COSAIM: Counter-based Stochastic-behaving Approximate Integer Multiplier for Deep Neural Networks

Author:

Yu Shuyuan,Liu Yibo,Tan Sheldon X.-D.

Publisher

IEEE

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Efficient Approximate Floating-Point Multiplier With Runtime Reconfigurable Frequency and Precision;IEEE Transactions on Circuits and Systems II: Express Briefs;2024-07

2. Multi-ALM: Run-time Multi-Level Reconfigurable Approximate Logarithmic Multiplier;2024 25th International Symposium on Quality Electronic Design (ISQED);2024-04-03

3. Accurate yet Efficient Stochastic Computing Neural Acceleration with High Precision Residual Fusion;2023 Design, Automation & Test in Europe Conference & Exhibition (DATE);2023-04

4. PAALM;Proceedings of the 28th Asia and South Pacific Design Automation Conference;2023-01-16

5. ApproxTorch: An Approximate Multiplier Evaluation Environment for CNNs based on Pytorch;2022 19th International SoC Design Conference (ISOCC);2022-10-19

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