A general purpose high-performance distributed execution engine for coarse-grained data-parallel applications is proposed that allows developers to easily create large-scale distributed applications without requiring them to master concurrency techniques beyond being able to draw a graph of the data-dependencies of their algorithms. Based on the graph, a job manager intelligently distributes the work load so that the resources of the execution engine are used efficiently. During runtime, the job manager (or other entity) can automatically modify the graph to improve efficiency. The modifications are based on runtime information, topology of the distributed execution engine, and/or the distributed application represented by the graph.