MOSDA: On-Chip Memory Optimized Sparse Deep Neural Network Accelerator With Efficient Index Matching

MOSDA: On-Chip Memory Optimized Sparse Deep Neural Network Accelerator With Efficient Index Matching

The irregular data access pattern caused by sparsity brings great challenges to efficient processing accelerators. Focusing on the index-matching property in DNN, this article aims to decompose sparse DNN processing into easy-to-handle processing tasks to maintain the utilization of processing eleme...

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Bibliographic Details
Main Authors: Hongjie Xu, Jun Shiomi, Hidetoshi Onodera
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Open Journal of Circuits and Systems
Subjects:
Sparsity
DNN
machine learning
hardware accelerator
Online Access:https://ieeexplore.ieee.org/document/9252845/

Internet

https://ieeexplore.ieee.org/document/9252845/

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