对速度的需求：硅悬挂键逻辑的高效精确仿真
The Need for Speed: Efficient Exact Simulation of Silicon Dangling Bond Logic
AI总结：
本文针对硅悬挂键逻辑精确物理仿真计算成本高的问题，提出QuickExact算法，通过物理信息搜索空间剪枝、部分解缓存和有效状态枚举三种技术，在随机布局和门库上分别实现超过5000倍和2000倍的运行时间加速。
摘要：
硅悬挂键（SiDB）逻辑平台是一种新兴的超越CMOS纳米技术计算平台，由于其能够实现比当前CMOS制造节点高出数个数量级的集成密度和时钟速度，因而成为一个有前景的竞争者。然而，SiDB布局的精确物理仿真是任何设计验证工作流程中必不可少的组成部分，其计算成本十分高昂。在本文中，我们提出了一种名为QuickExact的新算法，旨在同时实现高效性与精确性。为此，我们引入了三种技术，即1）基于物理信息的搜索空间剪枝，2）部分解缓存，以及3）有效状态枚举。大量实验评估证实，与最先进的算法相比，所得到的方法在随机生成的布局上带来了超过5000倍的显著运行时间优势，在一个既有的门库上带来了超过2000倍的优势。
英文摘要：
The Silicon Dangling Bond (SiDB) logic platform, an emerging computational beyond-CMOS nanotechnology, is a promising competitor due to its ability to achieve integration density and clock speed values that are several orders of magnitude higher compared to current CMOS fabrication nodes. However, the exact physical simulation of SiDB layouts, which is an essential component of any design validation workflow, is computationally expensive. In this paper, we propose a novel algorithm called QuickExact, which aims to be both, efficient and exact. To this end, we are introducing three techniques, namely 1) Physically-informed Search Space Pruning, 2) Partial Solution Caching, and 3) Effective State Enumeration. Extensive experimental evaluations confirm that, compared to the state-of-the-art algorithm, the resulting approach leads to a paramount runtime advantage of more than a factor of 5000 on randomly generated layouts and more than a factor of 2000 on an established gate library.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
