PaSTeL: Parallel Runtime and Algorithms for Small Datasets

Abstract

In this paper, we put forward PaSTeL, an engine dedicated to parallel algorithms. PaSTeL offers both a programming model, to build parallel algorithms and an execution model based on work-stealing. Special care has been taken on using optimized thread activation and synchronization mechanisms. In order to illustrate the use of PaSTeL a subset of the STL's algorithms was implemented, which were also used on performance experiments. PaSTeL's performance is evaluated on a laptop computer using two cores, but also on a 16 cores platform. PaSTeL shows better performance than other implementations of the STL, especially on small datasets.