3 papers
cs.LG2025
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…
cs.NE2024
Neuromorphic Programming: Emerging Directions for Brain-Inspired Hardware
Steven Abreu, Jens E. Pedersen
The value of brain-inspired neuromorphic computers critically depends on our ability to program them for relevant tasks. Currently, neuromorphic hardware often relies on machine le…
cs.NE2024
Neuromorphic Intermediate Representation: A Unified Instruction Set for Interoperable Brain-Inspired Computing
Jens E. Pedersen, Steven Abreu, Matthias Jobst +12
Spiking neural networks and neuromorphic hardware platforms that simulate neuronal dynamics are getting wide attention and are being applied to many relevant problems using Machine…