DTune: Leveraging reliable code generation for adaptive dependability tuning under process variation and aging-induced effects

Semeen Rehman, Florian Kriebel, Duo Sun, Muhammad Shafique, Jörg Henkel

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Designing dependable on-chip manycore systems is subjected to consideration of multiple reliability threats, i.e. soft errors, aging, process variation, etc. In this paper, we introduce a novel adaptive Dependability Tuning (dTune) scheme for manycore processors. It leverages the knowledge of varying vulnerability and error masking properties of different applications along with multiple compiled versions (each offering distinct reliability and performance properties). Our dTune system dynamically tunes the dependability mode at the hardware level through hybrid Redundant Multithreading tuning and at the software level through selection of reliable code version under given performance constraints. It jointly accounts for soft errors and cores' performance variations due to design-time process variation and/or run-time aging-induced performance degradation. We compare our dTune system with four different state-of-the-art techniques and achieve on average 44% and up to 63% improved task reliability for different chip configurations, different variability maps, and different aging years.

Original languageEnglish (US)
Title of host publicationDAC 2014 - 51st Design Automation Conference, Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781479930173
StatePublished - 2014
Event51st Annual Design Automation Conference, DAC 2014 - San Francisco, CA, United States
Duration: Jun 2 2014Jun 5 2014

Publication series

NameProceedings - Design Automation Conference
ISSN (Print)0738-100X


Other51st Annual Design Automation Conference, DAC 2014
Country/TerritoryUnited States
CitySan Francisco, CA

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Modeling and Simulation


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