Highly efficient gang scheduling implementation
SC '98 Proceedings of the 1998 ACM/IEEE conference on Supercomputing
A Gang-Scheduling System for ASCI Blue-Pacific
HPCN Europe '99 Proceedings of the 7th International Conference on High-Performance Computing and Networking
STORM: lightning-fast resource management
Proceedings of the 2002 ACM/IEEE conference on Supercomputing
Proceedings of the 2003 ACM/IEEE conference on Supercomputing
System noise, OS clock ticks, and fine-grained parallel applications
Proceedings of the 19th annual international conference on Supercomputing
The impact of noise on the scaling of collectives: a theoretical approach
HiPC'05 Proceedings of the 12th international conference on High Performance Computing
The Impact of noise on the scaling of collectives: the nearest neighbor model
HiPC'07 Proceedings of the 14th international conference on High performance computing
jitSim: a simulator for predicting scalability of parallel applications in presence of OS jitter
EuroPar'10 Proceedings of the 16th international Euro-Par conference on Parallel processing: Part I
Self-similarity of parallel machines
Parallel Computing
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It is increasingly becoming evident that operating system interference in the form of daemon activity and interrupts contribute significantly to performance degradation of parallel applications in large clusters. An earlier theoretical study has evaluated the impact of system noise on application performance for different noise distributions [1]. Our work complements the theoretical analysis by presenting an empirical study of noise in production clusters. We designed a parallel benchmark that was used on large clusters at SanDeigo Supercomputing Center for collecting noise related data. This data was fed to a simulator that predicts the performance of collective operations using the model of [1]. We report our comparison of the predicted and the observed performance. Additionally, the tools developed in the process have been instrumental in identifying anomalous nodes that could potentially be affecting application performance if undetected.