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An Efficient Streaming Star Network for Multi-core Parallel DSP Processor

机译:适用于多核并行DSP处理器的高效流星型网络

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As more and more computing components are integrated into one digital signal processing (DSP) system to achieve high computing power by executing tasks in parallel, it is soon observed that the inter-processor and processor to memory communication overheads become the performance bottleneck and limit the scalability of a multi-processor platform. For chip multiprocessor (CMP) DSP systems targeting on predictable computing, an appreciation of the communication characteristics is essential to design an efficient interconnection architecture and improve performance. This paper presents a Star network designed for the ePUMA multi-core DSP processor based on analysis of the network communication models. As part of ePUMA's multi-layer interconnection network, the Star network handles core to off-chip memory communications for kernel computing on slave processors. The network has short setup latency, easy multiprocessor synchronization, rich memory addressing patterns, and power efficient streaming data transfer. The improved network efficiency is evaluated in comparison with a previous study.
机译:随着越来越多的计算组件集成到一个数字信号处理(DSP)系统中,以通过并行执行任务来实现高计算能力,很快就会发现,处理器间和处理器到内存的通信开销已成为性能瓶颈,并限制了性能。多处理器平台的可伸缩性。对于以可预测计算为目标的芯片多处理器(CMP)DSP系统,对通信特性的了解对于设计高效的互连体系结构和提高性能至关重要。本文基于对网络通信模型的分析,提出了一种专为ePUMA多核DSP处理器设计的Star网络。作为ePUMA多层互连网络的一部分,Star网络处理核心到芯片外的内存通信,以便在从属处理器上进行内核计算。该网络具有较短的设置等待时间,轻松的多处理器同步,丰富的内存寻址模式以及省电的流数据传输。与以前的研究相比,评估了提高的网络效率。

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