Proceedings of the 14th international conference on Supercomputing
Semicoarsening Multigrid on Distributed Memory Machines
SIAM Journal on Scientific Computing
Time, clocks, and the ordering of events in a distributed system
Communications of the ACM
Validation of Dimemas Communication Model for MPI Collective Operations
Proceedings of the 7th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface
A framework for performance modeling and prediction
Proceedings of the 2002 ACM/IEEE conference on Supercomputing
HINT: A new way to measure computer performance
HICSS '95 Proceedings of the 28th Hawaii International Conference on System Sciences
How to use SimPoint to pick simulation points
ACM SIGMETRICS Performance Evaluation Review - Special issue on tools for computer architecture research
International Journal of High Performance Computing Applications
Performance prediction with skeletons
Cluster Computing
Parallelism profiling and wall-time prediction for multi-threaded applications
Proceedings of the 4th ACM/SPEC International Conference on Performance Engineering
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Accurate prediction of parallel applications' performance is becoming increasingly complex. We seek to characterize the behavior of message-passing applications by extracting a signature to predict the performance in different target systems. We have developed a tool we called Parallel Application Signature for Performance Prediction (PAS2P) that strives to describe an application based on its behavior. Based on the application's message-passing activity, we have been able to identify and extract representative phases, with which we created a signature. We have experimented using scientific applications and we predicted the execution times on multicore architectures with an average accuracy of over 97%.