Models and languages for parallel computation
ACM Computing Surveys (CSUR)
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
Journal of Computational and Applied Mathematics
A Programming Methodology for Dual-Tier Multicomputers
IEEE Transactions on Software Engineering - Special issue on architecture-independent languages and software tools for parallel processing
Parallel software abstractions for structured adaptive mesh methods
Journal of Parallel and Distributed Computing
ORT: a communication library for orthogonal processor groups
Proceedings of the 2001 ACM/IEEE conference on Supercomputing
Approaches for Integrating Task and Data Parallelism
IEEE Concurrency
Bandwidth-Efficient Collective Communication for Clustered Wide Area Systems
IPDPS '00 Proceedings of the 14th International Symposium on Parallel and Distributed Processing
Exploiting Hierarchy in Parallel Computer Networks to Optimize Collective Operation Performance
IPDPS '00 Proceedings of the 14th International Symposium on Parallel and Distributed Processing
MPICH-G2: a Grid-enabled implementation of the Message Passing Interface
Journal of Parallel and Distributed Computing - Special issue on computational grids
Optimizing Parallel Applications for Wide-Area Clusters
IPPS '98 Proceedings of the 12th. International Parallel Processing Symposium on International Parallel Processing Symposium
A programming model for block-structured scientific calculations on smp clusters
A programming model for block-structured scientific calculations on smp clusters
Irregular Coarse-Grain Data Parallelism under LPARX
Scientific Programming
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Many parallel applications from scientific computing use MPI global communication operations to collect or distribute data. Since the execution times of these communication operations increase with the number of participating processors, scalability problems might occur. In this article, we show for different MPI implementations how the execution time of global communication operations can be significantly improved by a restructuring based on orthogonal processor structures. As platform, we consider a dual Xeon cluster, a Beowulf cluster and a Cray T3E with different MPI implementations. We show that the execution time of operations like MPI_Bcast() or MPI_Allgather() can be reduced by 40% and 70% on the dual Xeon cluster and the Beowulf cluster. But also on a Cray T3E a significant improvement can be obtained by a careful selection of the processor groups. We demonstrate that the optimized communication operations can be used to reduce the execution time of data parallel implementations of complex application programs without any other reordering of the computation and communication structure.