具有高吞吐量NoC的智能任务调度程序,用于实时移动目标识别SoC

K. Lee, Junyoung Park, Injoon Hong, H. Yoo
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引用次数: 4

摘要

为了减少片上网络(NoC)的网络拥塞,提高多核系统的吞吐量,实现快速准确的目标识别,提出了智能任务调度(ITS)和避免拥塞灵活路由(CAFeR)技术。ITS预测下一帧的通信模式,并智能地将任务分配给消费者核心。它还自适应控制NoC中各链路的缓冲阈值,支持CAFeR,以提高数据包的事务吞吐量,减少数据包的通信拥塞。由于提出的ITS具有91.4%的预测精度和CAFeR,总体延迟降低了50.2%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligent task scheduler with high throughput NoC for real-time mobile object recognition SoC
An Intelligent Task Scheduler (ITS) together with Congestion-avoiding Flexible Routing (CAFeR) are proposed to minimize network congestion of network-on-chip (NoC), so as to improve the throughput of multi-core system for fast and accurate object recognition. The ITS predicts the communication pattern of next frame and intelligently assigns tasks to consumer cores. It also adaptively controls buffer threshold of each link in NoC to support CAFeR to enhance packet transaction throughput, which enables packets to communicate with less congestion. Thanks to the proposed ITS with 91.4% of prediction accuracy and CAFeR, the overall latency is reduced by 50.2%.
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