A workload-aware mapping approach for data-parallel programs

Much compiler-orientated work in the area of mapping parallel programs to parallel architectures has ignored the issue of external workload. Given that the majority of platforms will not be dedicated to just one task at a time, the impact of other jobs needs to be addressed. As mapping is highly dependent on the underlying machine, a technique that is easily portable across platforms is also desirable. In this paper we develop an approach for predicting the optimal number of threads for a given data-parallel application in the presence of external workload. We achieve 93.7% of the maximum speedup available which gives an av

• Type: Journal
• Year: 2011
• Where: HIPEAC
• Authors: Dominik Grewe, Zheng Wang, Michael F. P. O'Boyle
• Keywords: HIPEAC 2011, Maximum Speedup, Parallel Application, Parallel Architectures, System Software