系统级设计中的周期计数精确内存建模

Y. Lo, Mao Lin Li, R. Tsay
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引用次数: 8

摘要

本文提出了一种从周期精确记忆模型(CAMM)的时钟有限状态机(CFSM)自动生成周期计数精确记忆模型(CCAMM)的有效方法。由于内存访问逐渐主导了系统活动,因此正确有效的内存时序模型对于系统级仿真至关重要。一般来说,CCAMM提供了足够的定时精度和低仿真开销,因此优于具有低精度的简单固定延迟模型(SFDM)或具有低性能的CAMM。该方法可以系统地生成CCAMM并保证其正确性。实验结果表明,该模型的精度与RTL模型相当,运行速度提高了100倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cycle count accurate memory modeling in system level design
In this paper, we propose an effective automatic generation approach for a Cycle-Count Accurate Memory Model (CCAMM) from the Clocked Finite State Machine (CFSM) of the Cycle Accurate Memory Model (CAMM). Since memory accesses are gradually dominating system activities, a correct and efficient memory timing model is essential to system-level simulation. In general, a CCAMM provides sufficient timing accuracy with low simulation overhead, and hence is preferred over the Simple Fixed Delay Model (SFDM), which has low accuracy, or the CAMM, which has low performance. Our proposed approach can systematically generate the CCAMM and guarantee correctness. The experimental results show that the generated model is as accurate as the Register Transfer Level (RTL) model while running 100X faster.
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