决策图高级模拟中的回溯和事件驱动技术

R. Ubar, J. Raik, A. Morawiec
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引用次数: 22

摘要

研究了用高层决策图(dd)建模的同步数字系统基于周期的仿真性能问题。介绍了一种新的数据存储表示,称为面向寄存器的数据存储(RODD)。对于高级循环仿真,RODD模型似乎是系统行为的有效和紧凑的表示。为了充分发挥rodd的优势,提出了一种基于周期的前向事件驱动和递归反向跟踪相结合的仿真算法。讨论了用于有效执行DD网络评估的仿真算法的特点。此外,在实际案例中进行的实验结果表明,该方法的仿真性能有所提高,并对四种基于周期的仿真算法进行了比较。此外,还与商业事件驱动和基于周期的HDL仿真工具进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Back-tracing and event-driven techniques in high-level simulation with decision diagrams
The paper addresses the problem of the cycle-based simulation performance of synchronous digital systems modeled by High-Level Decision Diagrams (DDs). A new class of DD representation, called Register-Oriented DDs (RODD) is introduced. The RODD model appears to be an efficient and compact representation of the system behavior for the high-level cycle simulation. In order to fully exploit the advantages of RODDs a new simulation algorithm, which is a combination of cycle-based forward event-driven and recursive back-tracing techniques is proposed. The characteristics of the simulation algorithms used to efficiently execute the evaluation of the DD network are discussed. Further the experimental results carried out on the real case examples demonstrating the gain in simulation performance of the proposed approach and a comparison of four cycle-based simulation algorithms are presented. Additionally, a comparison with the commercial event-driven and cycle-based HDL simulation tools is included.
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