Energy-efficient magnetic 5:2 compressors based on SHE-assisted hybrid MTJ/FinFET logic

Abstract

Energy dissipation in integrated circuits has become a matter of grave concern. Various approaches at different levels of abstraction such as logic-in-memory structures based on magnetic tunnel junction (MTJ) devices and approximate computing can be employed to reduce energy consumption. Efficient hybrid MTJ/FinFET designs for exact and approximate 5:2 compressors are proposed herein. The proposed designs use the spin Hall effect (SHE)-assisted writing method to store data in MTJs, which significantly improves the energy efficiency of the MTJ switching as compared with the conventional spin transfer torque (STT) method. The circuits are simulated in HSPICE using 7-nm FinFET and SHE perpendicular MTJ models. The results indicate that the proposed approximate designs provide significant improvements in terms of energy consumption and device count compared with their exact counterpart. The first and second proposed approximate designs improve the power consumption by 51%, read delay by 16% and 26%, and transistor count by 63% and 70%, respectively, as compared with the exact design. The second approximate compressor offers a significantly lower error rate (27% versus 48%) in comparison with the first approximate design, as well as better performance parameters. The imprecise 5:2 compressors are used in image processing applications to assess their accuracy metrics. Comprehensive MATLAB simulations indicate that the proposed approach provides great capabilities for image processing applications considering various accuracy and quality metrics.