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AutoSLIDE: Automatic Source-Level Instrumentation and Debugging for HLS

机译:AutoSLIDE:HLS的自动源代码级检测和调试

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Improved quality of results from high level synthesis (HLS) tools have led to their increased adoption in hardware design. However, functional verification of HLS-produced designs remains a major challenge. Once a bug is exposed, designers must backtrace thousands of signals and simulation cycles to determine the underlying cause. The challenge is further exacerbated with HLS-produced non-human-readable RTL. In this paper, we present AutoSLIDE, an automated cross-layer verification framework that instruments critical operations, detects discrepancies between software and hardware execution, and traces the suspect datapath tree to identify bug source for the detected discrepancy. AutoSLIDE also maintains mappings between RTL datapath operations, LLVM-IR operations, and C/C++ source code to precisely pinpoint the root-cause of bugs to the exact line/operation in source code, substantially reducing user effort to localize bugs. We demonstrate the effectiveness by detecting and localizing bugs from former versions of the CHStone benchmark suite. Furthermore, we demonstrate the efficiency of AutoSLIDE, with low overhead in HLS time (27%), software trace gathering (10%), and significantly reduced trace size and simulation time compared to exhaustive instrumentation.
机译:高级综合(HLS)工具提高了结果质量,导致其在硬件设计中的采用率越来越高。但是,对HLS生产的设计进行功能验证仍然是一个主要挑战。一旦发现错误,设计人员必须回溯数千个信号和仿真周期,以确定根本原因。 HLS生产的非人类可读RTL进一步加剧了这一挑战。在本文中,我们介绍了AutoSLIDE,这是一种自动化的跨层验证框架,可检测关键操作,检测软件和硬件执行之间的差异,并跟踪可疑数据路径树以识别所检测到差异的错误源。 AutoSLIDE还维护RTL数据路径操作,LLVM-IR操作和C / C ++源代码之间的映射,以将错误的根本原因精确地定位到源代码中的确切行/操作,从而大大减少了用户定位错误的工作。我们通过检测和本地化CHStone基准测试套件早期版本中的错误来证明其有效性。此外,与穷举仪器相比,我们展示了AutoSLIDE的效率,其HLS时间的开销较低(27%),软件跟踪收集(10%),并且显着减少了跟踪大小和仿真时间。

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