Energy-Efficient All-Spin BNN Using Voltage-Controlled Spin-Orbit Torque Device for Digit Recognition
In: IEEE Transactions on Electron Devices, Jg. 68 (2021), S. 385-392
Online
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Zugriff:
Artificial intelligence has been demonstrated for numerous applications including image recognition and processing, internet-of-things (IoT), and speech recognition. Recent neural network (NN) architectures escalating to perform these functionalities require deep-learning and deep NN (DNN) implementation. However, the present algorithm and circuit of DNN suffer from area and energy-efficiency. The usage of an energy-efficient and cost-effective binary NN (BNN) can mitigate the performance bottleneck. The basic component of BNN (the XNOR and accumulate module) is capable of replacing the conventional multiply-and-accumulate (MAC) operation. Among various emerging nonvolatile memories (NVMs), spintronics-based devices are attracting attention for the implementation of the aforementioned architectures. Multilevel voltage-controlled spin-orbit torque -based magnetic memory (MV-SOTM) spin device as synapse and voltage-controlled SOTM (V-SOTM) device as spin-neuron are capable of producing an all-spin NN. This article presents advanced XNOR operation using a computing-in-memory (CiM) mechanism wherein both V-SOTM and MV-SOTM (using series and parallel configuration) based synapses are compared. The MV-SOTM design dissipates 35.51% lesser energy as compared to the 1-bit V-SOTM. Further, the 8-bit synaptic crossbar array is implemented using both the devices with two output spin-neurons. These series and parallel MV-SOTM-based synaptic arrays consume 42.22% and 45.12% lesser power, respectively, as compared to 1-bit V-SOTM based synaptic array. Furthermore, the all-spin BNN design demonstrates a handwritten digit recognition application.
Titel: |
Energy-Efficient All-Spin BNN Using Voltage-Controlled Spin-Orbit Torque Device for Digit Recognition
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Autor/in / Beteiligte Person: | Brajesh Kumar Kaushik ; Piramanayagam, S. N. ; Shreya, Sonal ; Verma, Gaurav |
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Zeitschrift: | IEEE Transactions on Electron Devices, Jg. 68 (2021), S. 385-392 |
Veröffentlichung: | Institute of Electrical and Electronics Engineers (IEEE), 2021 |
Medientyp: | unknown |
ISSN: | 1557-9646 (print) ; 0018-9383 (print) |
DOI: | 10.1109/ted.2020.3038140 |
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