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Error correction for approximate computing

Authors: Hang Zhang 0013; Afshin Abdi; Faramarz Fekri; Hadi Esmaeilzadeh;

Error correction for approximate computing

Abstract

Approximate computing, which sacrifices the accuracy during computation, is a promising technology to save energy. However, large number of computation errors may violate the accuracy requirement of certain applications and should be corrected. Consider a Graphical Processing Unit (GPU) with multiple Streaming Multiprocessors (SMs), where some of these SMs perform accurate computation while the others perform approximate computation. Provided the approximate outputs are correlated with other accurate outputs, we exploit this relation and model the approximate computation process as a communication process. Then the problem of error correction transforms to a problem of decoding and we want to solve it with certain error correction code. Different from the classical communications process, approximate computing raises additional constraints on the code design. In this paper, we propose a semi-regular LDPC code satisfying these constraints and prove this code can be perfectly decoded. Certain properties of the code are analyzed and simulations are provided to verify the statement.

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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!
1
Average
Average
Average
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