Flexible and Efficient Workflow Deployment of Data-Intensive Applications On Grids With MOTEUR

Workflows offer a powerful way to describe and deploy applications on grid infrastructures. Many workflow management systems have been proposed but there is still a lack of a system that would allow both a simple description of the dataflow of the application and an efficient execution on a grid platform. In this paper, we study the requirements of such a system, underlining the need for well-defined data composition strategies on the one hand and for a fully parallel execution on the other hand. As combining those features is not straight forward, we then propose algorithms to do so and we describe the design and implementation of MOTEUR, a workflow engine that fulfills those requirements. Performance results and overhead quantification are shown to evaluate MOTEUR with respect to existing comparable workflow systems on a production grid.