Performance and energy efficiency analysis of data reuse transformation methodology on multicore processor

Authors:
Abdullah Al Hasib;Per Gunnar Kjeldsberg;Lasse Natvig
Affiliations:
Department of Computer and Information Science, Norwegian University of Science and Technology, Trondheim, Norway;Department of Electronics and Telecommunications, Norwegian University of Science and Technology, Trondheim, Norway;Department of Computer and Information Science, Norwegian University of Science and Technology, Trondheim, Norway
Venue:
Euro-Par'12 Proceedings of the 18th international conference on Parallel processing workshops
Year:
2012

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Abstract

Memory latency and energy efficiency are two key constraints to high performance computing systems. Data reuse transformations aim at reducing memory latency by exploiting temporal locality in data accesses. Simultaneously, modern multicore processors provide the opportunity of improving performance with reduced energy dissipation through parallelization. In this paper, we investigate to what extent data reuse transformations in combination with a parallel programming model in a multicore processor can meet the challenges of memory latency and energy efficiency constraints. As a test case, a "full-search motion estimation" kernel is run on the Intel® CoreTM i7-2600 processor. Energy Delay Product (EDP) is used as a metric to compare energy efficiencies. Achieved results show that performance and energy efficiency can be improved by a factor of more than 6 and 15, respectively, by exploiting a data reuse transformation methodology and parallel programming model in a multicore system.