Improving Workflows Execution on DAGMan by a Perfomance-driven Scheduling Tool

Abstract

In several scientific and business environments, the magnitude of problems require the execution of complex applications, like work-flows. Condor includes DAGMan extension in order to manage workflows. Such kind of applications are very popular because jobs can be reused and distributed. Scheduling is a central issue in the assignation of resources to workflows. It can be seen as the process of assigning the resources to the workflow's jobs in a convenient way. This work presents a performance-driven approach to make these assignments (also known as mappings). The mappings generated determine in which resources the jobs must be executed. The execution stage is delegated to the DAGMan Workflow System. This approach is compared with the standalone execution of the workflow over DAGMan. Experimental results show that the performance-driven approach improves the execution time of workflows in comparison with the standalone DAGMan approach.