LogP: towards a realistic model of parallel computation
PPOPP '93 Proceedings of the fourth ACM SIGPLAN symposium on Principles and practice of parallel programming
The communication challenge for MPP: Intel Paragon and Meiko CS-2
Parallel Computing
LogGP: incorporating long messages into the LogP model for parallel computation
Journal of Parallel and Distributed Computing
MagPIe: MPI's collective communication operations for clustered wide area systems
Proceedings of the seventh ACM SIGPLAN symposium on Principles and practice of parallel programming
Adaptive parallel computing on heterogeneous networks with mpC
Parallel Computing
Assessing Fast Network Interfaces
IEEE Micro
Fast Measurement of LogP Parameters for Message Passing Platforms
IPDPS '00 Proceedings of the 15 IPDPS 2000 Workshops on Parallel and Distributed Processing
Efficient collective communication in distributed heterogeneous systems
Journal of Parallel and Distributed Computing
Scheduling Algorithms for Efficient Gather Operations in Distributed Heterogeneous Systems
ICPP '00 Proceedings of the 2000 International Workshop on Parallel Processing
Commodity cluster-based parallel processing of hyperspectral imagery
Journal of Parallel and Distributed Computing
HeteroMPI: Towards a message-passing library for heterogeneous networks of computers
Journal of Parallel and Distributed Computing
ICPADS '06 Proceedings of the 12th International Conference on Parallel and Distributed Systems - Volume 2
Data Partitioning with a Functional Performance Model of Heterogeneous Processors
International Journal of High Performance Computing Applications
Performance analysis of MPI collective operations
Cluster Computing
Accurate Heterogeneous Communication Models and a Software Tool for Their Efficient Estimation
International Journal of High Performance Computing Applications
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Analytical predictive communication models play an important role in the optimization of communication operations in scientific applications running on computational clusters. The effectiveness of this model-based optimization strongly depends on the accuracy of the estimation of the parameters of these models. The task of accurate estimation of the model is particularly challenging for heterogeneous communication models that use a much larger number of point-to-point parameters than their homogeneous counterparts. One particular challenge occurs when the number of point-to-point parameters describing communication between a pair of processors becomes larger than the number of independent point-to-point communication experiments traditionally used for estimation of the parameters. In this paper, we address this and other related issues and propose an approach that allows us to design a set of communication experiments sufficient for the accurate and efficient estimation of the parameters of a heterogeneous communication performance model. The experiments on heterogeneous clusters demonstrate the accuracy and efficiency of the proposed solution.