Massive High-Performance Global File Systems for Grid computing
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
Parallel job scheduling — a status report
JSSPP'04 Proceedings of the 10th international conference on Job Scheduling Strategies for Parallel Processing
A dynamic co-allocation service in multicluster systems
JSSPP'04 Proceedings of the 10th international conference on Job Scheduling Strategies for Parallel Processing
LOMARC — lookahead matchmaking for multi-resource coscheduling
JSSPP'04 Proceedings of the 10th international conference on Job Scheduling Strategies for Parallel Processing
Co-scheduling with user-settable reservations
JSSPP'05 Proceedings of the 11th international conference on Job Scheduling Strategies for Parallel Processing
Pitfalls in parallel job scheduling evaluation
JSSPP'05 Proceedings of the 11th international conference on Job Scheduling Strategies for Parallel Processing
Scheduling mixed-parallel applications with advance reservations
HPDC '08 Proceedings of the 17th international symposium on High performance distributed computing
Combining batch execution and leasing using virtual machines
HPDC '08 Proceedings of the 17th international symposium on High performance distributed computing
Scheduling mixed-parallel applications with advance reservations
Cluster Computing
Future Generation Computer Systems
Performance evaluation of bag of gangs scheduling in a heterogeneous distributed system
Journal of Systems and Software
An Analysis of Power Consumption Logs from a Monitored Grid Site
GREENCOM-CPSCOM '10 Proceedings of the 2010 IEEE/ACM Int'l Conference on Green Computing and Communications & Int'l Conference on Cyber, Physical and Social Computing
Scheduling real-time divisible loads with advance reservations
Real-Time Systems
Architecture for the next generation system management tools
Future Generation Computer Systems
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The TeraGrid is a closely linked community of diverse resources: computational, data, and experimental, e.g., the imminent very large computational system at the University of Texas, the extensive data facilities at SDSC, and the physics experiments at ORNL. As research efforts become more extensive in scope, the co-scheduling of multiple resources becomes an essential part of scientific progress. This can be at odds with the traditional management of the computational systems, where utilization, queue wait times, and expansion factors are considered paramount and anything that affects their performance is considered with suspicion. The only way to assuage concerns is with intensive investigation of the likely effects of allowing advance reservations on these performance metrics. To understand the impact, we developed a simulator that reads our actual production job log and reservation request data to investigate different scheduling scenarios. We explored the effect of reservations and policies using job log data from two different months within consecutive years and present our initial results. Results from the simulations suggest that utilization, expansion factor and queue wait time indeed can be affected negatively by significant numbers and size of reservations, but this effect can be mitigated with appropriate policies.