SEALPAA
This is the web app or web related tool named SEALPAA whose latest release can be downloaded as StatisticalErrorAnalysisofLowPowerApproximateAdder_DAC17_MATLABCode.zip from this website redcoolmedia.net
SEALPAA
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Low-power approximate adders provide basic building blocks for approximate computing hardware that have shown remarkable energy efficiency for error-resilient applications (like image/video processing, computer vision, etc.), especially for battery-driven portable systems. In this paper, we present a novel scalable, fast yet accurate analytical method to evaluate the output error probability of multi-bit low power adders for a predetermined probability of input bits. Our method recursively computes the error probability by considering the accurate cases only, which are considerably smaller than the erroneous ones. Our method can handle the error analysis of a wider-range of adders with negligible computational overhead. To ensure its rapid adoption in industry and academia, we have open-sourced our LabVIEW and MATLAB libraries.Lab Web Page: http://save.seecs.nust.edu.pk/projects/SEALPAA/
Emails: 14mseemayub@seecs.edu.pk, osman.hasan@seecs.edu.pk, muhammad.shafique@tuwien.ac.at
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