Fork-join and data-driven execution models on multi-core architectures: Case study of the FMM

Amer, Abdelhalim; Maruyama, Naoya; Pericàs, Miquel; Taura, Kenjiro; Yokota, Rio; Matsuoka, Satoshi

Fork-join and data-driven execution models on multi-core architectures: Case study of the FMM

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Type

Conference Paper

Authors

Amer, Abdelhalim
Maruyama, Naoya
Pericàs, Miquel
Taura, Kenjiro
Yokota, Rio

Matsuoka, Satoshi

KAUST Department

Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Extreme Computing Research Center

Date

2013

Abstract

Extracting maximum performance of multi-core architectures is a difficult task primarily due to bandwidth limitations of the memory subsystem and its complex hierarchy. In this work, we study the implications of fork-join and data-driven execution models on this type of architecture at the level of task parallelism. For this purpose, we use a highly optimized fork-join based implementation of the FMM and extend it to a data-driven implementation using a distributed task scheduling approach. This study exposes some limitations of the conventional fork-join implementation in terms of synchronization overheads. We find that these are not negligible and their elimination by the data-driven method, with a careful data locality strategy, was beneficial. Experimental evaluation of both methods on state-of-the-art multi-socket multi-core architectures showed up to 22% speed-ups of the data-driven approach compared to the original method. We demonstrate that a data-driven execution of FMM not only improves performance by avoiding global synchronization overheads but also reduces the memory-bandwidth pressure caused by memory-intensive computations. © 2013 Springer-Verlag.

Citation

Amer, A., Maruyama, N., Pericàs, M., Taura, K., Yokota, R., & Matsuoka, S. (2013). Fork-Join and Data-Driven Execution Models on Multi-core Architectures: Case Study of the FMM. Supercomputing, 255–266. doi:10.1007/978-3-642-38750-0_19