Autotuning is an established technique for optimizing the performance of parallel applications. However, programmers must prepare applications for autotuning, which is tedious and error prone coding work. We demonstrate how applications become ready for autotuning with few or no modifications by extending Threading Building Blocks (TBB), a library for parallel programming, with autotuning. The extended TBB library optimizes all application-independent tuning parameters fully automatically. We compare manual effort, autotuning overhead and performance gains on 17 examples. While some examples benefit only slightly, others speed up by 28% over standard TBB.
@article{arxiv.1405.2918,
title = {Autotuning and Self-Adaptability in Concurrency Libraries},
author = {Thomas Karcher and Christopher Guckes and Walter F. Tichy},
journal= {arXiv preprint arXiv:1405.2918},
year = {2014}
}
Comments
Presented at 1st Workshop on Resource Awareness and Adaptivity in Multi-Core Computing (Racing 2014) (arXiv:1405.2281)