PVM: a framework for parallel distributed computing
Concurrency: Practice and Experience
An introduction to parallel algorithms
An introduction to parallel algorithms
Parallel programming with MPI
Simulation Modeling and Analysis
Simulation Modeling and Analysis
Distributed Systems: Concepts and Design
Distributed Systems: Concepts and Design
Reducing the variance of point to point transfers in the IBM 9076 parallel computer
Proceedings of the 1994 ACM/IEEE conference on Supercomputing
Proceedings of the 11 IPPS/SPDP'99 Workshops Held in Conjunction with the 13th International Parallel Processing Symposium and 10th Symposium on Parallel and Distributed Processing
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
MPI: A Message-Passing Interface Standard
MPI: A Message-Passing Interface Standard
Proceedings of the 2003 ACM/IEEE conference on Supercomputing
Analysis of microbenchmarks for performance tuning of clusters
CLUSTER '04 Proceedings of the 2004 IEEE International Conference on Cluster Computing
Right-weight kernels: an off-the-shelf alternative to custom light-weight kernels
ACM SIGOPS Operating Systems Review
Proceedings of the 2007 ACM/IEEE conference on Supercomputing
Characterizing the Influence of System Noise on Large-Scale Applications by Simulation
Proceedings of the 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis
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
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The ability to understand the factors contributing to parallel program performance are vital for understanding the impact of machine parameters on the performance of specific applications. We propose a methodology for analyzing the performance characteristics of parallel programs based on message-passing traces of their execution on a set of processors. Using this methodology, we explore how perturbations in both single processor performance and the messaging layer impact the performance of the traced run. This analysis provides a quantitative description of the sensitivity of applications to a variety of performance parameters to better understand the range of systems upon which an application can be expected to perform well. These performance parameters include operating system interference and variability in message latencies within the interconnection network layer.