Multi-bit Data Flow Error Detection Method Based on SDC Vulnerability Analysis

Abstract

One of the most difficult data flow errors to detect caused by single-event upsets in space radiation is the Silent Data Corruption (SDC). To solve the problem of multi-bit upsets causing program SDC, an instruction multi-bit SDC vulnerability prediction model based on one-class support vector machine classification is built using SDC vulnerability analysis, which has more accurate vulnerability instruction identification capabilities. By hardening the program with selective instruction redundancy, we propose a multi-bit data flow error detection method for detecting SDC error (SDCVA-OCSVM), aiming to protect the data in the memory or register used by the program. We have also verified the effectiveness of the method through comparative experiments. The method has been verified to have a higher error detection rate and lower code size and time overhead.