Scalable Actor Networks with CAL

Abstract

Dataflow is a Model of Computation (MoC) that describes applications as networks of actors. The CAL Actor Language (CAL) is one of the programming languages for describing such actors. A downside to CAL is that the actors and their networks are rigidly defined - it is not possible to have a parametric number of ports or actions in an actor. This makes it difficult to define flexible applications or large actors without extra programmer effort.The key contribution of this paper is the addition of constructs to CAL to allow for parametric actor and network creation. These constructs include defining and using arrays and sub-arrays ports, as well as a generate statement for creating multiple similar actions. We give examples of the types of parametric applications that our new constructs enable.We use our work to demonstrate some of the limitations in dataflow tools when applied to non-trivial actors. We focus on the processing effort required to transform an actor into an intermediate representation (IR). We make the case for future research to use parametric actors to test the scaling of dataflow toolchains.CCS CONCEPTS• Theory of computation → Streaming models; • Software and its engineering → Concurrent programming languages.