Automatic Constraint Generation for guided random simulation

Hu-Hsi Yeh, Chung-Yang Huang
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引用次数: 15

Abstract

In this paper, we proposed an Automatic Target Constraint Generation (ATCG) technique to automatically generate compact and high-quality constraints for the guided random simulation environment. Our objective is to tackle the biggest bottleneck of the entire constrained random simulation process — the time-consuming and error-prone manual testbench composition process. By taking only the design under verification and simulation coverage as our inputs, our automatic constraint generation technique can successfully generate just a few key constraints while achieving very high simulation coverage. Our experimental results show that the proposed approach can outperform both directed and random simulations in both coverage and simulation runtime for a variety of designs
导向随机仿真的自动约束生成
本文提出了一种自动目标约束生成(ATCG)技术,为引导随机仿真环境自动生成紧凑、高质量的约束。我们的目标是解决整个约束随机模拟过程中最大的瓶颈——耗时且容易出错的手动测试台组成过程。通过仅将验证和仿真覆盖下的设计作为输入,我们的自动约束生成技术可以成功地生成几个关键约束,同时获得很高的仿真覆盖率。我们的实验结果表明,该方法在各种设计的覆盖范围和仿真运行时间上都优于定向和随机模拟
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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