In this paper, we study seven well-known trace analysis techniques both from the hardware and software domain and discuss their performance on communication-centric system-on-chip (SoC) traces. SoC traces are usually huge in size and concurrent in nature, therefore mining SoC traces poses additional challenges. We provide a hands-on discussion of the selected tools/algorithms in terms of the input, output, and analysis methods they employ. Hardware traces also varies in nature when observed in different level, this work can help developers/academicians to pick up the right techniques for their work. We take advantage of a synthetic trace generator to find the interestingness of the mined outcomes for each tool as well as we work with a realistic GEM5 set up to find the performance of these tools on more realistic SoC traces. Comprehensive analysis of the tool's performance and a benchmark trace dataset are also presented.

翻译：在本文中,我们研究了硬件和软件领域的七种众所周知的跟踪分析技术,并讨论了这些技术在通信中心系统芯片(SoC)跟踪上的性能。 SoC的痕迹通常体积巨大,性质同时存在,因此采矿 SoC的痕迹带来了更多的挑战。我们从输入、输出和分析方法的角度对选定的工具/数值进行了亲手讨论。硬件的痕迹在性质上也不同,在不同层次上观测时,可以帮助开发者/学者收集正确的工作技术。我们利用合成的跟踪生成器,为每个工具寻找所开采结果的有趣性,我们还利用一个现实的GEM5来寻找这些工具在更现实的 SoC跟踪方面的性能。还介绍了对该工具的性能和基准跟踪数据集的全面分析。