论文标题
FPDetect：使用选择性直接评估的有效推理有关模板程序的有效推理
FPDetect: Efficient Reasoning About Stencil Programs Using Selective Direct Evaluation
论文作者
论文摘要
我们提出了FPDetect，这是一种低间接费用方法，用于检测逻辑错误和无需产生误报而影响模板计算的软误差。我们开发了一个离线分析，该分析严格估计了跨模板应用程序保存的浮点位数量。该估计严格地界定了计算数据空间中预期的值。违反这种约束的行为可以肯定地归因于错误。 FPDetect有助于合成针对用户指定级别的准确性和覆盖层定制的错误检测器。 FPDetect还可以基于在时空和时间上部署这些探测器而实现高架减少技术。实验评估证明了我们方法的实用性。
We present FPDetect, a low overhead approach for detecting logical errors and soft errors affecting stencil computations without generating false positives. We develop an offline analysis that tightly estimates the number of floating-point bits preserved across stencil applications. This estimate rigorously bounds the values expected in the data space of the computation. Violations of this bound can be attributed with certainty to errors. FPDetect helps synthesize error detectors customized for user-specified levels of accuracy and coverage. FPDetect also enables overhead reduction techniques based on deploying these detectors coarsely in space and time. Experimental evaluations demonstrate the practicality of our approach.
