贝叶斯网络在SoC事务级验证平台中的应用

Application of Bayesian Network in SoC Transaction-level Testbench

在越来越复杂的SoC芯片设计过程中,功能验证已成为芯片设计周期中最主要的瓶颈;采用人工智能算法在功能覆盖率指导下自动生成随机激励的方法已成为该领域的研究热点;针对贝叶斯网络强大的不确定性概率推理和数据分析能力以及事务级验证平台的特点,采用贝叶斯网络来自动分析验证平台中的事务配置参数和功能覆盖率统计数据之间的不确定关系,提出了一种改进的功能覆盖率驱动验证平台;与传统的约束随机验证平台相比,能快速达到覆盖率目标,缩短验证周期。

In the complex SoC chip design process,functional verification is considered to be a major bottleneck in the hardware design cycle.Application of artificial intelligence algorithms in Coverage Directed test Generation is one of the hot topics in this area.Attributed to Bayesian networks which have a strong uncertainty reasoning and data analysis capabilities and transaction-level testbench feature,using BN automatically analyze uncertainty relations between the testbench transaction configuration parameters and coverage report statistical data,propose an improved testbench.Compared to the traditional constrained random testbench,this testbench can quickly achieve the coverage goals,shorten the verification cycle.