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Efficient trace data compression using statically selected dictionary

机译:使用静态选择的字典进行有效的跟踪数据压缩

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Post-silicon validation and debug have gained importance in recent years to track down errors that have escaped the pre-silicon phase. Limited observability of internal signals during post-silicon debug necessitates the storage of signal states in real time. Trace buffers are used to store these states. To increase the debug observation window, it is essential to compress these trace signals, so that trace data over larger number of cycles can be stored in the trace buffer while keeping its size constant. In this paper, we propose several dictionary based compression techniques for trace data compression that takes account of the fact that the difference between golden and erroneous trace data is small. Therefore, the static dictionary selected based on golden trace data can provide notably better compression performance than the dynamic dictionaries selected in the current approaches. This will also significantly reduce the hardware overhead by reducing the dictionary size. Our experimental results demonstrate that our approach can provide up to 60% better compression compared to existing approaches, while reducing the architecture overhead by 84%.
机译:近年来,硅后验证和调试对于追踪逃脱硅前阶段的错误已变得越来越重要。硅调试后内部信号的可观察性有限,因此必须实时存储信号状态。跟踪缓冲区用于存储这些状态。为了增加调试观察窗口,必须压缩这些跟踪信号,以便可以将更多周期的跟踪数据存储在跟踪缓冲区中,同时保持其大小不变。在本文中,我们提出了几种基于字典的跟踪数据压缩技术,其中考虑到黄金和错误跟踪数据之间的差异很小。因此,与当前方法中选择的动态字典相比,基于黄金跟踪数据选择的静态字典可以提供明显更好的压缩性能。通过减小字典大小,这也将大大减少硬件开销。我们的实验结果表明,与现有方法相比,我们的方法可提供高达60%的压缩,同时将体系结构开销减少84%。

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