Emerging resistive-crossbar memory (RCM) technology can be promising for computationally-expensive analog pattern-matching tasks. However, the use of CMOS analog-circuits with RCM would result in large power-consumption and poor scalability, thereby eschewing the benefits of RCM-based computation. We propose the use of low-voltage, fast-switching,… (More)
While the promise of spin-torque devices for future on-chip memory is now well recognized, application of spin devices in computational hardware remains an exploratory research-domain. Several 'all-spin' as well as hybrid design-techniques have been explored for computing applications of nano-magnets. A majority of such efforts have been focused on digital… (More)
18] K. Hijikata, et. al. "Study on heat transfer from small heating elements in an integrated circuit chip.
Recent years have witnessed growing interest in the field of brain-inspired computing based on neural-network architectures. In order to translate the related algorithmic models into powerful, yet energy-efficient cognitive-computing hardware, computing-devices beyond CMOS may need to be explored. The suitability of such devices to this field of computing… (More)
In this paper we discuss the potential of emerging spin-torque devices for computing applications. Recent proposals for spin-based computing schemes may be differentiated as 'all-spin' vs. hybrid, programmable vs. fixed, and, Boolean vs. non-Boolean. All-spin logic-styles may offer high area-density due to small form-factor of nano-magnetic devices.… (More)
— A threshold logic gate (TLG) performs weighted sum of multiple inputs and compares the sum with a threshold. We propose Spin-Memeristor Threshold Logic (SMTL) gates, which employ memristive crossbar array (MCA) to perform current-mode summation of binary inputs, whereas, the low-voltage fast-switching spintronic threshold devices (STD) carry out the… (More)
We propose dynamic resistive threshold-logic (DRTL) design based on non-volatile resistive memory. A threshold logic gate (TLG) performs summation of multiple inputs multiplied by a fixed set of weights and compares the sum with a threshold. DRTL employs resistive memory elements to implement the weights and the thresholds, while a compact dynamic CMOS… (More)
CMOS neurons show that STT-SNNs can achieve more than two orders of magnitude lower energy consumption.