Palirria: Accurate On-line Parallelism Estimation for Adaptive Work-Stealing

Authors:
Georgios Varisteas;Mats Brorsson
Affiliations:
KTH Royal Institute of Technology;KTH Royal Institute of Technology
Venue:
Proceedings of Programming Models and Applications on Multicores and Manycores
Year:
2014

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Abstract

We present Palirria, a self-adapting work-stealing scheduling method for nested fork/join parallelism that can be used to estimate the number of utilizable workers and self-adapt accordingly. The estimation mechanism is optimized for accuracy, minimizing the requested resources without degrading performance. We implemented Palirria for both the Linux and Barrelfish operating systems and evaluated it on two platforms: a 48-core NUMA multiprocessor and a simulated 32-core system. Compared to state-of-the-art, we observed higher accuracy in estimating resource requirements. This leads to improved resource utilization and performance on par or better to executing with fixed resource allotments.