Integer Programming Based Heterogeneous CPU-GPU Cluster Scheduler for SLURM Resource Manager

Abstract

We present an integer programming based heterogeneous CPU-GPU cluster scheduler for the widely used SLURM resource manager. Our scheduler algorithm takes windows of jobs and solves an allocation problem in which free CPU cores and GPU cards are allocated collectively to jobs so as to maximize some objective function. We perform realistic SLURM emulation tests using the Effective System Performance (ESP) workloads. The test results show that our scheduler produces better resource utilization and shorter average job waiting times. The SLURM scheduler plug-in that implements our algorithm is available at http://code.google.com/p/slurm-ipsched/.