Magnetic Nanoelectronics for Brain Inspired Computing (MN BRIC): From Circuit Models to Full System Architecture Simulations
Abstract
This technical report summarizes the R and D efforts for the AFRL project Magnetic Nanoelectronics for Brain-Inspired Computing (MN-BRIC): From Circuit Models to Full System Architecture Simulations. This research project enabled the performance benchmarking of a spintronics hardware platform designed for handling neuromorphic tasks. Spintronics devices that use the spin of electrons as the information state variable have the potential to emulate neuro-synaptic dynamics and can be realized within a compact form-factor, while operating at ultra-low energy-delay point. To explore the benefits of spintronics-based hardware on realistic neuromorphic workloads, we developed a Parallel Discrete-Event Simulation model called Doryta, which is further integrated with a materials-to-systems benchmarking framework. The benchmarking framework allows us to obtain quantitative metrics on the throughput and energy of spintronics-based neuromorphic computing and compare these against standard CMOS-based approaches. Although spintronics hardware offers significant energy and latency advantages, we find that for larger neuromorphic circuits, the performance is limited by the interconnection networks rather than the spintronics-based neurons and synapses. This limitation is overcome by architectural changes to the network.
Document Details
- Document Type
- Technical Report
- Publication Date
- May 19, 2023
- Accession Number
- AD1201507
Entities
People
- Christopher Carothers
Organizations
- Rensselaer Polytechnic Institute