A Python-based High-Level Programming Flow for CPU-FPGA Heterogeneous Systems : (Invited Paper)

Sitao Huang, Kun Wu, S. R. Chalamalasetti, Izzat El Hajj, Cong Xu, P. Faraboschi, Deming Chen
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引用次数: 0

Abstract

The fast-growing complexity of new applications and new use scenarios poses serious challenges for computing systems. Heterogeneous systems consist of different types of processors and accelerators, and provide unique combined benefits of hard-ware acceleration from each individual component. CPU-FPGA heterogeneous systems provide both programmable logic and general-purpose processors, and they have demonstrated great flexibility, performance, and efficiency. Heterogeneous systems have been created and deployed in many different applications and scenarios. However, as system complexity and application complexity grow rapidly, programming and optimizing heterogeneous systems require great manual efforts and consume a lot of time. In this work, we propose a Python-based high-level programming framework to simplify programming and optimization of CPU-FPGA heterogeneous systems. The proposed high-level operations isolate underlying hardware details from programmers and provide more optimization opportunities for the compiler.
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基于python的CPU-FPGA异构系统高级编程流程(特邀论文)
新应用程序和新使用场景的快速增长的复杂性对计算系统提出了严峻的挑战。异构系统由不同类型的处理器和加速器组成,并提供来自每个单独组件的硬件加速的独特组合优势。CPU-FPGA异构系统既提供可编程逻辑和通用处理器,也展示了极大的灵活性、性能和效率。异构系统已经被创建并部署在许多不同的应用程序和场景中。然而,随着系统复杂性和应用程序复杂性的快速增长,编程和优化异构系统需要大量的手工工作和消耗大量的时间。在这项工作中,我们提出了一个基于python的高级编程框架,以简化CPU-FPGA异构系统的编程和优化。所建议的高级操作将底层硬件细节与程序员隔离开来,并为编译器提供了更多的优化机会。
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