Short Papers
Orbit, Control Operator, Query Processing, Iteration
Various scientific applications compute iterations on a huge set of input data. Examples include parameter sweep, which processes the same model through hundreds or thousands of input data, scientific visualization and numeric methods to solve hyperbolic equations. The state of the art for executing such applications is to model them as scientific workflows and to run them in HPC infrastructure. The execution model strives to combine pipeline parallelism, among activities of the workflow, with intra-workflow parallelism over data partitions, both of them subjected to workflow characteristics. In such scenario, the scientific workflow execution model can be approximated to that of parallel query processing. In fact, database groups at LNCC and COPPE have implemented parallel workflow engines, QEF and Chiron, under this assumption. In order to full integrate iterations within a data processing execution model, an extension is required to treat the loop control operator. In this paper we investigate the problem of efficiently executing scientific workflows that include iterations. We introduce Orbit which is a generic operator to manage the data flow in an iterative procedure. An execution model centered into Orbit is proposed including a centralized and parallelized modes. Additionally, two new execution strategies are investigated: first-tuple-first, first-iteration-first. We have obtained initial results that evaluate the different execution strategies in both centralized and parallel modes.
Douglas Ericson de Oliveira, Fábio Porto