面向嵌入式设备的线程感知区域高效高级综合编译器

Changsu Kim, Shinnung Jeong, Sungjun Cho, Yongwoo Lee, William J. Song, Youngsok Kim, Hanjun Kim
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引用次数: 0

摘要

在嵌入式设备市场,定制硬件平台,如专用集成电路(ASIC)和现场可编程门阵列(FPGA)由于其高性能和高能效而具有吸引力。然而,其巨大的设计成本使制造商难以及时推出新设备。高级综合(HLS)通过将服务算法自动转换为硬件逻辑,有助于显著降低设计成本;然而,目前的HLS编译器并不适合嵌入式设备,因为它们在支持来自不同外设(如传感器、执行器和网络模块)的并发事件时,无法产生区域高效的解决方案。本文提出了一种新的线程感知HLS编译器——Duro,该编译器可以生成面积高效的嵌入式设备。Duro通过新的线程感知区域成本模型在不同的调用者和线程之间共享常用的函数和操作符,从而有效地减小了逻辑大小。此外,Duro通过自动集成外设控制器和接口作为外设驱动程序,支持多种设备外设。对6个带有10个外设的嵌入式设备的实验结果表明,与采用最先进的HLS编译器生成的设计相比,Duro使嵌入式设备的面积和能量消耗分别减少了28.5%和25.3%。本工作还使用Duro实现了六个器件的FPGA原型,测量结果表明,与Raspberry Pi Zero相比,节能65.3%,计算性能略好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Thread-Aware Area-Efficient High-Level Synthesis Compiler for Embedded Devices
In the embedded device market, custom hardware platforms such as an application specific integrated circuit (ASIC) and a field programmable gate array (FPGA) are attractive thanks to their high performance and power efficiency. However, its huge design costs make it challenging for manufacturers to timely launch new devices. High-level synthesis (HLS) helps significantly reduce the design costs by automating the translation of service algorithms into hardware logics; however, current HLS compilers do not fit well to embedded devices as they fail to produce area-efficient solutions while supporting concurrent events from diverse peripherals such as sensors, actuators and network modules. This paper proposes a new thread-aware HLS compiler named Duro that produces area-efficient embedded devices. Duro shares commonly-invoked functions and operators across different callers and threads with a new thread-aware area cost model, and thus effectively reduces the logic size. Moreover, Duro supports a variety of device peripherals by automatically integrating peripheral controllers and interfaces as peripheral drivers. The experiment results of six embedded devices with ten peripherals demonstrate that Duro reduces the area and energy dissipation of embedded devices by 28.5% and 25.3% compared with the designs generated by the state-of-the-art HLS compiler. This work also implements FPGA prototypes of the six devices using Duro, and the measurement results show 65.3% energy saving over Raspberry Pi Zero with slightly better computation performance.
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