Compute-Capable Block RAMs for Efficient Deep Learning Acceleration on FPGAs-Reference-Cited by-同舟云学术

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Compute-Capable Block RAMs for Efficient Deep Learning Acceleration on FPGAs

Published:2021-05 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE 29th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)
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Author:

Wang Xiaowei,Goyal Vidushi,Yu Jiecao,Bertacco Valeria,Boutros Andrew,Nurvitadhi Eriko,Augustine Charles,Iyer Ravi,Das Reetuparna

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9444021/9443653/09444060.pdf?arnumber=9444060

Cited by 15 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. PIMSAB: A P rocessing- I n- M emory System with S patially- A ware Communication and B it-Serial-Aware Computation;ACM Transactions on Architecture and Code Optimization;2024-09-05

2. The BRAM is the Limit: Shattering Myths, Shaping Standards, and Building Scalable PIM Accelerators;2024 IEEE 32nd Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM);2024-05-05

3. Table-Lookup MAC: Scalable Processing of Quantised Neural Networks in FPGA Soft Logic;Proceedings of the 2024 ACM/SIGDA International Symposium on Field Programmable Gate Arrays;2024-04

4. Towards High-Throughput Neural Network Inference with Computational BRAM on Nonvolatile FPGAs;2024 Design, Automation & Test in Europe Conference & Exhibition (DATE);2024-03-25

5. Achieving Green Sustainability in Computing Devices in Machine Learning and Deep Learning Techniques;Advances in Computational Intelligence and Robotics;2024-02-27

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