Modern embedded and cyber-physical systems require every day more performance, power efficiency and flexibility, to execute several profiles and functionalities targeting the ever growing adaptivity needs and preserving execution efficiency. Such requirements pushed designers towards the adoption of heterogeneous and reconfigurable substrates, which development and management is not that straightforward. Despite acceleration and flexibility are desirable in many domains, the barrier of hardware deployment and operation is still there since specific advanced expertise and skills are needed. Related challenges are effectively tackled by leveraging on automation strategies that in some cases, as in the proposed work, exploit model-based approaches. This paper is focused on the Multi-Dataflow Composer (MDC) tool, that intends to solve issues related to design, optimization and operation of coarse-grain reconfigurable hardware accelerators and their easy adoption in modern heterogeneous substrates. MDC latest features and improvements are introduced in detail and have been assessed on the so far unexplored robotics application field. A multi-profile trajectory generator for a robotic arm is implemented over a Xilinx FPGA board to show in which cases coarse-grain reconfiguration can be applied and which can be the parameters and trade-offs MDC will allow users to play with.
翻译:现代嵌入式和网络物理系统要求每天提高性能、电力效率和灵活性,以针对不断增长的适应性需求执行若干剖面和功能,并保持执行效率。这些要求促使设计者采用多种和可重新配置的子系统,而开发和管理则不是那么简单。尽管在许多领域需要加快和灵活,但硬件部署和运作的障碍仍然存在,因为需要具体的先进知识和技能。相关的挑战通过利用自动化战略得到有效解决,而自动化战略在某些情况下,如拟议工作中那样,利用基于模型的方法。本文侧重于多数据流合成器(多数据流合成器)工具,该工具旨在解决与设计、优化和操作可混凝固的可重新配置硬件加速器有关的问题,并容易在现代混集的子系统采用这些硬件加速器。MDC的最新特点和改进是详细引入的,并且已经对迄今为止尚未探索的机器人应用领域进行了评估。在Xilinx FPGA板上安装了一个多位式轨道生成器,以显示可应用的可剖面重的硬硬件再配置器的情况,并允许使用这些参数和MDRD。