David I. August
Professor in the Department of Computer Science, Princeton University
Visiting Professor in the Department of Electrical Engineering, Columbia University
Affiliated with the Department of Electrical Engineering, Princeton University
Ph.D. May 2000, Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign

Office: Computer Science Building Room 209
Email: august@princeton.edu
Phone: (609) 258-2085
Fax: (609) 964-1699

Front Page Publication List (with stats) Curriculum Vitae (PDF) The Liberty Research Group


Please beware of the "Princeton University - Part-Time Research Job" scam. I am not hiring remote research assistants for the Department of Computer Science. Anyone doing so would use a campus address or phone number. Princeton students, please visit the Phish Bowl before responding to unsolicited communication.


Parallelism Orchestration using DoPE: the Degree of Parallelism Executive [abstract] (ACM DL, PDF)
Arun Raman, Hanjun Kim, Taewook Oh, Jae W. Lee, and David I. August
Proceedings of the 32nd ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), June 2011.
Accept Rate: 23% (55/236).

In writing parallel programs, programmers expose parallelism and optimize it to meet a particular performance goal on a single platform under an assumed set of workload characteristics. In the field, changing workload characteristics, new parallel platforms, and deployments with different performance goals make the programmer's development-time choices suboptimal. To address this problem, this paper presents the Degree of Parallelism Executive (DoPE), an API and run-time system that separates the concern of exposing parallelism from that of optimizing it. Using the DoPE API, the application developer expresses parallelism options. During program execution, DoPE's run-time system uses this information to dynamically optimize the parallelism options in response to the facts on the ground. We easily port several emerging parallel applications to DoPE's API and demonstrate the DoPE run-time system's effectiveness in dynamically optimizing the parallelism for a variety of performance goals.