Generating Control Logic for Optimized Soft Error Resilience

Wenchao Li, Susmit Jha, and Sanjit A. Seshia. Generating Control Logic for Optimized Soft Error Resilience. In Proc. 9th Workshop on Silicon Errors in Logic - System Effects (SELSE), March 2013.

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Abstract

Aggressive technology scaling has necessitated the development of techniques to ensure resilience to device faults, including soft errors, circuit wear-out, variability, and environmental effects. All error resilience techniques employ some form of redundancy, resulting in added cost such as area or power overhead. Existing selective hardening techniques have been focused on identifying on the most vulnerable components and then statically harden them. This paper proposes a new technique that can further reduce this overhead for error resilience mechanisms that are controllable. The key idea is to generate control predicates1 that can turn the resilience mechanisms ON and OFF dynamically, at the right time. These predicates are mined using an optimization formulation that leverages fault injection simulation information. Our experimental results demonstrate that our approach significantly outperforms the static hardening approach for optimizing soft error resilience.

BibTeX

@inproceedings{li-selse13,
  author    = {Wenchao Li and Susmit Jha and Sanjit A. Seshia},
  title     = {Generating Control Logic for Optimized Soft Error Resilience},
 booktitle = {Proc. 9th Workshop on Silicon Errors in Logic - System Effects (SELSE)},
 month = "March",
 year = {2013},
 abstract = {Aggressive technology scaling has necessitated the 
development of techniques to ensure resilience to device faults, 
including soft errors, circuit wear-out, variability, and environmental 
effects. All error resilience techniques employ some form 
of redundancy, resulting in added cost such as area or power 
overhead. Existing selective hardening techniques have been 
focused on identifying on the most vulnerable components and 
then statically harden them. This paper proposes a new technique 
that can further reduce this overhead for error resilience mechanisms 
that are controllable. The key idea is to generate control 
predicates1 that can turn the resilience mechanisms ON and 
OFF dynamically, at the right time. These predicates are mined 
using an optimization formulation that leverages fault injection 
simulation information. Our experimental results demonstrate 
that our approach significantly outperforms the static hardening 
approach for optimizing soft error resilience.},
}

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