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COLOQUIO DEL 17/05: "Brain-Inspired Computing Using Magnetic Domain Wall Devices"

Brain-Inspired Computing Using Magnetic Domain Wall Devices

Professor S. N. PiramanayagamProfessor S. N. PiramanayagamSchool of Physical and Mathematical Sciences, Nanyang Technological University, Singaporea.


Neuromorphic computing or brain-inspired computing is considered as a potential solution to overcome the
energy inefficiency of the von Neumann architecture for artificial intelligence applications [1-4]. To realize
spin-based neuromorphic computing practically, it is essential to design and fabricate electronic analogues
of neurons and synapses. An electronic analogue of a synaptic device should provide multiple resistance
states. A neuron device should receive multiple inputs and should provide a pulse output when the
summation of the multiple inputs exceeds a threshold.

Our group has been carrying out investigations on the design and development of various synaptic and
neuron devices in our laboratory. Domain wall (DW) devices based on magnetic tunnel junctions (MTJs),
where the DW can be moved by spin-orbit torque, are suitable candidates for the fabrication of synaptic
and neuron devices [2]. Spin-orbit torque helps in achieving DW motion at low energies whereas the use of
MTJs helps in translating DW position information into resistance levels (or voltage pulses) [3]. This talk will
summarize various designs of synthetic neurons synaptic elements and materials [4]. The first half of the
talk will be at an introductory level, aimed at first-year graduate students. The second half will provide
details of the latest research.

[1] K Roy, A Jaiswal and P Panda, Naure 575 607-617 (2019)
[2] WLW Mah, JP Chan, KR Ganesh, VB Naik, SN Piramanayagam, Leakage function in magnetic domain wall
based artificial neuron using stray field, Appl. Phys. Lett., 123 (9) 092401 (2023).
[3] D Kumar, HJ Chung, JP Chan, TL Jin, ST Lim, SSP Parkin, R Sbiaa and SN Piramanayagam, Ultralow Energy
Domain Wall Device for Spin-Based Neuromorphic Computing ACS Nano 17(7) 6261-6274 (2023)
[4] R Maddu, D Kumar, S Bhatti and S.N. Piramanayagam, Spintronic Heterostructures for Artificial Intelligence: A
Materials Perspective, Phys. Stat. Sol. RRL 17(6) 2200493 (2023).

S. N. (Prem) Piramanayagam got the Ph.D. from the Indian Institute of Technology, Bombay, India, in 1994. HeS. N. (Prem) Piramanayagam got the Ph.D. from the Indian Institute of Technology, Bombay, India, in 1994. Hecarried out further research at Shinshu University, Japan (19951999) and worked at the Data Storage Institute(DSI), Singapore (A*STAR). He is currently an Associate Professor at Nanyang Technological University (NTU),Singapore. He has 30 years of experience in magnetism, with research topics including amorphous magneticalloys, permanent magnetic materials, and thin films and nanostructures for recording and spintronicsapplications. His current interest lies in the interdisciplinary areas of magnetism, electronics, and nanotechnology.
Prem has received an award for teaching excellence from NTU Singapore and several awards for outstandingresearch from DSI Singapore. He is a Senior Member of IEEE and has been an active volunteer in the IEEEMagnetics Society, including chair of the Technical Committee, elected member of the Administrative Committee,chair of the Singapore Chapter, and co-chair of the 2018 Intermag Conference in Singapore. He has publishedover 200 journal articles and has filed several patent applications. He serves as an editor of IEEE Transactions onMagnetics and as editor-in-chief of Nano (World Scientific). He co-edited the book, Developments in DataStorage: Materials Perspective (Wiley-IEEE Press, 2011).

Viernes 17/5, 14.30hs.Viernes 17/5, 14.30hs.

Duración aproximada: 45 min de exposición y luego se habilita un tiempo para preguntas.

Salón de Actos del Instituto Balseiro. Av. Bustillo km 9,5, San Carlos de Bariloche.
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