同步数据流网络的乱序执行

D. Baudisch, J. Brandt, K. Schneider
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引用次数: 14

摘要

数据流过程网络(dpn)作为分布式和异步系统的一种方便的计算模型被引入,因为每个过程节点可以独立于其他节点工作,即不需要全局协调。同步和循环静态数据流处理网络甚至允许在编译时派生出有效的静态调度,从而允许在有效利用可用资源的情况下运行这些系统,例如在嵌入式系统中。dpn的单进程节点是基于流的计算设备,它将输入流转换为唯一定义的相应输出流,以便在有足够的输入值可用时立即计算输出流的单个值。从这个意义上说,它们与传统微处理器执行指令流有关。在本文中,我们展示了为有效使用微处理器中的多个功能单元而引入的乱序执行如何也可用于在多处理器上实现dpn。通过这种方式,在多处理器上实现DPN可以优化单个进程节点的吞吐量,正如我们的实验所示,也可以优化整个DPN的吞吐量。
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Out-Of-order execution of synchronous data-flow networks
Data flow process networks (DPNs) have been introduced as a convenient model of computation for distributed and asynchronous systems since each process node can work independently of the other nodes, i. e. without the need of a global coordination. Synchronous and cyclo-static data flow process networks even allow to derive at compile-time efficient static schedules that allow one to run these systems with an efficient use of available resources, e. g. in embedded systems. Single process nodes of DPNs are stream-based computing devices that transform input streams to uniquely defined corresponding output streams such that single values of the output streams are computed as soon as sufficient input values are available. In this sense, they are related to the execution of an instruction stream by a conventional microprocessor. In this paper, we show how out-of-order execution that has been introduced for the efficient use of multiple functional units in microprocessors can also be used for the implementation of DPNs on multiprocessors. This way, the implementation of DPNs on multiprocessors allows one to optimize the throughput of single process nodes, and as shown by our experiments, also of the entire DPN.
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