Heuristics for resource matching in Intel's compute farm

In this paper we investigate the issue of resource matching between jobs and machines in Intel's compute farm. We show that common heuristics such as Best-Fit and Worse-Fit may fail to properly utilize the available resources when applied to either cores or memory in isolation. In an attempt to overcome the problem we propose Mix-Fit, a heuristic which attempts to balance usage between resources. While this indeed usually improves upon the single-resource heuristics, it too fails to be optimal in all cases. As a solution we default to Max-Jobs, a meta-heuristic that employs all the other heuristics as sub-routines, and selects the one which matches the highest number of jobs. Extensive simulations that are based on real workload traces from four different Intel sites demonstrate that Max-Jobs is indeed the most robust heuristic for diverse workloads and system configurations, and provides up to 22 % reduction in the average wait time of jobs.