3 papers
cs.AR2026
Non-uniform Memory Partitioning For Low-Power Spiking Neural Networks
Simon Richter, Darío Fernández Khatiboun, Maryam Sadeghi +2
Spiking Neural Networks (SNNs) naturally excel in processing temporally rich and sparse data. However, because of their time-stepped processing, memory access, specifically to syna…
cs.NE2026
Event-Driven Language Models with Sparse Neural Activity for Neuromorphic Hardware
Simon Richter, Ruhai Lin, Jason Yik +4
Inference with transformer-based large language models (LLMs) is often limited by the memory-bound KV cache and quadratic attention cost. State-space models (SSMs) mitigate this th…
physics.app-ph2026
Reconfigurable Multistate MRAM Synapses with Vortex STNO based Neurons for Scalable In-Memory Convolutional Neural Networks
Ravish Kumar Raj, Simon N. Richter, Saeed Baghaee Ivriq +9
Magnetic tunnel junction (MTJ)-based magnetic random-access memory (MRAM) is a promising platform for neuromorphic and in-memory computing owing to its non-volatility, high enduran…