Efficient execution of multiple query workloads in data analysis applications
Proceedings of the 2001 ACM/IEEE conference on Supercomputing
Processing large-scale multi-dimensional data in parallel and distributed environments
Parallel Computing - Parallel data-intensive algorithms and applications
Distributed Computing with Load-Managed Active Storage
HPDC '02 Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing
Language and Compiler Support for Adaptive Applications
Proceedings of the 2004 ACM/IEEE conference on Supercomputing
Compiler Support for Exploiting Coarse-Grained Pipelined Parallelism
Proceedings of the 2003 ACM/IEEE conference on Supercomputing
A Services Oriented Framework for Next Generation Data Analysis Centers
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 10 - Volume 11
Supporting dynamic migration in tightly coupled grid applications
Proceedings of the 2006 ACM/IEEE conference on Supercomputing
Supporting fault-tolerance in streaming grid applications
Proceedings of the 12th ACM SIGPLAN symposium on Principles and practice of parallel programming
Self-Adaptive Configuration of Visualization Pipeline Over Wide-Area Networks
IEEE Transactions on Computers
P2P file sharing for P2P computing
Multiagent and Grid Systems - Content management and delivery through P2P-based content networks
Web-Based Visualization of Atmospheric Nucleation Processes Using Java3D
CCGRID '09 Proceedings of the 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid
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Johns Hopkins Medical InstitutionsRecent research on programming models for developing applications in the Grid has proposed component-based models as a viable approach, in which an application is composed of multiple interacting computational objects. We have been developing a framework, called filter-stream programming, for building data-intensive applications that query, analyze and manipulate very large data sets in a distributed environment. In this model, the processing structure of an application is represented as a set of processing units, referred to as filters. In this paper, we develop the problem of scheduling instances of a filter group. A filter group is a set of filters collectively performing a computation for an application. In particular, we seek the answer to the following question: should a new instance be created, or an existing one reused? We experimentally investigate the effects of instantiating multiple filter groups on performance under varying application characteristics.