SD3: A Scalable Approach to Dynamic Data-Dependence Profiling

Abstract--As multicore processors are deployed in mainstream computing, the need for software tools to help parallelize programs is increasing dramatically. Data-dependence profiling is an important technique to exploit parallelism in programs. More specifically, manual or automatic parallelization can use the outcomes of data-dependence profiling to guide where to parallelize in a program. However, state-of-the-art data-dependence profiling techniques are not scalable as they suffer from two major issues when profiling large and long-running applications: (1) runtime overhead and (2) memory overhead. Existing data-dependence profilers are either unable to profile large-scale applications or only report very limited information. In this paper, we propose a scalable approach to datadependence profiling that addresses both runtime and memory overhead in a single framework. Our technique, called SD3 , reduces the runtime overhead by parallelizing the dependence profiling step itself. To r...

• Type: Journal
• Year: 2010
• Where: MICRO
• Authors: Minjang Kim, Hyesoon Kim, Chi-Keung Luk
• Keywords: Cores, Data Dependence, Data-dependence Profiling, Hardware, MICRO 2010