The Processor Working Set and its Use in Scheduling Multiprocessor Systems
IEEE Transactions on Software Engineering
Scheduling parallelizable tasks: putting it all on the shelf
SIGMETRICS '92/PERFORMANCE '92 Proceedings of the 1992 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
SIGMETRICS '94 Proceedings of the 1994 ACM SIGMETRICS conference on Measurement and modeling of computer systems
Processor allocation in multiprogrammed distributed-memory parallel computer systems
Journal of Parallel and Distributed Computing
Scheduling with implicit information in distributed systems
SIGMETRICS '98/PERFORMANCE '98 Proceedings of the 1998 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
An evaluation of parallel job scheduling for ASCI Blue-Pacific
SC '99 Proceedings of the 1999 ACM/IEEE conference on Supercomputing
ESP: a system utilization benchmark
Proceedings of the 2000 ACM/IEEE conference on Supercomputing
Improving Gang Scheduling through job performance analysis and malleability
ICS '01 Proceedings of the 15th international conference on Supercomputing
Scheduling on hierarchical clusters using malleable tasks
Proceedings of the thirteenth annual ACM symposium on Parallel algorithms and architectures
IEEE Transactions on Parallel and Distributed Systems
Highly efficient gang scheduling implementation
SC '98 Proceedings of the 1998 ACM/IEEE conference on Supercomputing
An infrastructure for efficient parallel job execution in Terascale computing environments
SC '98 Proceedings of the 1998 ACM/IEEE conference on Supercomputing
When the Herd Is Smart: Aggregate Behavior in the Selection of Job Request
IEEE Transactions on Parallel and Distributed Systems
Data parallel programming in an adaptive environment
IPPS '95 Proceedings of the 9th International Symposium on Parallel Processing
A Model for Moldable Supercomputer Jobs
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
Using Runtime Measured Workload Characteristics in Parallel Processor Scheduling
IPPS '96 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
Dynamic vs. Static Quantum-Based Parallel Processor Allocation
IPPS '96 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
Implementing Multiprocessor Scheduling Disciplines
IPPS '97 Proceedings of the Job Scheduling Strategies for Parallel Processing
Theory and Practice in Parallel Job Scheduling
IPPS '97 Proceedings of the Job Scheduling Strategies for Parallel Processing
An Integrated Approach to Parallel Scheduling Using Gang-Scheduling, Backfilling, and Migration
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
Gang scheduling for highly efficient, distributed multiprocessor systems
FRONTIERS '96 Proceedings of the 6th Symposium on the Frontiers of Massively Parallel Computation
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
Concurrency and Computation: Practice & Experience
Performance-driven processor allocation
OSDI'00 Proceedings of the 4th conference on Symposium on Operating System Design & Implementation - Volume 4
Towards a general model of the multi-criteria workflow scheduling on the grid
Future Generation Computer Systems
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Time-shared execution of parallel jobs via gang scheduling is known to yield better average response times than space sharing. We incorporate adaptive CPU/node-resource allocation to consider varying system load and to reduce fragmentation. As main innovations, our SCOJO approach provides a clear model how to adapt, and considers realistic job mixes with moldable, malleable and rigid jobs. Our adaptive SCOJO significantly decreases response times and average slowdowns, while using a lower multiprogramming level than standard gang scheduling uses best and, therefore, decreasing the memory pressure. These benefits apply though the realistic job mixes limit the flexibility in resource allocation.