GATEST: 使用遗传算法自动生成模拟矢量的验证平台

对硬件设计进行功能验证的一个关键问题是需要大量的模拟矢量来保证验证的充分性。本文针对Verilog语言，采用遗传算法(Genetic Algorithm, GA)作为解决方案，设计了一个使用遗传算法自动生成模拟矢量的验证平台GATEST。该平台的一个特点是，根据指定的关键信号使用数据流分析产生关键路径集合，并采用基于该集合的路径覆盖率作为适应度函数引导模拟矢量的生成。使用该验证平台对北大众志-863系统芯片的功能模块进行实验，并详细分析了不同控制参数配置下的实验结果，说明该平台具有一定的有效性。

GATEST: A Validation Platform of Automatic Simulation Vectors Generation Using Genetic Algorithms

The approaches of simulation-based validation need a large amount of simulation-vectors for verifying the comer cases of VLSI designs. The authors developed a validation platform of automatic simulation vectors generation based on the path coverage metric using genetic algorithm for RT-level designs. Given the critical signals, it used techniques of data flow analysis to acquire the critical path set and choose the critical path coverage to be the fitness function used in the GA. The authors performed experiments on some functional modules of Unity-863 SoC. The relationship between the final results and the control factors were also analyzed in detail. The results show that GATEST is effective and efficient.