In the upcoming internet of things (IoT) era, spin transfer torque magnetic tunnel junction (STT-MTJ) based non-volatile (NV) memory and circuits for IoT nodes and normally-off electronics will need to meet constraints in speed, energy and robustness. This study focuses on NV logic-in-memory (LIM) architecture. Supply voltage (Vdd) scaling in MTJ based NV-LIM is evaluated on FD-SOI 28 nm node. In order to overcome Vddscaling bottleneck, an efficient framework for Vddscaling in NV circuits is proposed with design strategies, e.g., back-bias (BB), poly biasing (PB), and approximate computing. The design vector (Vdd,VBB,PB) generated power-delay curves can provide user-defined LIM circuit aiming for dynamic/leakage power saving, power/speed efficiency and process variation resilient. The design space is explored in near-threshold regime around 0.5 V supply. Simulations of NV-logic, full adder (NV-FA) and flip-flop (NV-FF) are performed, along with insights for circuit design and practical implementation of NV-LIM circuits with FD-SOI technology.
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Cai et al. (2016) studied this question.
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