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首页> 美国卫生研究院文献>Sensors (Basel Switzerland) >FPGA-Based High-Performance Embedded Systems for Adaptive Edge Computing in Cyber-Physical Systems: The ARTICo3 Framework
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FPGA-Based High-Performance Embedded Systems for Adaptive Edge Computing in Cyber-Physical Systems: The ARTICo3 Framework

机译：基于FPGA的高性能嵌入式系统用于网络物理系统中的自适应边缘计算：ARTICo3框架

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摘要

Cyber-Physical Systems are experiencing a paradigm shift in which processing has been relocated to the distributed sensing layer and is no longer performed in a centralized manner. This approach, usually referred to as Edge Computing, demands the use of hardware platforms that are able to manage the steadily increasing requirements in computing performance, while keeping energy efficiency and the adaptability imposed by the interaction with the physical world. In this context, SRAM-based FPGAs and their inherent run-time reconfigurability, when coupled with smart power management strategies, are a suitable solution. However, they usually fail in user accessibility and ease of development. In this paper, an integrated framework to develop FPGA-based high-performance embedded systems for Edge Computing in Cyber-Physical Systems is presented. This framework provides a hardware-based processing architecture, an automated toolchain, and a runtime to transparently generate and manage reconfigurable systems from high-level system descriptions without additional user intervention. Moreover, it provides users with support for dynamically adapting the available computing resources to switch the working point of the architecture in a solution space defined by computing performance, energy consumption and fault tolerance. Results show that it is indeed possible to explore this solution space at run time and prove that the proposed framework is a competitive alternative to software-based edge computing platforms, being able to provide not only faster solutions, but also higher energy efficiency for computing-intensive algorithms with significant levels of data-level parallelism.
机译：网络物理系统正在经历一种范式转换，其中处理已重新分配到分布式传感层，并且不再以集中方式执行。这种方法通常称为边缘计算，要求使用硬件平台，这些平台能够管理对计算性能稳定增长的要求，同时保持能效和与物理世界交互所带来的适应性。在这种情况下，与智能电源管理策略结合使用的基于SRAM的FPGA及其固有的运行时可重配置性是合适的解决方案。但是，它们通常在用户可访问性和易于开发方面均失败。在本文中，提出了一个集成框架，可为基于网络的物理系统中的边缘计算开发基于FPGA的高性能嵌入式系统。该框架提供了基于硬件的处理体系结构，自动工具链和运行时，可以根据高级系统描述透明地生成和管理可重新配置的系统，而无需其他用户干预。此外，它为用户提供了对动态调整可用计算资源的支持，以在由计算性能，能耗和容错能力定义的解决方案空间中切换体系结构的工作点。结果表明，确实有可能在运行时探索此解决方案空间，并证明所提出的框架是基于软件的边缘计算平台的竞争替代品，不仅能够提供更快的解决方案，而且能够为计算提供更高的能源效率，具有大量数据级别并行性的密集算法。

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