Ring-Mesh：一种可扩展的高性能众核加速器方法
Ring-Mesh: A Scalable and High-Performance Approach for Manycore Accelerators
摘要：
有越来越多的作品解决快速，可扩展的解决方案，为越来越多的新型应用程序的设计挑战。近来，许多解决方案旨在提高处理元件能力以加速机器学习应用领域的执行。然而，只有少数的工作集中在互连子系统作为一个潜在的性能改善的来源。将多个内核包装在一起提供了出色的并行性，但它带来了其他挑战（例如，适当的互连）。需要可扩展的、功率感知的互连来支持这种数量不断增长的处理元件以及现代应用。在本文中，我们提出了一个可扩展的和节能的片上网络架构融合的优势，环以及2D网格，而不使用任何网桥路由器，以提供高性能。动态适应机制允许更好地适应应用需求。仿真结果显示，与流行的2D-mesh相比，在多个统计流量模式场景下进行测试时，功耗效率高（连接1024个核心可节省高达141.3%），吞吐量增长2倍（平均），可扩展性更好（最多1024个处理元件）。
英文摘要：
There are increasing number of works addressing the design challenges of fast, scalable solutions for the growing number of new type of applications. Recently, many of the solutions aimed at improving processing element capabilities to speed up the execution of machine learning application domain. However, only a few works focused on the interconnection subsystem as a potential source of performance improvement. Wrapping many cores together offer excellent parallelism, but it brings other challenges (e.g., adequate interconnections). Scalable, power-aware interconnects are required to support such a growing number of processing elements, as well as modern applications. In this paper, we propose a scalable and energy efficient Network-on-Chip architecture fusing the advantages of rings as well as the 2D-mesh without using any bridge router to provide high-performance. A dynamic adaptation mechanism allows to better adapt to the application requirements. Simulation results show efficient power consumption (up to 141.3% saving for connecting 1024 cores), 2x (on average) throughput growth with better scalability (up to 1024 processing elements) compared to popular 2D-mesh while tested in multiple statistical traffic pattern scenarios.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
