David I. August
Professor in the Department of Computer Science, Princeton 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 221
Email: august@princeton.edu
Phone: (609) 258-2085
Fax: (609) 964-1699
Administrative Assistant: Pamela DelOrefice, (609) 258-5551

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

Publications

The Liberty Structural Specification Language: A High-Level Modeling Language for Component Reuse [abstract] (ACM DL, PDF)
Manish Vachharajani, Neil Vachharajani, and David I. August
Proceedings of the 2004 ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), June 2004.
Accept Rate: 19% (25/128).

Rapid exploration of the design space with simulation models is essential for quality hardware systems research and development. Despite striking commonalities across hardware systems, designers routinely fail to achieve high levels of reuse across models constructed in existing general-purpose and domain-specific languages. This lack of reuse adversely impacts hardware system design by slowing the rate at which ideas are evaluated. This paper presents an examination of existing languages to reveal their fundamental limitations regarding reuse in hardware modeling. With this understanding, a solution is described in the context of the design and implementation of the Liberty Structural Specification Language (LSS), the input language for a publicly available high-level digital-hardware modeling tool called the Liberty Simulation Environment. LSS is the first language to enable low-overhead reuse by simultaneously supporting static inference based on hardware structure and flexibility via parameterizable structure. Through LSS, this paper also introduces a new type inference algorithm and a new programming language technique, called use-based specialization, which, in a manner analogous to type inference, customizes reusable components by statically inferring structural properties that otherwise would have had to have been specified manually.