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

NOTE:

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.

Publications

Automatic Instruction-Level Software-Only Recovery [abstract] (IEEE Xplore, PDF, Top Picks Version)
Jonathan Chang, George A. Reis, and David I. August
Proceedings of the International Conference on Dependable Systems and Networks (DSN), June 2006.
Accept Rate: 18% (34/187).
Winner of the William C. Carter Award.
Selected for IEEE Micro's "Top Picks" special issue for papers "most relevant to industry and significant in contribution to the field of computer architecture" in 2006.

As chip densities and clock rates increase, processors are becoming more susceptible to transient faults that can affect program correctness. Computer architects have typically addressed reliability issues by adding redundant hardware, but these techniques are often too expensive to be used widely. Software-only reliability techniques have shown promise in their ability to protect against soft-errors without any hardware overhead. However, existing low-level software-only fault tolerance techniques have only addressed the problem of detecting faults, leaving recovery largely unaddressed. In this paper, we present the concept, implementation, and evaluation of automatic, instruction-level, software-only recovery techniques, as well as various specific techniques representing different trade-offs between reliability and performance. Our evaluation shows that these techniques fulfill the promises of instruction-level, software-only fault tolerance by offering a wide range of flexible recovery options