Electrical Engineering, University of Illinois at Urbana-Champaign, 2000

My research group has two main thrusts. First, my group focuses on the design of future computing architectures and software systems for data centers and cloud computers. Second, my research group investigates the broad area of green computing including how to minimize the impact of computing systems on the environment and how to design computer systems to be serviced and ultimately decommissioned in a sustainable manner. The ever shrinking transistor and continuation of Moore’s Law has afforded the computer architect a wealth of transistor resources. Using these transistors to increase the performance of single processor systems is now at the point of diminishing returns. As humanity still desires higher performance computers, my research group and industry has turned to allocating additional transistors for parallel computing resources (more processor cores). A separate, but equally important trend is the growth of cloud computing systems, which has been fueled by the economies of scale derived from centrally managing computers. The ability for a user to leverage computing in an on-demand fashion and treat computation as a true commoditized utility enables new classes of computation and opens the door for the average programmer to solve problems unthinkable without the ability to easily harness huge amounts of computation. We are investigating the intersection of manycore computers and cloud systems. Many challenging problems need to be solved in order to build the cloud computer of twenty years in the future. My group is investigating how to build the chips, interconnect, system design, heating, cooling, power distribution, and software to fuel the 5000 core chip integrated into a million core data center of the future. The environment is one of humanities most important resources. It sustains life and without a suitable environment, humanity may cease to exist. Unfortunately, advances in computing systems have largely come at the expense of the environment. The never ending computer upgrade cycle has created large amounts of e-waste. In my research group, we are investigating how to create computing systems which are sustainable across the entire life-cycle of the system. This work not only aims to reduce the power and environmental operational impact of computer systems, but also the impact of computing systems after they have become obsolete. We are focusing on how to design computing systems such that they can be recycled easier, they can be serviced and upgraded easier to increase their usable lifetime, and how to design computer chips and systems such that they can be dismantled in the most environmentally friendly manner.

Selected Publications

  1. David Wentzlaff, Charles Gruenwald III, Nathan Beckmann, Kevin Modzelewski, Adam Belay, Lamia Youseff, Jason Miller, and Anant Agarwal. An operating system for multicore and clouds: mechanisms and implementation. In SoCC: Proceedings of the 1st ACM symposium on Cloud computing, pages 3–14. ACM, June 2010.

  2. Henry Hoffmann, David Wentzlaff, and Anant Agarwal. Remote store programming. In HiPEAC: Proceedings of High Performance Embedded Architectures and Compilers, 5th International Conference, pages 3–17, January 2010.

  3. David Wentzlaff and Anant Agarwal. Factored operating systems (fos): the case for a scalable operating system for multicores. SIGOPS Operating Systems Review, 43(2):76–85, 2009.

  4. Shane Bell, Bruce Edwards, John Amann, Rich Conlin, Kevin Joyce, Vince Leung, John MacKay, Mike Reif, Liewei Bao, John Brown, Matthew Mattina, Chyi-Chang Miao, Carl Ramey, David Wentzlaff, Walker Anderson, Ethan Berger, Nat Fairbanks, Durlov Khan, Froilan Montenegro, Jay Stickney, and John Zook. Tile64 - processor: A 64-core SoC with mesh interconnect. In ISSCC: Digest of Technical Papers of the IEEE International Solid-State Circuits Conference, pages 88–89,598, 3-7 2008

  5. David Wentzlaff, Patrick Griffin, Henry Hoffmann, Liewei Bao, Bruce Edwards, Carl Ramey, Matthew Mattina, Chyi-Chang Miao, John F. Brown III, and Anant Agarwal. On-chip interconnection architecture of the tile processor. IEEE Micro, 27:15–31, 2007.

  6. David Wentzlaff and Anant Agarwal. Constructing virtual architectures on a tiled processor. In CGO: Proceedings of the IEEE/ACM International Symposium on Code Generation and Optimization, pages 173–184. IEEE Computer Society, 2006.

  7. David Wentzlaff and Anant Agarwal. A quantitative comparison of reconfigurable, tiled, and conventional architectures on bit-level computation. In FCCM: Proceedings of the Annual IEEE Symposium on Field-Programmable Custom Computing Machines, pages 289–290. IEEE Computer Society, 2004.

  8. Michael B. Taylor, Walter Lee, Jason Miller, David Wentzlaff, Ian Bratt, Ben Greenwald, Henry Hoffmann, Paul Johnson, Jason Kim, James Psota, Arvind Saraf, Nathan Shnidman, Volker Strumpen, Matt Frank, Saman Amarasinghe, and Anant Agarwal. Evaluation of the raw microprocessor: An exposed-wire-delay architecture for ilp and streams. In ISCA: Proceedings of the International Symposium on Computer Architecture, pages 2–13. IEEE Computer Society, 2004.

  9. Jason Sungtae Kim, Michael B. Taylor, Jason Miller, and David Wentzlaff. Energy characterization of a tiled architecture processor with on-chip networks. In ISLPED: Proceedings of the International Symposium on Low Power Electronics and Design, pages 424–427.ACM, 2003.

  10. Michael B. Taylor, Jason Kim, Jason Miller, David Wentzlaff, Fae Ghodrat, Ben Greenwald, Henry Hoffman, Paul Johnson, Jae-Wook Lee, Walter Lee, Albert Ma, Arvind Saraf, Mark Seneski, Nathan Shnidman, Volker Strumpen, Matt Frank, Saman Amarasinghe, and Anant Agarwal. The Raw microprocessor: A computational fabric for software circuits and general-purpose programs. IEEE Micro, 22:25–35, 2002.