Backfilling with lookahead to optimize the performance of parallel job scheduling

The utilization of parallel computers depends on how jobs are packed together: if the jobs axe not packed tightly, resources are lost due to fragmentation. The problem is that the goal of high utilization may conflict with goals of fairness or even progress for all jobs. The common solution is to use backfilling, which combines a reservation for the first job in the interest of progress with packing of later jobs to fill in holes and increase utilization. However, backfilling considers the queued jobs one at a time, and thus might miss better packing opportunities. We propose the use of dynamic programming to find the best packing possible given the current composition of the queue. Simulation results show that this indeed improves utilization, and thereby reduces the average response time and average slowdown of all jobs.