Robust Workflows for Science and Engineering

Scientific workflow tools allow users to specify complex computational experiments and provide a good framework for robust science and engineering. Workflows consist of pipelines of tasks that can be used to explore the behaviour of some system, involving computations that are either performed locally or on remote computers. Robust scientific methods require the exploration of the parameter space of a system (some of which can be run in parallel on distributed resources), and may involve complete state space exploration, experimental design or numerical optimization techniques. Whilst workflow engines provide an overall framework, they have not been developed with these concepts in mind, and in general, don't provide the necessary components to implement robust workflows. In this paper we discuss Nimrod/K- a set of add in components and a new run time machine for a general workflow engine, Kepler. Nimrod/K provides an execution architecture based on the tagged dataflow concepts developed in 1980's for highly parallel machines. This is embodied in a new Kepler 'Director ' that orchestrates the execution on clusters, Grids and Clouds using many-task computing. Nimrod/K also provides a set of 'Actors ' that facilitate the various modes of parameter exploration discussed above. We demonstrate the power of Nimrod/K to solve real problems in cardiac science.