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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Veröffentlicht in:	IEEE open journal of circuits and systems 2021, Vol.2, p.144-155
Hauptverfasser:	Xu, Hongjie, Shiomi, Jun, Onodera, Hidetoshi
Format:	Artikel
Sprache:	eng
Schlagworte:	Accelerators Artificial neural networks Chips (memory devices) Convolution DNN Feature extraction Hardware hardware accelerator Indexes machine learning Matching Parallel processing Sparse matrices Sparsity Task analysis
Online-Zugang:	Volltext
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