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Buffer Capacity Computation for Throughput Constrained Streaming Applications with Data-Dependent Inter-Task Communication

机译:具有数据相关任务间通信的吞吐量受限流应用程序的缓冲区容量计算

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摘要

Streaming applications are often implemented as task graphs, in which data is communicated from task to task over buffers. Currently, techniques exist to compute buffer capacities that guarantee satisfaction of the throughput constraint if the amount of data produced and consumed by the tasks is known at design-time. However, applications such as audio and video decoders have tasks that produce and consume an amount of data that depends on the decoded stream. This paper introduces a dataflow model that allows for data-dependent communication, together with an algorithm that computes buffer capacities that guarantee satisfaction of a throughput constraint. The applicability of this algorithm is demonstrated by computing buffer capacities for an H.263 video decoder.
机译:流应用程序通常被实现为任务图,其中数据通过缓冲区在任务之间传递。当前,存在计算缓冲容量的技术,如果在设计时已知任务产生和消耗的数据量,则可以保证满足吞吐量约束。但是,诸如音频和视频解码器之类的应用程序具有产生和消耗大量数据的任务,这些数据取决于解码后的流。本文介绍了一种数据流模型,该模型允许进行与数据相关的通信,并提供一种算法,该算法计算可确保满足吞吐量约束的缓冲区容量。通过为H.263视频解码器计算缓冲区容量来证明该算法的适用性。

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