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A TLM-RTL Systemverilog-Based Verification Franework for OCP Design

机译:基于TLM-RTL系统基于Verilog的OCP设计验证框架

摘要

Open Core Protocol (OCP) establishes itself as the only non-proprietary, openly licensed, core-centric protocol that is used to support “plug-and-play” SoC (System-On-Chip) design practices. Designer can reuse OCP-compliance IP cores based on system integration and verification approach in multiple designs without reworking, reducing the development time and cutting down overall design costs.udIn this thesis, we develop a reusable verification framework of OCP. Assertion-based verification was chosen in order to enforce the flow. An OCP SystemVerilog monitor which is developed in house is used to verify the OCP SystemC TL1 (Cycle-accurate Level) design. The monitor can also be reused for OCP designs described at different abstraction level and thus dramatically reduce the time needed for OCP functional verification. To increase the functional coverage of OCP models, Cell-based Genetic Algorithm (CGA) with random number generators based on different probability distribution functions is provided on OCP TL1 models for generating and evolving the OCP transactions. Furthermore, SystemC Verification Library (SCV) is employed as pure random number generator to compare with the proposed CGA. The experiments show that some probability distributions have more effect on the coverage than others. The best population of the CGA can be reused on OCP RTL models to reduce the verification time.
机译:开放核心协议(OCP)将自身确立为唯一的非专有,开放许可,以核心为中心的协议,用于支持“即插即用” SoC(片上系统)设计实践。设计人员可以基于系统集成和验证方法在多个设计中重用符合OCP要求的IP核,而无需重新设计,从而减少了开发时间并降低了总体设计成本。 ud本文中,我们开发了可重用的OCP验证框架。选择基于声明的验证以强制执行流程。内部开发的OCP SystemVerilog监视器用于验证OCP SystemC TL1(精确周期级别)设计。该监视器也可以重新用于以不同抽象级别描述的OCP设计,从而大大减少了OCP功能验证所需的时间。为了增加OCP模型的功能覆盖范围,在OCP TL1模型上提供了具有基于不同概率分布函数的基于随机数生成器的基于细胞的遗传算法(CGA),用于生成和发展OCP事务。此外,SystemC验证库(SCV)被用作纯随机数生成器,以与提出的CGA进行比较。实验表明,某些概率分布对覆盖率的影响大于其他概率分布。可以在OCP RTL模型上重用最佳的CGA,以减少验证时间。

著录项

  • 作者

    Zhang Shihua;

  • 作者单位
  • 年度 2011
  • 总页数
  • 原文格式 PDF
  • 正文语种 en
  • 中图分类
  • 入库时间 2022-08-20 20:21:45

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