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A Threshold Logic Gate (TLG) performs weighted summation of multiple binary inputs and compares the summation with a threshold. Different logic functions can be implemented by reconfiguring the weights and threshold of the same TLG circuit. This paper introduces a novel design of reconfigurable Spintronic Threshold Logic Gate (STLG), which employs(More)
As an intriguing ultra-small particle-like magnetic texture, skyrmion has attracted lots of research interests in next-generation ultra-dense and low power magnetic memory/logic designs. Previous studies have demonstrated a single skyrmion-domain wall pair collision in a specially designed magnetic racetrack junction. In this work, we investigate the(More)
In this paper, we propose an energy efficient in-memory computing platform based on novel 4-terminal spin Hall effect-driven domain wall motion devices that could be employed as both non-volatile memory cell and in-memory logic unit. The proposed designs lead to unity of memory and logic. The device to architecture level simulation results show that, with(More)
This paper presents a new Reconfigurable dualmode In-Memory Processing Architecture based on spin Hall effect-driven domain wall motion device called RIMPA. In this architecture, a portion of spintronic memory array can be reconfigured to either non-volatile memory or in-memory logic. Accordingly, computation can be performed within memory without long(More)
Current-mode Analog-to-Digital Converter (ADC) has drawn many attentions due to its high operating speed, power and ground noise immunity, and etc. However, 2n -- 1 comparators are required in traditional n-bit current-mode ADC design, leading to inevitable high power consumption and large chip area. In this work, we propose a low power and compact current(More)
The logic-in-memory architecture is highly promising for high-throughput data-driven applications. This paper presents a novel dual-mode magnetic crossbar architecture consisting of perpendicularly cross-coupled magnetic racetrack nanowires, which could morph between non-volatile multi-bit racetrack memory mode and in-memory data encryption mode. The(More)
In this work, we have proposed a revolutionary neuromorphic computing methodology to implement All-Skyrmion Spiking Neural Network (AS-SNN). Such proposed methodology is based on our finding that skyrmion is a topological stable spin texture and its spatiotemporal motion along themagnetic nano-track intuitively interprets the pulse signal transmission(More)
In-Memory computing has drawn many attentions as a promising solution to reduce massive power hungry data traffic between computing and memory units, leading to significant improvement of entire system performance and energy efficiency. Emerging spintronic device based non-volatile memory is becoming a next-generation universal memory candidate due to its(More)