LauWS: Local Adaptive Unstructured Weight Sparsity of Load Balance for DNN in Near-Data Processing-Reference-Cited by-同舟云学术

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LauWS: Local Adaptive Unstructured Weight Sparsity of Load Balance for DNN in Near-Data Processing

Published:2024-05-19 Issue: Volume: Page:1-5
ISSN:
Container-title:2024 IEEE International Symposium on Circuits and Systems (ISCAS)
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Author:

Li Zixu¹,Wang Wang¹,Zhong Xin¹,Li Manni¹,Yang Jiayu¹,Lin Yinyin¹,Kim Guhyun²,Song Yosub²,Wang Chengchen³,Xiong Xiankui³

Affiliation:

1. Fudan University,State Key Laboratory of Integrated Chips and Systems, School of Microelectronics,Shanghai,China,201203

2. SK Hynix Inc.,Solution Development Division,South Korea

3. ZTE Corporation,State Key Laboratory of Mobile Multimedia Technology,Shenzhen,China,518055

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10557746/10557828/10558554.pdf?arnumber=10558554

Reference23 articles.

1. Language models are few-shot learners;Brown

2. Eyeriss: An Energy-Efficient Reconfigurable Accelerator for Deep Convolutional Neural Networks

3. Hardware Architecture and Software Stack for PIM Based on Commercial DRAM Technology : Industrial Product

4. A 1ynm 1.25V 8Gb, 16Gb/s/pin GDDR6-based Accelerator-in-Memory supporting 1TFLOPS MAC Operation and Various Activation Functions for Deep-Learning Applications

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