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Time-triggered Static Schedulable Dataflows for Multimedia Systems

机译:多媒体系统的时间触发静态可调度数据流

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Software-based reactive multimedia computation systems are pervasive today in desktops but also in mobile and ultra-portable devices. Most such systems offer a callback-based architecture to incorporate specific stream processing. The Synchronous Dataflow model (SDF) and its variants are appropriate for many continuous stream processing problems such as the ones involving video and audio. SDF allows for static scheduling of multi-rate processing graphs therefore enabling optimal run-time efficiency. But the SDF abstraction does not adapt well to real-time processing because it lacks the notion of time: executing non-trivial schedules of multi-rate dataflows in a time-triggered callback architecture, though possible through buffering, causes jitter, excessive latency and run-time inefficiencies. In this paper we formally describe a new Time-Triggered SDF (TTSDF) model with a static scheduling algorithm that produces periodic schedules than can be split among several callback activations, solving the above-mentioned problems. The model has the same expressiveness than SDF, in the sense that any graph computable by one model will also be computable by the other. Additionally, it enables parallelization and run time load balancing between callback activations.
机译:基于软件的反应式多媒体计算系统如今在台式机中无处不在,在移动和超便携式设备中也是如此。大多数此类系统提供基于回调的体系结构,以合并特定的流处理。同步数据流模型(SDF)及其变体适用于许多连续流处理问题,例如涉及视频和音频的问题。 SDF允许对多速率处理图进行静态调度,因此可以实现最佳的运行时效率。但是SDF抽象缺乏实时性,因为它缺乏时间概念:尽管可以通过缓冲实现,但在时间触发的回调体系结构中执行多速率数据流的非常规调度可能会导致抖动,过多的延迟和运行时效率低下。在本文中,我们正式描述了一种新的时间触发SDF(TTSDF)模型,该模型具有静态调度算法,该算法会生成周期性计划,然后将其分配给多个回调激活,从而解决上述问题。该模型具有与SDF相同的表现力,从某种意义上说,一个模型可计算的任何图也将由另一个模型计算。此外,它还可以在回调激活之间实现并行化和运行时负载平衡。

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