29.3 An 8.09TOPS/W Neural Engine Leveraging Bit-Sparsified Sign-Magnitude Multiplications and Dual Adder Trees-Reference-Cited by-同舟云学术

29.3 An 8.09TOPS/W Neural Engine Leveraging Bit-Sparsified Sign-Magnitude Multiplications and Dual Adder Trees

Published:2023-02-19 Issue: Volume: Page:
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Container-title:2023 IEEE International Solid- State Circuits Conference (ISSCC)
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Author:

An Hyochan¹,Chen Yu¹,Fan Zichen¹,Zhang Qirui¹,Abillama Pierre¹,Kim Hun-Seok¹,Blaauw David¹,Sylvester Dennis¹

Affiliation:

1. University of Michigan,Ann Arbor,MI,United States

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10067248/10067251/10067269.pdf?arnumber=10067269

Reference5 articles.

1. BitBlade: Energy-Efficient Variable Bit-Precision Hardware Accelerator for Quantized Neural Networks

2. 7.1 A 3.4-to-13.3TOPS/W 3.6TOPS Dual-Core Deep-Learning Accelerator for Versatile AI Applications in 7nm 5G Smartphone SoC

3. Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding;han;ArXiv Preprint,2015

4. A 28nm SoC with a 1.2GHz 568nJ/Prediction Sparse Deep-Neural-Network Engine with >0.1 Timing Error Rate Tolerance for loT Applications;whatmough;ISSCC,2017

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