Efficient and extensible algorithms for multi query optimization
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
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Proceedings of the 2001 ACM/IEEE conference on Supercomputing
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IEEE Transactions on Parallel and Distributed Systems
Improving Performance of Multiple Sequence Alignment Analysis in Multi-Client Environments
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
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CCGRID '01 Proceedings of the 1st International Symposium on Cluster Computing and the Grid
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IPDPS '00 Proceedings of the 14th International Symposium on Parallel and Distributed Processing
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Journal of Parallel and Distributed Computing
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ICCS '09 Proceedings of the 9th International Conference on Computational Science: Part I
MT-clustalW: multithreading multiple sequence alignment
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
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This paper addresses the efficient execution of a Multiple Sequence Alignment (MSA) method, in particular the progressive alignment-based CLUSTAL W algorithm, on a cluster of workstations. We describe a scalable component-based implementation of CLUSTAL W program targeting distributed memory machines and multiple query workloads. We look at the effect of data caching on the performance of the data server. We present a distributed, persistent cache approach for caching intermediate results for reuse in subsequent or concurrent queries. Our initial results show that the cache-enabled CLUSTAL W program scales well on a cluster of workstations.