Dataflow programming in CAL—balancing expressiveness, analyzability, and implementability

Abstract

In this paper we lay out a case for the use of dataflow programming and the CAL language as a way of addressing current challenges in programming parallel hardware such as multicore systems and FPGAs. We show how the design of the CAL language balances conflicting concerns of expressiveness, analyzability, and implementability, making it a promising tool for the implementation of parallel stream processing applications. The language itself as well as the design considerations are presented and illustrated with a number of different use cases from a wide range of application domains.