HRF: A Resource Allocation Scheme for Moldable Jobs

Moldable jobs, which allow the number of allocated proces-sors to be adjusted before running in clusters, have attracted increasing concern in parallel job scheduling research. Com-pared with traditional rigid jobs where the number of allo-cated processors is fixed, moldable jobs are more flexible and therefore have more potential for improving their average turnaround time (a crucial metric to describe performance of jobs in a cluster). Average turnaround time of mold-able jobs depends greatly on resource allocation schemes. Unfortunately, existing schemes do not perform well in re-ducing average turnaround time, either because they only consider a single job’s turnaround time instead of the aver-age turnaround time of all jobs, or because they just aim at fairness between short and long jobs instead of their av-erage turnaround time. In this paper, we investigate how resource allocation affects the average turnaround time of moldable jobs in clusters, and propose a scheme named HRF (highest revenue first), which allocates processors according to the highest revenue of shortening runtime. In our sim-ulations, experimental results show that HRF can reduce average turnaround time up to 71 % when compared with state-of-the-art schemes