467 citations · 474 across the 12 of their papers we have counts for
4 papers · 1 filter
Autonomous Reinforcement Learning Robot Control with Intel's Loihi 2 Neuromorphic Hardware
Kenneth Stewart, Roxana Leontie, Samantha Chapin +3
We present an end-to-end pipeline for deploying reinforcement learning (RL) trained Artificial Neural Networks (ANNs) on neuromorphic hardware by converting them into spiking Sigma…
Neuromorphic Principles for Efficient Large Language Models on Intel Loihi 2
Steven Abreu, Sumit Bam Shrestha, Rui-Jie Zhu +1
Large language models (LLMs) deliver impressive performance but require large amounts of energy. In this work, we present a MatMul-free LLM architecture adapted for Intel's neuromo…
Region Masking to Accelerate Video Processing on Neuromorphic Hardware
Sreetama Sarkar, Sumit Bam Shrestha, Yue Che +3
The rapidly growing demand for on-chip edge intelligence on resource-constrained devices has motivated approaches to reduce energy and latency of deep learning models. Spiking neur…
Accelerating Linear Recurrent Neural Networks for the Edge with Unstructured Sparsity
Alessandro Pierro, Steven Abreu, Jonathan Timcheck +3
Linear recurrent neural networks enable powerful long-range sequence modeling with constant memory usage and time-per-token during inference. These architectures hold promise for s…