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Assuring application-level correctness against soft errors

机译:确保应用程序级别正确无误

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Traditionally, research in fault tolerance has required architectural state to be numerically perfect for program execution to be correct. However, in many programs, even if execution is not 100% numerically correct, the program can still appear to execute correctly from the user's perspective. To quantify user satisfaction, application-level fidelity metrics (such as PSNR) can be used. The output for such applications is defined to be correct if the fidelity metrics satisfy a certain threshold. However, such applications still contain instructions whose outputs are critical — i.e. their correctness decides if the overall quality of the program output is acceptable. In this paper, we present an analysis technique for identifying such critical program segments. More importantly, our technique is capable of guaranteeing application-level correctness through a combination of static analysis and runtime monitoring. Our static analysis consists of data flow analysis followed by control flow analysis to find static critical instructions which affect several instructions. Critical instructions are further refined into likely non-critical and likely critical sets in a profiling phase. At runtime, we use a monitoring scheme to monitor likely non-critical instructions and take remedial actions if some likely non-critical instructions become critical. Based on this analysis, we minimize the number of instructions that are duplicated and checked at runtime using a software-based fault detection and recovery technique [20]. Put together, our approach can lead to 22% average energy savings for multimedia applications while guaranteeing application-level correctness, when compared to a recent work [9], which cannot guarantee application-level correctness. Comparing to the approach proposed in [20] which guarantees both application-level and numerical correctness, our method achieves 79% energy reduction.
机译:传统上,对容错性的研究要求体系结构状态在数值上是完美的,以使程序执行正确。但是,在许多程序中,即使执行不是数字上100%正确的,从用户的角度来看,该程序仍然可以正确执行。为了量化用户满意度,可以使用应用程序级别的保真度指标(例如PSNR)。如果保真度指标满足某个阈值,则将此类应用程序的输出定义为正确的。但是,此类应用程序仍然包含其输出至关重要的指令,即它们的正确性决定了程序输出的整体质量是否可以接受。在本文中,我们提出了一种用于识别此类关键程序段的分析技术。更重要的是,我们的技术能够通过静态分析和运行时监视的组合来保证应用程序级别的正确性。我们的静态分析包括数据流分析,然后是控制流分析,以查找会影响多条指令的静态关键指令。关键指令在概要分析阶段进一步细化为可能的非关键和可能的关键集。在运行时,我们使用监视方案来监视可能的非关键指令,并在某些可能的非关键指令变得关键时采取补救措施。基于此分析,我们使用基于软件的故障检测和恢复技术,将运行时重复和检查的指令数量减至最少[20]。综上所述,与最近的工作[9]相比,我们的方法可以确保多媒体应用平均节能22%,同时又可以保证应用级别的正确性,而后者无法保证应用级别的正确性。与[20]中提出的可同时保证应用级和数值正确性的方法相比,我们的方法可实现79%的能耗降低。

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