论文标题
GVSOC:基于RISC-V的物联网处理器的高度可配置,快速,准确的全平面模拟器
GVSoC: A Highly Configurable, Fast and Accurate Full-Platform Simulator for RISC-V based IoT Processors
论文作者
论文摘要
在过去的几年中,物联网处理器的出现:超低功率系统(SOCS)结合了轻质和柔性的微控制器单元(MCUS),通常基于开放式ISA RISC-V核心,以及应用特定的加速器,以最大程度地提高性能和能效。总体而言,这种异质性水平需要复杂的硬件和成熟的软件堆栈来协调执行和利用平台功能。因此,使敏捷的设计空间探索成为这一新的低功耗SOC的关键资产。在这种情况下,高级模拟器在分别保留循环精度模拟器和FPGA原型的速度和设计工作方面起着至关重要的作用,同时保留了功能和时间准确性。我们提出GVSOC,这是一种可配置高度可配置的事件驱动的模拟器,将C ++模型的效率与Python配置脚本的灵活性相结合。 GVSOC是完全开源的,目的是推动基于RISC-V的高度平行和异质的IoT处理器领域的未来研究,利用了三个基本功能:基于Python的硬件描述的模块化配置,易于校准平台参数的校准,以进行准确的性能估计以及高速模拟。实验结果表明,GVSOC可以在全平台级别(处理器,内存,外围设备和iOS)上实现实用功能和性能分析以及设计探索,相对于循环精确的模拟,具有2500倍的加速模拟,误差通常低于10%,以进行性能分析。
The last few years have seen the emergence of IoT processors: ultra-low power systems-on-chips (SoCs) combining lightweight and flexible micro-controller units (MCUs), often based on open-ISA RISC-V cores, with application-specific accelerators to maximize performance and energy efficiency. Overall, this heterogeneity level requires complex hardware and a full-fledged software stack to orchestrate the execution and exploit platform features. For this reason, enabling agile design space exploration becomes a crucial asset for this new class of low-power SoCs. In this scenario, high-level simulators play an essential role in breaking the speed and design effort bottlenecks of cycle-accurate simulators and FPGA prototypes, respectively, while preserving functional and timing accuracy. We present GVSoC, a highly configurable and timing-accurate event-driven simulator that combines the efficiency of C++ models with the flexibility of Python configuration scripts. GVSoC is fully open-sourced, with the intent to drive future research in the area of highly parallel and heterogeneous RISC-V based IoT processors, leveraging three foundational features: Python-based modular configuration of the hardware description, easy calibration of platform parameters for accurate performance estimation, and high-speed simulation. Experimental results show that GVSoC enables practical functional and performance analysis and design exploration at the full-platform level (processors, memory, peripherals and IOs) with a speed-up of 2500x with respect to cycle-accurate simulation with errors typically below 10% for performance analysis.