Autotuning and Self-Adaptability in Concurrency Libraries
This reduces the coding burden for programmers working on parallel applications, though it is incremental as it builds on existing autotuning and TBB techniques.
The paper tackles the problem of tedious manual preparation for autotuning in parallel applications by extending the Threading Building Blocks (TBB) library to enable autotuning with minimal code modifications, resulting in speedups of up to 28% over standard TBB in some examples.
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.