Muhammad Kamran Ayub, Osman Hasan, Muhammad Shafique
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.
Instructions to Run Lab View Codes
You need LabVIEW version 2015 or later to view these codes. If you are working on previous LabVIEW version, please write us an email so that we may provide the codes for previous versions. Also, the MATLAB scripts will be uploaded soon.
To Run the LabVIEW Code, please follow below:
- Install LabVIEW 2015 or later
- Open project file with name “LPAA Error Analysis Code for LabVIEW”
- For Statistical Error Analysis, open “LPAA Statistical Error Analysis VI.vi” and follow instructions as on Front Panel
- For Exhaustive Simulation Analysis/Validations, open “LPAA Exhaustive Simulation Based Error Analysis VI.vi” and follow instructions as on Front Panel
Instructions to Run MATLAB
Instructions to run the MATLAB Script will be updated soon.
Muhammad Kamran Ayub is Post Graduate students of Electrical Engineering at NUST School of Electrical Engineering & Computer Science. He is working on this project in the System Analysis & Verification (SAVE) Lab of NUST-SEECS, under the supervision of Dr. Osman Hasan.