Approximate graph clustering for program characterization
Abstract
An important aspect of system optimization research is the discovery of program traits or behaviors. In this paper, we present an automated method of program characterization which is able to examine and cluster program graphs, i.e., dynamic data graphs or control flow graphs. Our novel approximate graph clustering technology allows users to find groups of program fragments which contain similar code idioms or patterns in data reuse, control flow, and context. Patterns of this nature have several potential applications including development of new static or dynamic optimizations to be implemented in software or in hardware.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jan 01, 2012
- Source ID
- 10.1145/2086696.2086700
Entities
People
- John Demme
- Simha Sethumadhavan
Organizations
- Air Force Research Laboratory
- Columbia University
- Defense Advanced Research Projects Agency