BEC: Bit-Level Static Analysis for Reliability against Soft Errors
Soft errors are a type of transient digital signal corruption that occurs in digital hardware components such as the internal flip-flops of CPU pipelines, the register file, memory cells, and even internal communication buses. Soft errors are caused by environmental radioactivity, magnetic interference, lasers, and temperature fluctuations, either unintentionally, or as part of a deliberate attempt to compromise a system and expose confidential data.
We propose a bit-level error coalescing (BEC) static program analysis and its two use cases to understand and improve program reliability against soft errors. The BEC analysis tracks each bit corruption in the register file and classifies the effect of the corruption by its semantics at compile time. The usefulness of the proposed analysis is demonstrated in two scenarios, fault injection campaign pruning, and reliability-aware program transformation. Experimental results show that bit-level analysis pruned up to 30.04 % of exhaustive fault injection campaigns (13.71 % on average), without loss of accuracy. Program vulnerability was reduced by up to 13.11 % (4.94 % on average) through bit-level vulnerability-aware instruction scheduling. The analysis has been implemented within LLVM and evaluated on the RISC-V architecture.
To the best of our knowledge, the proposed BEC analysis is the first bit-level compiler analysis for program reliability against soft errors. The proposed method is generic and not limited to a
specific computer architecture.
Tue 5 MarDisplayed time zone: London change
14:20 - 15:40 | Static/Dynamic AnalysesMain Conference at Tinto Chair(s): Laure Gonnord Univ. Grenoble Alpes, Grenoble INP, LCIS, Valence, France | ||
14:20 20mTalk | BEC: Bit-Level Static Analysis for Reliability against Soft Errors Main Conference Pre-print | ||
14:40 20mTalk | Boosting the Performance of Multi-solver IFDS Algorithms with Flow-Sensitivity Optimizations Main Conference Haofeng Li Institute of Computing Technology at Chinese Academy of Sciences, Jie Lu Institute of Computing Technology at Chinese Academy of Sciences, Haining Meng Institute of Computing Technology at Chinese Academy of Sciences; University of Chinese Academy of Sciences, Liqing Cao Institute of Computing Technology at Chinese Academy of Sciences; University of Chinese Academy of Sciences, Lian Li Institute of Computing Technology at Chinese Academy of Sciences; University of Chinese Academy of Sciences; Zhongguancun Laboratory, Lin Gao TianqiSoft Pre-print | ||
15:00 20mTalk | Representing Data Collections in an SSA Form Main Conference Tommy McMichen Northwestern University, Nathan Greiner Northwestern University, Peter Zhong Northwestern University, Federico Sossai Northwestern University, Atmn Patel Northwestern University, Simone Campanoni Northwestern University Pre-print | ||
15:20 20mTalk | Revamping Sampling-Based PGO with Context-Sensitivity and Pseudo-instrumentation Main Conference |