Towards architecture independent metrics for multicore performance analysis

Abstract

The prevalence of multicore architectures has made the performance analysis of multithreaded applications an intriguing area of inquiry. An understanding of locality effects and communication behavior can provide programmers with valuable information about performance bottlenecks and opportunities for optimization. Unfortunately, most performance analyses are architecture dependent, and hence insights gleaned from an application's behavior on one platform may not apply when the application is run on another. In this position paper, we argue that what is needed are architecture independent metrics that characterize the behavior of an application in a system-agnostic manner. Such metrics will allow a program's performance to be analyzed across a range of architectures without incurring the overhead of repeated profiling and analysis. We propose two specific analyses: multicore-aware reuse distance, which captures the locality properties of an application and communication analysis, which exposes the structure of communication in an application. We also discuss a number of applications of these analyses, in the domains of optimization, code restructuring and performance modeling.