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LoAS: Fully Temporal-Parallel Dataflow for Dual-Sparse Spiking Neural Networks

Year: 2024

Type: conference-paper

Source: Proceedings of the ... annual International Symposium on Microarchitecture/Proceedings of the annual International Symposium on Microarchitecture

DOI: 10.1109/micro61859.2024.00084

Authors: Ruokai Yin, Youngeun Kim, Di Wu, Priyadarshini Panda

Institutions: Yale University, University of Central Florida

Language: English

Topic: Advanced Memory and Neural Computing

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: closed

Funder: National Science Foundation

Award: Collaborative Research: SHF: Medium: Memory-efficient Algorithm and Hardware Co-Design for Spike-based Edge Computing

OpenAlex ID: W4404954477

FWCI: 15.19

Cites: 58

Cited by: 19

Related to: 10