EmuNoC:基于fpga的快速灵活的片上网络原型混合仿真

Y. Y. Tan, Felix Staudigl, Lukas Jünger, Anna Drewes, R. Leupers, J. Joseph
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引用次数: 0

摘要

从多核cpu到边缘人工智能加速器,芯片网络(noc)最近得到了广泛应用。与缓慢的仿真相比,fpga上的仿真有望加速其RTL建模。然而,现实的测试刺激是具有挑战性的硬件生成不同的应用。换句话说,既需要快速又灵活的设计框架。最有希望的解决方案是混合仿真,其中部分设计在软件中进行仿真,其他部分在硬件中进行仿真。本文提出了一种新的混合仿真框架EmuNoC。我们引入了时钟同步方法和仅软件包生成,在最先进的框架上将仿真速度提高了36.3 ×至79.3 ×,同时保留了纯软件接口的灵活性,用于刺激仿真。我们还提高了区域效率,在单个FPGA上建模高达169个路由器的NoC,而以前的框架只能实现64个路由器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
EmuNoC: Hybrid Emulation for Fast and Flexible Network-on-Chip Prototyping on FPGAs
Networks-on-Chips (NoCs) recently became widely used, from multi-core CPUs to edge-AI accelerators. Emulation on FPGAs promises to accelerate their RTL modeling compared to slow simulations. However, realistic test stimuli are challenging to generate in hardware for diverse applications. In other words, both a fast and flexible design framework is required. The most promising solution is hybrid emulation, in which parts of the design are simulated in software, and the other parts are emulated in hardware. This paper proposes a novel hybrid emulation framework called EmuNoC. We introduce a clock-synchronization method and software-only packet generation that improves the emulation speed by 36.3 × to 79.3 × over state-of-the-art frameworks while retaining the flexibility of a pure-software interface for stimuli simulation. We also increased the area efficiency to model up to an NoC with 169 routers on a single FPGA, while previous frameworks only achieved 64 routers.
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