Adaptive Scheduling under Memory Pressure on Multiprogrammed Clusters

This paper presents scheduling techniques that enable the adaptation of parallel programs to clustered computational farms with limited memory capacity. The purpose of the techniques is to coschedule communicating processes and prevent paging, using two cooperating extensions to the kernel scheduler. A paging prevention module enables memory-bound programs to adapt to memory short-age, by suspending their threads at well-defined execution points. The associated operating system interface provides a generic mechanism that enables programs to adapt in different ways, including application-specific forms of adaptation. At the same time, a dynamic coscheduling heuristic implemented in the kernel scheduler increases periodically the priority of communicating processes so that parallel jobs are eased through communication points. We show that when a parallel job competes with randomized sequential load running in the nodes of the cluster, the combination of coscheduling and paging prevention reduces drastically the slowdown of the job at high levels of memory utilization. We also show that if memory resources are ample, coscheduling should take priority over paging prevention, whereas if memory resources are scarce, preventing paging should take priority over coscheduling.