Deng Tiantai, Crookes Danny, Woods Roger, Siddiqui Fahad
Department of Electronics and Electrical Engineering, The University of Sheffield, Sheffield S1 3JD, UK.
School of Electronics, Electrical Engineering and Computer Science, Queen's University Belfast, Belfast BT7 1NN, UK.
J Imaging. 2022 Feb 11;8(2):42. doi: 10.3390/jimaging8020042.
Developing Field Programmable Gate Array (FPGA)-based applications is typically a slow and multi-skilled task. Research in tools to support application development has gradually reached a higher level. This paper describes an approach which aims to further raise the level at which an application developer works in developing FPGA-based implementations of image and video processing applications. The starting concept is a system of streamed soft coprocessors. We present a set of soft coprocessors which implement some of the key abstractions of Image Algebra. Our soft coprocessors are designed for easy chaining, and allow users to describe their application as a dataflow graph. A prototype implementation of a development environment, called SCoPeS, is presented. An application can be modified even during execution without requiring re-synthesis. The paper concludes with performance and resource utilization results for different implementations of a sample algorithm. We conclude that the soft coprocessor approach has the potential to deliver better performance than the soft processor approach, and can improve programmability over dedicated HDL cores for domain-specific applications while achieving competitive real time performance and utilization.
开发基于现场可编程门阵列（FPGA）的应用程序通常是一项缓慢且需要多种技能的任务。支持应用程序开发的工具研究已逐渐达到更高水平。本文描述了一种旨在进一步提高应用程序开发人员在开发基于FPGA的图像和视频处理应用程序实现时的工作水平的方法。起始概念是一个流式软协处理器系统。我们展示了一组实现图像代数一些关键抽象的软协处理器。我们的软协处理器设计用于轻松链接，并允许用户将其应用程序描述为数据流图。展示了一个名为SCoPeS的开发环境的原型实现。即使在执行期间，应用程序也可以修改而无需重新合成。本文最后给出了示例算法不同实现的性能和资源利用结果。我们得出结论，软协处理器方法有可能提供比软处理器方法更好的性能，并且对于特定领域的应用程序，与专用HDL内核相比，可以提高可编程性，同时实现具有竞争力的实时性能和利用率。
