论文标题
采矿SOC消息与注意模型流动
Mining SoC Message Flows with Attention Model
论文作者
论文摘要
高质量的系统级消息流量规格对于全面验证片（SOC）设计是必需的。但是，此类规格的手动开发和维护是艰巨的任务。我们提出了一种破坏性的方法，该方法利用了通过注意机制来推断SOC通信痕迹的准确流动规范。所提出的方法可以克服由现有采矿工具的同时执行SOC痕迹造成的SOC痕迹的固有复杂性，而现有采矿工具通常会发现极具挑战性。我们对五个高度并发痕迹进行实验，发现所提出的方法的表现优于几种现有的最新痕量挖掘工具。
High-quality system-level message flow specifications are necessary for comprehensive validation of system-on-chip (SoC) designs. However, manual development and maintenance of such specifications are daunting tasks. We propose a disruptive method that utilizes deep sequence modeling with the attention mechanism to infer accurate flow specifications from SoC communication traces. The proposed method can overcome the inherent complexity of SoC traces induced by the concurrent executions of SoC designs that existing mining tools often find extremely challenging. We conduct experiments on five highly concurrent traces and find that the proposed approach outperforms several existing state-of-the-art trace mining tools.
