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Area-Time Efficient Self-Checking ALU Based on Scalable Error Detection Coding

Authors: Zahid Ali Siddiqui; Park Hui-Jong; Jeong-A Lee;

Area-Time Efficient Self-Checking ALU Based on Scalable Error Detection Coding

Abstract

In this paper, we propose a self-checking ALU based on Scalable Error Detection Coding (SEDC) algorithm which is capable of detecting 100% unidirectional errors. The SEDC encoded ALU is scalable based on the input data length. The area overhead increases only by a small factor with increase in data length while the computational latency remains constant irrespective of the binary data length. We show that the proposed scheme is faster and easily scalable compared with the previous implementations based on Berger and Bose-Lin codes and also more area efficient than Berger Check Prediction based ALU.

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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!
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Average
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