Computer Science Professor Publishes Research in Journal Special Issue
Research led by Assistant Professor Kevin Angstadt ‘14 was recently published in the September/October 2022 special issue of IEEE Micro on Compiling for Accelerators.
Demands by business leaders for real-time analyses of data and the increasing technical challenges of designing faster general-purpose processors have led to the development and adoption of specialized, application-specific computer hardware, known as accelerators.
Angstadt’s paper, Synthesizing Legacy String Code for FPGAs Using Bounded Automata Learning, focuses on automatically converting existing software to run on these new accelerators. Existing programming techniques require specialized training and knowledge, but the new approach presented by Angstadt and his collaborators can reduce this burden significantly for certain kinds of programs used across many domains, including virus scanning, network security, social network analysis, machine learning, and bioinformatics. The paper published in IEEE Micro also includes experimental results demonstrating that Angstadt’s new approach also improves the speed and reduces the hardware requirements of resulting programs when compared with the current industry standard tools.
This publication was the result of collaboration between Kevin Angstadt at St. Lawrence University, Tommy Tracy II and Kevin Skadron at the University of Virginia, and Jean-Baptiste Jeannin and Westley Weimer at the University of Michigan. The work was supported in part by the National Science Foundation, Air Force Research Labs, Jefferson Scholars Foundation, and the Center for Research in Intelligent Storage and Processing in Memory (CRISP), one of six centers in the Joint University Microelectronics Program (JUMP), a Semiconductor Research Corporation (SRC) program sponsored by the Defense Advanced Research Projects Agency (DARPA).
