Domain scientists synthesize different data and computing resources to solve their scientific problems. Making use of distributed execution within scientific workflows is a growing and promising way to achieve better execution performance and efficiency. This paper presents a high-level distributed execution framework, which is designed based on the distributed execution requirements identified within the Kepler community. It also discusses mechanisms to make the presented distributed execution framework easy-to-use, comprehensive, adaptable, extensible and efficient.
['Jianwu Wang', 'Ilkay Altintas', 'Chad Berkley', 'Lucas Gilbert', 'Matthew B. Jones']
A High-Level Distributed Execution Framework for Scientific Workflows