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Synchronization Views for Event-loop Actors

机译:事件循环参与者的同步视图

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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 nice conditions, and keeps the semantics of macro-step execution.
机译:actor模型已经证明了自己是一个有趣的并发模型,该模型避免了因构造而导致的死锁和争用条件等问题,从而简化了并发编程。代价是牺牲了表达性和效率,特别是在数据并行性方面。但是,许多解决计算量昂贵问题的标准解决方案都采用数据并行算法,以在并行系统上获得更好的性能。我们确定了三个问题,这些问题阻碍了参与者模型中数据并行算法的使用。首先,参与者模型的主要特性之一是没有数据共享,这是最严重的性能瓶颈之一。特别是共享状态无法真正并行读取的事实。其次,参与者模型本身没有提供一种机制来为成批的消息指定额外的同步条件,从而导致事件级数据争用。最后,程序员被迫以连续传递样式(CPS)编写代码以处理典型的请求-响应情况。但是,CPS破坏了代码的顺序流,并且通常很难理解,这增加了复杂性并降低了可维护性。我们提出了同步视图来解决这三个问题,同时又不影响参与者模型的语义特性。因此,最终的并发模型保持了无死锁,避免了低级别的良好条件并保留了宏步骤执行的语义。

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