Embedded systems continue to rapidly proliferate in diverse fields, including medical devices, autonomous vehicles, and more generally, the Internet of Things (IoT). Many embedded systems require application-specific hardware components to meet precise timing requirements within limited resource (area and energy) constraints. High-level synthesis (HLS) is an increasingly popular approach for improving the productivity of designing hardware and reducing the time/cost by using high-level languages to specify computational functionality and automatically generate hardware implementations. However, current HLS methods provide limited or no support to incorporate or utilize precise timing specifications within the synthesis and optimization process. In this paper, we present a hybrid high-level synthesis (H-HLS) framework that integrates state-based high-level synthesis (SB-HLS) with performance-driven high-level synthesis (PD-HLS) methods to enable the design and optimization of application-specific embedded systems in which timing information is explicitly and precisely defined in state-based system models. We demonstrate the results achieved by this H-HLS approach using case studies including a wearable pregnancy monitoring device, an ECG-based biometric authentication system, and a synthetic system, and compare the design space exploration results using two PD-HLS tools to show how H-HLS can provide low energy and area under timing constraints.

翻译：嵌入式系统在包括医疗设备、自动驾驶汽车以及更广泛的物联网（IoT）等众多领域中持续快速普及。许多嵌入式系统需要在有限的资源（面积和能耗）约束下，满足精确的时序要求，因此需要专用硬件组件。高级综合（HLS）是一种日益流行的技术，它通过使用高级语言指定计算功能并自动生成硬件实现，来提高硬件设计的生产力并降低时间/成本。然而，当前的HLS方法在综合与优化过程中，对纳入或利用精确时序规格的支持有限甚至缺失。本文提出了一种混合高级综合（H-HLS）框架，将基于状态的高级综合（SB-HLS）与性能驱动的高级综合（PD-HLS）方法相结合，以实现专用嵌入式系统的设计与优化——其中时序信息在以状态为基础的系统模型中被显式且精确地定义。我们通过案例研究（包括一款可穿戴式妊娠监测设备、一个基于心电图的生物特征认证系统及一个合成系统）展示了H-HLS方法所取得的成果，并对比了使用两种PD-HLS工具进行设计空间探索的结果，以说明H-HLS如何在满足时序约束的条件下实现低能耗与低面积开销。