An analysis of address and branch patterns with PatternFinder

Abstract

Current processors employ aggressive prediction mechanisms to improve performance and reduce power. It is increasingly important to understand and quantify a program's dynamic behavior to effectively design next-generation prediction mechanisms. In this paper, we develop algorithms and mechanisms inspired by DNA discovery tools to analyze and quantify program dynamic behavior in terms of regularities and patterns. We describe our PatternFinder tool and analyze its results to summarize most important branch and data address pattern behaviors for a set of program traces and SPEC CPU 2006 benchmarks.