用于自动派生应用程序感知错误检测器的端到端方法

Galen Lyle, Shelley Cheny, K. Pattabiraman, Z. Kalbarczyk, R. Iyer
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引用次数: 34

摘要

基于关键变量重新计算(Critical Variable Recomputation, CVR)的错误检测为应用程序的关键数据提供了高覆盖率,同时减少了与检测良性错误相关的性能开销。然而,当仅在软件中实现时,与基于CVR的检测相关的性能损失是不合适的高。本文通过提供一个混合硬件/软件工具链来解决这一限制,该工具链允许在最小化额外硬件的同时设计有效的错误检测器。在编译过程中自动派生检测机制,并将其映射到硬件上,在运行时与原始任务并行执行。当使用FPGA平台进行测试时,结果表明我们的方法导致53%的区域开销,而平均增加27%的执行时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An end-to-end approach for the automatic derivation of application-aware error detectors
Critical Variable Recomputation (CVR) based error detection provides high coverage for data critical to an application while reducing the performance overhead associated with detecting benign errors. However, when implemented exclusively in software, the performance penalty associated with CVR based detection is unsuitably high. This paper addresses this limitation by providing a hybrid hardware/software tool chain which allows for the design of efficient error detectors while minimizing additional hardware. Detection mechanisms are automatically derived during compilation and mapped onto hardware where they are executed in parallel with the original task at runtime. When tested using an FPGA platform, results show that our approach incurs an area overhead of 53% while increasing execution time by 27% on average.
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