BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/New_York BEGIN:DAYLIGHT DTSTART:20250309T030000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:EDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20241103T010000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:EST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20241213T170614Z UID:8AE5D22F-F811-44E9-8ED2-04D250A94DF7 DTSTART;TZID=America/New_York:20241209T100000 DTEND;TZID=America/New_York:20241209T110000 DESCRIPTION:The IEEE Magnetics Toronto Section invites you to a distinguish ed speaker seminar titled "Brain-Inspired Computing Using Magnetic Domain Wall Devices" by Dr. S. N. Piramanayagam.\n\nNeuromorphic computing or bra in-inspired computing is considered as a potential solution to overcome th e energy\ninefficiency of the von Neumann architecture for artificial inte lligence applications [1-4]. To realize spin-based\nneuromorphic computing practically\, it is essential to design and fabricate electronic analogue s of neurons and\nsynapses. An electronic analogue of a synaptic device sh ould provide multiple resistance states. A neuron device\nshould receive m ultiple inputs and should provide a pulse output when the summation of the multiple inputs exceeds\na threshold.\nOur group has been carrying out in vestigations on the design and development of various synaptic and neuron\ ndevices in our laboratory. Domain wall (DW) devices based on magnetic tun nel junctions (MTJs)\, where the DW\ncan be moved by spin-orbit torque\, a re suitable candidates for the fabrication of synaptic and neuron devices [2].\nSpin-orbit torque helps in achieving DW motion at low energies where as the use of MTJs helps in translating DW\nposition information into resi stance levels (or voltage pulses) [3]. This talk will summarize various de signs of\nsynthetic neurons synaptic elements and materials [4]. The first half of the talk will be at an introductory level\,\naimed at first-year graduate students. The second half will provide details of the latest rese arch.\n[1] K Roy\, A Jaiswal and P Panda\, Naure 575 607-617 (2019)\n[2] W LW Mah\, JP Chan\, KR Ganesh\, VB Naik\, SN Piramanayagam\, Leakage functi on in magnetic domain wall\nbased artificial neuron using stray field\, Ap pl. Phys. Lett.\, 123 (9) 092401 (2023).\n[3] D Kumar\, HJ Chung\, JP Chan \, TL Jin\, ST Lim\, SSP Parkin\, R Sbiaa and SN Piramanayagam\, Ultralow Energy\nDomain Wall Device for Spin-Based Neuromorphic Computing ACS Nano 17(7) 6261-6274 (2023)\n[4] R Maddu\, D Kumar\, S Bhatti and S.N. Piramana yagam\, Spintronic Heterostructures for Artificial Intelligence: A\nMateri als Perspective\, Phys. Stat. Sol. RRL 17(6) 2200493 (2023).\n\nSpeaker(s) : Prem Piramanayagam\n\nRoom: ENG101\, Bldg: George Vari Engineering and C omputing Centre (ENG)\, Toronto Metropolitan University\, 350 Victoria Ste et\, Toronto\, Ontario\, Canada\, M5B2K3 LOCATION:Room: ENG101\, Bldg: George Vari Engineering and Computing Centre (ENG)\, Toronto Metropolitan University\, 350 Victoria Steet\, Toronto\, O ntario\, Canada\, M5B2K3 ORGANIZER:ofalou@gmail.com SEQUENCE:34 SUMMARY:Brain-Inspired Computing Using Magnetic Domain Wall Devices URL;VALUE=URI:https://events.vtools.ieee.org/m/451029 X-ALT-DESC:Description: <br /><p>The IEEE Magnetics Toronto Section invites you to a distinguished speaker seminar titled "Brain-Inspired Computing U sing Magnetic Domain Wall Devices" by Dr. S. N. Piramanayagam.</p>\n<p>Neu romorphic computing or brain-inspired computing is considered as a potenti al solution to overcome the energy<br>inefficiency of the von Neumann arch itecture for artificial intelligence applications [1-4]. To realize spin-b ased<br>neuromorphic computing practically\, it is essential to design and fabricate electronic analogues of neurons and<br>synapses. An electronic analogue of a synaptic device should provide multiple resistance states. A neuron device<br>should receive multiple inputs and should provide a puls e output when the summation of the multiple inputs exceeds<br>a threshold. <br>Our group has been carrying out investigations on the design and devel opment of various synaptic and neuron<br>devices in our laboratory. Domain wall (DW) devices based on magnetic tunnel junctions (MTJs)\, where the D W<br>can be moved by spin-orbit torque\, are suitable candidates for the f abrication of synaptic and neuron devices [2].<br>Spin-orbit torque helps in achieving DW motion at low energies whereas the use of MTJs helps in tr anslating DW<br>position information into resistance levels (or voltage pu lses) [3]. This talk will summarize various designs of<br>synthetic neuron s synaptic elements and materials [4]. The first half of the talk will be at an introductory level\,<br>aimed at first-year graduate students. The s econd half will provide details of the latest research.<br>[1] K Roy\, A J aiswal and P Panda\, Naure 575 607-617 (2019)<br>[2] WLW Mah\, JP Chan\, K R Ganesh\, VB Naik\, SN Piramanayagam\, Leakage function in magnetic domai n wall<br>based artificial neuron using stray field\, Appl. Phys. Lett.\, 123 (9) 092401 (2023).<br>[3] D Kumar\, HJ Chung\, JP Chan\, TL Jin\, ST L im\, SSP Parkin\, R Sbiaa and SN Piramanayagam\, Ultralow Energy<br>Domain Wall Device for Spin-Based Neuromorphic Computing ACS Nano 17(7) 6261-627 4 (2023)<br>[4] R Maddu\, D Kumar\, S Bhatti and S.N. Piramanayagam\, Spin tronic Heterostructures for Artificial Intelligence: A<br>Materials Perspe ctive\, Phys. Stat. Sol. RRL 17(6) 2200493 (2023).</p>\n<p>&nbsp\;</p> END:VEVENT END:VCALENDAR