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Expressing and Composing Actors for Deterministic and Scalable Programming in Cloud

机译:表达和组成Actor以进行云中的确定性和可扩展编程

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Actor model is an asynchronous message-passing model for fine-grained concurrency and distributed memory applications. However, it is inherently non-deterministic due to low-level synchronization primitives such as send and receive, leading to high-complexity and error-prone code when programming deterministic applications expressed by actors. In order to to support deterministic actor programming, this paper proposes a high-level programming model named distask. The core solution is to express complex synchronization in a simple and deterministic pattern by introducing features of functional programming. In detail, we design a set of composing operators on distasks in several pre-defined patterns called synchronization strategies. A distask can be composed of other distasks in a deterministic manner instead of non-deterministic communication within original actors. In addition, automatic distribution, scalability and fault handing features are supported to adapt to dynamic Cloud environment. We have implemented distask in a system called UniAS. The implementation language is Erlang, an actor-based industrial language. It is readily applied to several vital distributed memory applications with little compromise of performance.
机译:Actor模型是用于细粒度并发和分布式内存应用程序的异步消息传递模型。但是,由于诸如发送和接收之类的低级同步原语,它本质上是不确定的,从而导致在对参与者表示的确定性应用程序进行编程时会导致高复杂度和易于出错的代码。为了支持确定性参与者编程,本文提出了一种高级编程模型,称为distask。核心解决方案是通过引入函数式编程的功能,以简单而确定的模式表达复杂的同步。详细地说,我们以几种预先定义的模式(称为同步策略)来设计一组组成任务的任务。一个混乱可以用确定性的方式由其他混乱组成,而不是由原始参与者之间的不确定性通信组成。此外,还支持自动分发,可伸缩性和故障处理功能,以适应动态云环境。我们已经在称为UniAS的系统中实现了任务分离。实现语言是基于角色的工业语言Erlang。它可以轻松地应用于几种重要的分布式内存应用程序,而不会影响性能。

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