Distributed Scheduling of Parallel Hybrid Computations

Abstract

Multicore computing is fast becoming the norm. Improving parallel programming productivity without compromising performance on multicores is a serious challenge facing research community and systems vendors. Towards this end, efficient run-time scheduling of parallel programs helps programmer by dynamically mapping tasks onto processors and scheduling them in appropriate order. Distributed scheduling of parallel computations on multiple places while ensuring low time and message complexity in bounded space is a very challenging problem. We attempt to address this challenge for hybrid parallel computations which contain tasks that have pre-specified affinity to a place and also tasks that can be mapped to any place in the system. This paper presents online distributed scheduling algorithms for hybrid parallel computations assuming both unconstrained and bounded space per place. We also present the time and message complexity for distributed scheduling of hybrid computations. To the best of our knowledge, this is the first time distributed scheduling algorithms for hybrid parallel computations have been presented and analyzed for time and message bounds under both unconstrained space and bounded space.