Runtime system for autonomic rescheduling of MPI programs

Abstract

Intensive research has been conducted on dynamic job scheduling, which dynamically allocates jobs to computing systems. However, most of the existing work is limited to redistribute independent tasks or at the algorithm design level. There is no runtime system available to support automatic redistribution of a running process in a heterogeneous network environment. In this study, we present the design and implementation of a system that dynamically reschedules running processes over a network of computing resources via automatic decision-making and process migration. The system is implemented on top of MPI-2 and HPCM (high performance computing mobility) middleware. Experimental and analytical results show that the runtime system works well. It makes dynamic rescheduling of running tasks possible and improves system performance considerably. While the implementation is for MPI programs and using HPCM, the design of the system is general and can be extended to other distributed environments as well.