Production Job Scheduling for Parallel Shared Memory Systems
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
Coscheduling under Memory Constraints in a NOW Environment
JSSPP '01 Revised Papers from the 7th International Workshop on Job Scheduling Strategies for Parallel Processing
Characteristics of a Large Shared Memory Production Workload
JSSPP '01 Revised Papers from the 7th International Workshop on Job Scheduling Strategies for Parallel Processing
Adjusting the Lengths of Time Slices when Scheduling PVM Jobs with High Memory Requirements
Proceedings of the 9th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface
Adaptive Memory Allocations in Clusters to Handle Unexpectedly Large Data-Intensive Jobs
IEEE Transactions on Parallel and Distributed Systems
Coscheduling in Clusters: Is It a Viable Alternative?
Proceedings of the 2004 ACM/IEEE conference on Supercomputing
LOMARC: Lookahead Matchmaking for Multiresource Coscheduling on Hyperthreaded CPUs
IEEE Transactions on Parallel and Distributed Systems
A comprehensive performance and energy consumption analysis of scheduling alternatives in clusters
The Journal of Supercomputing
Minimizing paging tradeoffs applying coscheduling techniques in a linux cluster
VECPAR'02 Proceedings of the 5th international conference on High performance computing for computational science
Service control with the preemptive parallel job scheduler Scojo-PECT
Cluster Computing
LOMARC — lookahead matchmaking for multi-resource coscheduling
JSSPP'04 Proceedings of the 10th international conference on Job Scheduling Strategies for Parallel Processing
Coarse-grain time slicing with resource-share control in parallel-job scheduling
HPCC'07 Proceedings of the Third international conference on High Performance Computing and Communications
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Almost all previous research on gang-scheduling has ignored the impact of real job memory requirements on the performance of the policy. This is despite the fact that on parallel supercomputers, because of the problems associated with demand paging, executing jobs are typically allocated enough memory so that their entire address space is memory-resident. In this paper, we examine the impact of job memory requirements on the performance of gang-scheduling policies. We first present an analysis of the memory-usage characteristics of jobs in the production workload on the Cray T3E at the San Diego Supercomputer Center. We also characterize the memory usage of some of the applications that form part of the workload on the LLNL ASCI supercomputer. Next, we examine the issue of long-term scheduling on MPPs, i.e., we study policies for deciding which jobs among a set of competing jobs should be allocated memory and thus should be allowed to execute on the processors of the system. Using trace-driven simulation, we evaluate the impact of using different long-term scheduling policies on the overall performance of Distributed Hierarchical Control (DHC), a gang-scheduling policy that has been studied extensively in the research literature.