The interaction of parallel and sequential workloads on a network of workstations
Proceedings of the 1995 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
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
The impact of job memory requirements on gang-scheduling performance
ACM SIGMETRICS Performance Evaluation Review
Understanding the Linux Kernel
Understanding the Linux Kernel
A Case for NOW (Networks of Workstations)
IEEE Micro
Demand-Based Coscheduling of Parallel Jobs on Multiprogrammed Multiprocessors
IPPS '95 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
Dynamic Coscheduling on Workstation Clusters
IPPS/SPDP '98 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
Coscheduling under Memory Constraints in a NOW Environment
JSSPP '01 Revised Papers from the 7th International Workshop on Job Scheduling Strategies for Parallel Processing
Correlation of the paging activity of individual node programs in the SPMD execution mode
HICSS '95 Proceedings of the 28th Hawaii International Conference on System Sciences
Gang Scheduling with Memory Considerations
IPDPS '00 Proceedings of the 14th International Symposium on Parallel and Distributed Processing
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Our research is focused on keeping both local and parallel jobs together in a non-dedicated cluster or NOW (Network of Workstations) and efficiently scheduling them by means of coscheduling mechanisms. The performance of a good coscheduling policy can decrease drastically if memory requirements are not kept in mind. The overflow of the physical memory into the virtual memory usually provokes a severe performance penalty. A real implementation of a coscheduling technique for reducing the number of page faults across a non-dedicated Linux cluster is presented in this article. Our technique is based on knowledge of events obtained during execution, such as communication activity, page faults and memory size of every task. Its performance is analyzed and compared with other coscheduling algorithms.