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Introducing Distributed Dynamic Data-intensive (D3) Science: Understanding Applications and Infrastructure

, , , and . Concurrency and Computation: Practice and Experience, (2017)
DOI: 10.1002/cpe.4032

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NEKTAR, SPICE and Vortonics: using federated grids for large scale scientific applications., , , , , , and . CLADE, page 34-42. IEEE Computer Society, (2006)Application skeletons: Construction and use in eScience., , , and . Future Gener. Comput. Syst., (2016)Energy landscape analysis for regulatory RNA finding using scalable distributed cyberinfrastructure., , , , and . Concurr. Comput. Pract. Exp., 23 (17): 2292-2304 (2011)Asynchronous Execution of Heterogeneous Tasks in AI-coupled HPC Workflows., , and . CoRR, (2022)RAPTOR: Ravenous Throughput Computing., , and . CCGRID, page 595-604. IEEE, (2022)Building gateways for life-science applications using the dynamic application runtime environment (DARE) framework., , and . TG, page 38:1-38:8. ACM, (2011)GRENDL: grid enabled distribution and control for Laptop Orchestras., , , , and . SIGGRAPH Posters, page 84:1. ACM, (2010)Big Data, Simulations and HPC Convergence., , , , and . WBDB, volume 10044 of Lecture Notes in Computer Science, page 3-17. Springer, (2015)Conceptualizing a Computing Platform for Science Beyond 2020: To Cloudify HPC, or HPCify Clouds?, and . CLOUD, page 808-810. IEEE Computer Society, (2017)Efficient Runtime Environment for Coupled Multi-physics Simulations: Dynamic Resource Allocation and Load-Balancing., , , , and . CCGRID, page 349-358. IEEE Computer Society, (2010)