Electrical and Information Technology

Faculty of Engineering, LTH

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Brain-inspired Computing using Phase Change Memory Devices


From: 2021-06-10 15:15 to 16:00
Place: Online at the zoom platform
Contact: mattias [dot] borg [at] eit [dot] lth [dot] se
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A part of Nanoscience Colloquia - open advanced talks on nanoscience

When: June 10th 15:15

Where: Online at the zoom platform. Please email for access link

Speaker: Dr. Abu Sebastian, IBM Research, Zurich

Host: Mattias Borg, NanoLund and Dept. ofElectrical and Information Technology, Lund university

Talk abstract

There is a significant need to build efficient non-von Neumann computing systems for highly data-centric artificial intelligence related applications. Brain-inspired computing is one such approach that shows significant promise. Memory is expected to play a key role in this form of computing and in particular, phase-change memory (PCM), arguably the most advanced emerging non-volatile memory technology. Brain-inspired computing is likely to be realized in multiple levels of inspiration given a lack of comprehensive understanding of the working principles of the brain. As the first level of inspiration, one could build computing units where memory and processing co-exist in some form. Computational memory is an example where the physical attributes and state dynamics of memory devices are exploited to perform certain computational tasks in place with very high areal and energy efficiency. In a second level of brain-inspired computing using PCM devices, one could design a co-processor comprising multiple cross-bar arrays of PCM devices to accelerate inference and training of deep neural networks. PCM technology could also play a key role in the space of specialized computing substrates for spiking neural networks and this can be viewed as the third level of brain-inspired computing using these devices.