Dynamic Path Contraction for Distributed, Dynamic Dataflow Languages

We present a work in progress report on applying deforestation to distributed, dynamic dataflow programming models. We propose a novel algorithm, dynamic path contraction, that applies and reverses optimizations to a distributed dataflow application as the program executes. With this algorithm, data and control flow is tracked by the runtime system used to identify potential optimizations as the system is running. We demonstrate and present preliminary results regarding this technique on an actor-based distributed programming model, Lasp, implemented on the Erlang virtual machine