High-Performance Spintronic Based-Neuromorphic Computing System Enabled by Current Monitoring Peripheral Circuit

Implementation of neuromorphic computing systems (NCSs) using digital and analog circuits occup ies a high chip area and consumes high power. With the advancement of nanotechnology, the hybrid Magnetic tunnel junction/Complementary metal–oxide–semiconductor (MTJ/CMOS) circuits have made it possible to implement NCSs with higher density and lower power consumption. However, still there is a gap between the performance of the human brain and NCSs. To mitigate this gap, it is essential to further decrease the energy consumption and the delay of the NCS. The high energy consumption of the MTJ-based NCS is mostly related to the high current needed to switch the MTJ state. Hence, some previous methods tried to perform real-time tracking of the MTJ state by monitoring its voltage and cutting off its current immediately after switching. However, due to the small voltage changes after switching, these methods suffer from a high-power consumption (they need power-hungry amplifiers). In this paper, a new method based on the tracking of MTJ current (instead of voltage) and terminating the MTJ current after switching is proposed. Due to the large changes in the MTJ current after switching (about 40%), there is no need to use an amplifier in the proposed circuit. Therefore, the conventional voltage-mode sensing circuit is replaced with the proposed circuit, to improve the energy efficiency, speed and delay of the NCS. In all state-of-the-art designs, the voltage changes on nodes across the MTJ (PL, FL or both of them) have been used to detect the MTJ switching. However, the proposed circuit detects the MTJ switching by properly sensing the MTJ current and terminates its current immediately. The simulation results in 65-nm CMOS technology confirm that the proposed technique improves the energy consumption and speed of the NCS by 49% and 2.1X compared with the typical NCS.