Journal of Parallel and Distributed Computing
Job Characteristics of a Production Parallel Scientivic Workload on the NASA Ames iPSC/860
IPPS '95 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
A Batch Scheduler for the Intel Paragon MPP System with a Non-contiguous Node Allocation Algorithm
IPPS '96 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
Packing Schemes for Gang Scheduling
IPPS '96 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
Workload Evolution on the Cornell Theory Center IBM SP2
IPPS '96 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
The impact of spatial layout of jobs on parallel I/O performance
Proceedings of the sixth workshop on I/O in parallel and distributed systems
Job scheduling in the presence of multiple resource requirements
SC '99 Proceedings of the 1999 ACM/IEEE conference on Supercomputing
A parallel workload model and its implications for processor allocation
Cluster Computing
Predicting Queue Times on Space-Sharing Parallel Computers
IPPS '97 Proceedings of the 11th International Symposium on Parallel Processing
Production Job Scheduling for Parallel Shared Memory Systems
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
Comparing Logs and Models of Parallel Workloads Using the Co-plot Method
IPPS/SPDP '99/JSSPP '99 Proceedings of the Job Scheduling Strategies for Parallel Processing
Benchmarks and Standards for the Evaluation of Parallel Job Schedulers
IPPS/SPDP '99/JSSPP '99 Proceedings of the Job Scheduling Strategies for Parallel Processing
Scheduling for Parallel Supercomputing: A Historical Perspective of Achievable Utilization
IPPS/SPDP '99/JSSPP '99 Proceedings of the 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
The Forgotten Factor: Facts on Performance Evaluation and Its Dependence on Workloads
Euro-Par '02 Proceedings of the 8th International Euro-Par Conference on Parallel Processing
Workload Modeling for Performance Evaluation
Performance Evaluation of Complex Systems: Techniques and Tools, Performance 2002, Tutorial Lectures
A Co-Plot analysis of logs and models of parallel workloads
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Development of scheduling strategies with Genetic Fuzzy systems
Applied Soft Computing
Future Generation Computer Systems
On advantages of scheduling using genetic fuzzy systems
JSSPP'06 Proceedings of the 12th international conference on Job scheduling strategies for parallel processing
A job self-scheduling policy for HPC infrastructures
JSSPP'07 Proceedings of the 13th international conference on Job scheduling strategies for parallel processing
Workload characteristics of a multi-cluster supercomputer
JSSPP'04 Proceedings of the 10th international conference on Job Scheduling Strategies for Parallel Processing
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The analysis of workload traces from real production parallel machines can aid a wide variety of parallel processing research, providing a realistic basis for experimentation in the management of resources over an entire workload. We analyze a five-month work-load trace of an Intel Paragon machine supporting a production parallel workload at the San Diego Super-computer Center (SDSC), comparing and contrasting it with a similar workload study of an Intel iPSC/860 machine at NASA Ames NAS. Our analysis of work-load characteristics takes into account the job scheduling policies of the sites and focuses on characteristics such as job size distribution (job parallelism), resource usage, runtimes, submission patterns, and wait times. Despite fundamental differences in the two machines and their respective usage environments, we observe a number of interesting similarities with respect to job size distribution, system utilization, runtime distribution, and interarrival time distribution. We hope to gain insight into the potential use of workload traces for evaluating resource management polices at super-computing sites and for providing both real-world job streams and accurate stochastic workload models for use in simulation analysis of resource management policies.