Architecture-Level Modeling of Photonic Deep Neural Network Accelerators-Reference-Cited by-同舟云学术

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Architecture-Level Modeling of Photonic Deep Neural Network Accelerators

Published:2024-05-05 Issue: Volume:589 Page:307-309
ISSN:
Container-title:2024 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)
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Author:

Andrulis Tanner¹,Chaudhry Gohar Irfan¹,Suriyakumar Vinith M.¹,Emer Joel S.²,Sze Vivienne¹

Affiliation:

1. MIT,Cambridge,USA

2. MIT, Nvidia,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10589923/10590014/10590061.pdf?arnumber=10590061

Reference23 articles.

1. CiMLoop: A Flexible, Accurate, and Fast Compute-In-Memory Modeling Tool

2. Timeloop: A Systematic Approach to DNN Accelerator Evaluation

3. Accelergy: An Architecture-Level Energy Estimation Methodology for Accelerator Designs

4. Ruby: Improving Hardware Efficiency for Tensor Algebra Accelerators Through Imperfect Factorization

5. An Electro-Photonic System for Accelerating Deep Neural Networks

Cited by 1 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. CiMLoop: A Flexible, Accurate, and Fast Compute-In-Memory Modeling Tool;2024 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS);2024-05-05

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