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Port Based Actor Model with Kahn Process Network Model and Decidable Dataflow Model

机译:具有Kahn过程网络模型和可确定数据流模型的基于端口的Actor模型

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摘要

This paper proposes a transitional actor model from legacy code to decidable dataflow. In addition, the proposed actor model provides dynamic behavior and top down design with static analysis such as deadlock detection and buffer memory size computation by combining Kahn process network (KPN) model and decidable dataflow (DCDF) model. In the proposed model, each port can have its own model of computation, which is different from the existing actor based models, so that it is called port based actor (PBA) model. Each port has either Kahn process network model or decidable dataflow model. A port group for KPN ports is introduced to specify KPN ports that are internally related. The proposed port based actor model is a generalized actor model extended from constant rate dataflow with intermediate ports (CRDF-IP) in which through the intermediate ports, an actor can consume and produce samples arbitrary times per execution. The decomposition of a PBA graph into DCDF graphs allows to apply static analysis, scheduling, and code generation methods developed for DCDF model. This paper explains formal definitions and static analysis for PBA model. Moreover, scheduling and efficient code generation methods are also explained. To validate that the proposed model works, PBA model has been implemented and an H.263 video encoder algorithm is specified and synthesized in PBA model.
机译:本文提出了一个从遗留代码到可判定数据流的过渡参与者模型。此外,拟议的参与者模型通过结合Kahn流程网络(KPN)模型和可判定数据流(DCDF)模型,为动态行为和自上而下的设计提供了静态分析,例如死锁检测和缓冲存储器大小计算。在提出的模型中,每个端口都可以具有自己的计算模型,该模型不同于现有的基于角色的模型,因此将其称为基于端口的角色(PBA)模型。每个端口都有Kahn流程网络模型或可确定的数据流模型。引入了KPN端口的端口组,以指定内部相关的KPN端口。提出的基于端口的参与者模型是从具有中间端口的恒定速率数据流(CRDF-IP)扩展而来的广义参与者模型,其中通过中间端口,参与者可以在每次执行中消耗和产生任意次数的样本。将PBA图分解为DCDF图,可以应用为DCDF模型开发的静态分析,调度和代码生成方法。本文解释了PBA模型的形式定义和静态分析。此外,还说明了调度和有效的代码生成方法。为了验证所提出的模型的有效性,已经实现了PBA模型,并在PBA模型中指定并合成了H.263视频编码器算法。

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