Journal of Parallel and Distributed Computing - Special issue on scalability of parallel algorithms and architectures
A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs
SIAM Journal on Scientific Computing
Using MPI-2: Advanced Features of the Message Passing Interface
Using MPI-2: Advanced Features of the Message Passing Interface
Proceedings of the 2001 ACM/IEEE conference on Supercomputing
Data and Metadata Collections for Scientific Applications
HPCN Europe 2001 Proceedings of the 9th International Conference on High-Performance Computing and Networking
High-performance scientific data management system
Journal of Parallel and Distributed Computing
A Peer-to-Peer Replica Location Service Based on a Distributed Hash Table
Proceedings of the 2004 ACM/IEEE conference on Supercomputing
Wide Area Data Replication for Scientific Collaborations
GRID '05 Proceedings of the 6th IEEE/ACM International Workshop on Grid Computing
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In the distributed computing environment, many large-scale scientific applications are irregular applications which perform their computation and I/O on an irregularly discretized mesh. However, most of the previous work in the area of irregular applications focuses mainly on the local environments. In distributed computing environments, since many remotely located scientists should share the data to produce useful results, providing a consistent data replication mechanism to minimize the remote data access time is a critical issue in achieving high-performance bandwidth. We have developed a replication software architecture(RSA) that enables the geographically distributed scientists to easily replicate irregular computations with minimum overheads, while safely sharing largescale data sets to produce useful results. Since RSA uses database support to store the data-related and computational-related metadata, it can easily be ported to any computing environments. In this paper, we describe the design and implementation of RSA for irregular applications and present performance results on Linux clusters.