Affiliation:
1. School of Information Engineering, Chang’an University, Xi’an 710061, China
Abstract
As process technology scales, electronic devices become more susceptible to soft errors. Soft errors can lead to silent data corruptions (SDCs), seriously compromising the reliability of a system. Researchers have explored error resilient encodings, which leverage crash patterns to detect SDCs. Despite its importance, much still remains to be determined regarding how errors propagate to cause SDCs or crashes. Understanding error propagation patterns could lead to more efficient implementation of error detection. An experimental study of program behavior in the presence of faulty instruction encoding under the IA-32 architecture is described in this study. Extensive fault injection experiments including over 70,000 faults were conducted, targeting all fields of instruction encoding. The analysis of the obtained data shows the following: (1) If the alignment of an instruction sequence is not preserved after injection, it causes crashes in a high probability (93.2%). (2) The SDC rate of an alignment-preserved category is close to that of a typical data injection. The SDC-prone fields include the opcode field, reg field, and immediate field. (3) Several crash patterns, such as violation of calling conventions, are revealed to extend the detection methods. These findings help us identify the vulnerable parts of instruction encoding, which need to be protected against soft errors. By applying the implications provided by the findings, we discuss feasible modifications, including swapping reg encodings, to reduce SDC rate, thus increasing the resilience of instruction set to soft errors.
Funder
Natural Science Foundation of China
Subject
Computer Science Applications,Software