PSB-RNN: A Processing-in-Memory Systolic Array Architecture using Block Circulant Matrices for Recurrent Neural Networks-Reference-Cited by-同舟云学术

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PSB-RNN: A Processing-in-Memory Systolic Array Architecture using Block Circulant Matrices for Recurrent Neural Networks

Published:2020-03 Issue: Volume: Page:
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Container-title:2020 Design, Automation & Test in Europe Conference & Exhibition (DATE)
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Author:

Challapalle Nagadastagiri,Rampalli Sahithi,Chandran Makesh,Kalsi Gurpreet,Subramoney Sreenivas,Sampson John,Narayanan Vijaykrishnan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9112295/9116186/09116469.pdf?arnumber=9116469

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. PyAIM: Pynq-Based Scalable Analog In-Memory Computing Prototyping Platform;2024 IEEE 6th International Conference on AI Circuits and Systems (AICAS);2024-04-22

2. In-depth Survey of Processing-in-memory Architectures for Deep Neural Networks;JOURNAL OF SEMICONDUCTOR TECHNOLOGY AND SCIENCE;2023-10-31

3. Path-Based Processing using In-Memory Systolic Arrays for Accelerating Data-Intensive Applications;2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD);2023-10-28

4. A Survey of Design and Optimization for Systolic Array-based DNN Accelerators;ACM Computing Surveys;2023-08-25

5. Domain-Specific Architectures: Research Problems and Promising Approaches;ACM Transactions on Embedded Computing Systems;2023-01-24

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