Some applications in science and engineering consist of a main job that invokes, or drives, other jobs. For example, a server process may receive a request, then invoke a workflow of stand-alone scripts or executables to handle the request, and then generate the final response. Java?s Runtime.exec() function allows jobs to be invoked from within a master Java program. However, these jobs are usually restricted to the same machine. If the number of jobs in the workflow is large, then it can be desirable to load balance the workload across different servers to maximize throughput.

We describe the design and implementation of the Trellis Driver, a newly-developed Java module that runs jobs using TrellisDriver.exec()and allows jobs to be scheduled across clusters and metacomputers (i.e., aggregations of servers). Using a Java-based bioinformatics application as a case study, we evaluate the performance improvement Trellis Driver offers through workflow parallelism.