A Fast Algorithm to Simulate Nonlinear Resistive Networks

arXiv:2402.11674v1 Announce Type: cross
Abstract: In the quest for energy-efficient artificial intelligence systems, resistor networks are attracting interest as an alternative to conventional GPU-based neural networks. These networks leverage the physics of electrical circuits for inference and can be optimized with local training techniques such as equilibrium propagation. Despite their potential advantage in terms of power consumption, the challenge of efficiently simulating these resistor networks has been a significant bottleneck to assess their scalability, with current methods either being limited …

abstract algorithm artificial artificial intelligence arxiv cond-mat.dis-nn cs.et cs.lg energy equilibrium gpu inference intelligence networks neural networks physics propagation quest systems training type