The actor model has already proven itself as an interesting concurrency model that avoids issues such as deadlocks and race conditions by construction, and thus facilitates concurrent programming. The tradeoff is that it sacrifices expressiveness and efficiency especially with respect to data parallelism. However, many standard solutions to computationally expensive problems employ data parallel algorithms for better performance on parallel systems.

We identified three problems that inhibit the use of data-parallel algorithms within the actor model. Firstly, one of the main properties of the actor model, the fact that no data is shared, is one of the most severe performance bottlenecks. Especially the fact that shared state can not be read truly in parallel. Secondly, the actor model on its own does not provide a mechanism to specify extra synchronization conditions on batches of messages which leads to event-level data-races. And lastly, programmers are forced to write code in a continuation-passing style (CPS) to handle typical request-response situations. However, CPS breaks the sequential flow of the code and is often hard to understand, which increases complexity and lowers maintainability.

We proposes synchronization views to solve these three issues without compromising the semantic properties of the actor model. Thus, the resulting concurrency model maintains deadlock-freedom, avoids low-level race conditions, and keeps the semantics of macro-step execution.
Original languageEnglish
Title of host publicationProceedings of the 17th ACM SIGPLAN symposium on Principles and Practice of Parallel Programming
Number of pages2
ISBN (Print)978-1-4503-1160-1
Publication statusPublished - Feb 2012
EventUnknown -
Duration: 1 Feb 2012 → …

Publication series

NameProceedings of the 17th ACM SIGPLAN symposium on Principles and Practice of Parallel Programming


Period1/02/12 → …

    Research areas

  • actor model, synchronization, data parallelism

ID: 2127955