ARXON：一种基于片上光子网络的近似通信框架
ARXON: A Framework for Approximate Communication over Photonic Networks-on-Chip
摘要：
近似计算范式提倡放松应用程序的精度目标，以提高能效和性能。最近，这种范例已经被探索以提高硅光子片上网络（PNoCs）的能量效率。硅光子互连由于产生载波波长的激光源和在不同不确定性下调节光子器件所需的调谐功率而遭受高功率耗散。在本文中，我们提出了一个框架，称为ARXON，以减少这种功耗开销，使智能和积极的近似在PNoCs的硅光子链路通信。我们的框架减少了激光和调谐功率开销，同时智能地近似通信，使应用程序的输出质量不会失真超过可接受的限制。仿真结果表明，我们的框架可以实现高达56.4%的激光器功耗降低和高达23.8%的能源效率比最知名的先前工作与硅光子互连的近似通信和相同的应用输出质量。
英文摘要：
The approximate computing paradigm advocates for relaxing accuracy goals in applications to improve energy-efficiency and performance. Recently, this paradigm has been explored to improve the energy-efficiency of silicon photonic networks-on-chip (PNoCs). Silicon photonic interconnects suffer from high power dissipation because of laser sources, which generate carrier wavelengths, and tuning power required for regulating photonic devices under different uncertainties. In this paper, we propose a framework called ARXON to reduce such power dissipation overhead by enabling intelligent and aggressive approximation during communication over silicon photonic links in PNoCs. Our framework reduces laser and tuning-power overhead while intelligently approximating communication, such that application output quality is not distorted beyond an acceptable limit. Simulation results show that our framework can achieve up to 56.4% lower laser power consumption and up to 23.8% better energy-efficiency than the best-known prior work on approximate communication with silicon photonic interconnects and for the same application output quality.
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