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The Kepler scientific workflow system enables creation, execution and sharing of workflows across a broad range of scientific and engineering disciplines while also facilitating remote and distributed execution of workflows. In this paper, we present and compare different approaches to distributed execution of workflows using the Kepler environment, including a distributed data-parallel framework using Hadoop and Stratosphere, and Cloud and Grid execution using Serpens, Nimrod/K and Globus actors. We also present real-life applications in computational chemistry, bioinformatics and computational physics to demonstrate the usage of different distributed computing capabilities of Kepler in executable workflows. We further analyze the differences of each approach and provide a guidance for their applications. [ABSTRACT FROM AUTHOR]

Abstract: One of the greatest challenges in computational chemistry is the design of enzymes to catalyze non-natural chemical reactions. We focus on harnessing the distributed parallel computational power of the Grid to automate the inside-out process of enzyme design using scientific workflow systems. This paper presents a scientific workflow based approach to facilitate the inside-out enzyme design process in the Grid execution environment by providing features such as resource consolidation, task parallelism, provenance tracking, fault tolerance and workflow reuse, which results in an automated, pipelined, efficient, extensible, stable, and easy-to-use computational process for enzyme design. [ABSTRACT FROM AUTHOR]