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Opportunistic Transient-Fault Detection

Authors: Mohamed A. Gomaa; T. N. Vijaykumar;

Opportunistic Transient-Fault Detection

Abstract

CMOS scaling increases susceptibility of microprocessors to transient faults. Most current proposals for transient-fault detection use full redundancy to achieve perfect coverage while incurring significant performance degradation. However, most commodity systems do not need or provide perfect coverage. A recent paper explores this leniency to reduce the soft-error rate of the issue queue during L2 misses while incurring minimal performance degradation. Whereas the previous paper reduces soft-error rate without using any redundancy, we target better coverage while incurring similarly-minimal performance degradation by opportunistically using redundancy. We propose two semi-complementary techniques, called partial explicit redundancy (PER) and implicit redundancy through reuse (IRTR), to explore the trade-off between soft-error rate and performance. PER opportunistically exploits low-ILP phases and L2 misses to introduce explicit redundancy with minimal performance degradation. Because PER covers the entire pipeline and exploits not only L2 misses but all low-ILP phases, PER achieves better coverage than the previous work. To achieve coverage in high-ILP phases as well, we propose implicit redundancy through reuse (IRTR). Previous work exploits the phenomenon of instruction reuse to avoid redundant execution while falling back on redundant execution when there is no reuse. IRTR takes reuse to the extreme of performance-coverage trade-off and completely avoids explicit redundancy by exploiting reuseýs implicit redundancy within the main thread for fault detection with virtually no performance degradation. Using simulations with SPEC2000, we show that PER and IRTR achieve better trade-off between soft-error rate and performance degradation than the previous schemes.

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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    90
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 1%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
90
Top 10%
Top 1%
Top 10%
bronze