Erbium: A Deterministic, Concurrent Intermediate Representation to Map Data-Flow Tasks to Scalable, Persistent Streaming Processes

International audienceTuning applications for multicore systems involve subtle concurrency concepts and target-dependent optimizations. This paper advocates for a streaming execution model, called \ER, where persistent processes communicate and synchronize through a multi-consumer multi-producer sliding window. Considering media and signal processing applications, we demonstrate the scalability and efficiency advantages of streaming compared to data-driven scheduling. To exploit these benefits in compilers for parallel languages, we propose an intermediate representation enabling the compilation of data-flow tasks into streaming processes. This intermediate representation also facilitates the application of classical compiler optimizations to concurrent programs