9 citations · 19 across the 15 of their papers we have counts for
4 papers · 1 filter
Lonic: Algorithm-Hardware Co-Design for Energy-Efficient Fully Local Online SNN Training with INT4 Precision
Peilin Chen, Xiaoxuan Yang
Spiking neural networks (SNNs) have recently attracted increasing attention as an energy-efficient learning paradigm. Existing works also propose temporally and fully local online…
SpikON: A Dual-Parallel and Efficient Accelerator for Online Spiking Neural Networks Learning
Peilin Chen, Xiaoxuan Yang
Spiking neural networks (SNNs) have emerged as a promising paradigm for energy-efficient brain-inspired computing. However, existing online unsupervised SNN learning suffers from l…
Area-Efficient In-Memory Computing for Mixture-of-Experts via Multiplexing and Caching
Hanyuan Gao, Xiaoxuan Yang
Mixture-of-Experts (MoE) layers activate a subset of model weights, dubbed experts, to improve model performance. MoE is particularly promising for deployment on process-in-memory…
End-to-End Transformer Acceleration Through Processing-in-Memory Architectures
Xiaoxuan Yang, Peilin Chen, Tergel Molom-Ochir +1
Transformers have become central to natural language processing and large language models, but their deployment at scale faces three major challenges. First, the attention mechanis…