Impact of Data Structure Layout on Performance

Abstract

One key issue to design parallel applications that scale on multicore systems is how to overcome the memory bottleneck. This paper presents a study of the impact of data structure layouts in locality of memory references, providing insights on strategies to ameliorate the memory bottleneck. The paper compares the performance of Java and C++ STL collections and presents the impact of locality of reference optimisations in a molecular dynamics simulation case study. The case study shows that the selected data structure layout has impact on single core performance, becoming a critical factor in the application scalability on multicore systems. Moreover, data collections provided in the Java language compromise performance due to pointer chasing and lack of spatial locality of memory references.

DOI: 10.1109/PDP.2013.24

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@article{Faria2013ImpactOD, title={Impact of Data Structure Layout on Performance}, author={Nuno Faria and Rui C. Silva and Jo{\~a}o L. Sobral}, journal={2013 21st Euromicro International Conference on Parallel, Distributed, and Network-Based Processing}, year={2013}, pages={116-120} }