Understanding and overcoming parallelism bottlenecks in ForkJoin applications

Gustavo Pinto, Anthony Canino, Fernando Castor, Guoqing Xu, Yu David Liu
2017 2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE)  
FORKJOIN framework is a widely used parallel programming framework upon which both core concurrency libraries and real-world applications are built. Beneath its simple and user-friendly APIs, FORKJOIN is a sophisticated managed parallel runtime unfamiliar to many application programmers: the framework core is a work-stealing scheduler, handles finegrained tasks, and sustains the pressure from automatic memory management. FORKJOIN poses a unique gap in the compute stack between high-level
more » ... n high-level software engineering and low-level system optimization. Understanding and bridging this gap is crucial for the future of parallelism support in JVM-supported applications. This paper describes a comprehensive study on parallelism bottlenecks in FORKJOIN applications, with a unique focus on how they interact with underlying system-level features, such as work stealing and memory management. We identify 6 bottlenecks, and found that refactoring them can significantly improve performance and energy efficiency. Our field study includes an in-depth analysis of AKKA -a real-world actor framework -and 30 additional open-source FORKJOIN projects. We sent our patches to the developers of 15 projects, and 7 out of the 9 projects that replied to our patches have accepted them.
doi:10.1109/ase.2017.8115687 dblp:conf/kbse/PintoCCXL17 fatcat:kffsnpfk25ekphz2pofoh2o7yu