Dynamic Path Contraction for Distributed Dataflow Languages
We present a work in progress report on applying deforestation techniques to distributed dataflow programming models. We propose a novel algorithm, dynamic path contraction, that applies and reverses optimizations to a distributed dataflow application as it executes. With this algorithm, control flow is tracked by the runtime system and optimizations are determined and applied 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.