Scaling Resolution of Gigapixel Whole Slide Images Using Spatial Decomposition on Convolutional Neural Networks-Reference-Cited by-同舟云学术

Scaling Resolution of Gigapixel Whole Slide Images Using Spatial Decomposition on Convolutional Neural Networks

Published:2023-06-26 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Platform for Advanced Scientific Computing Conference
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Author:

Tsaris Aristeidis¹^ORCID,Romero Josh²^ORCID,Kurth Thorsten²^ORCID,Hinkle Jacob¹^ORCID,Yoon Hong-Jun¹^ORCID,Wang Feiyi¹^ORCID,Dash Sajal¹^ORCID,Tourassi Georgia¹^ORCID

Affiliation:

1. Oak Ridge National Laboratory, Oak Ridge, United States of America

2. NVIDIA Inc., Santa Clara, United States of America

Funder

U.S. Department of Energy

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3592979.3593401

Reference24 articles.

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3. Peter Jin , Boris Ginsburg , and Kurt Keutzer . Spatially parallel convolutions , 2018 . Peter Jin, Boris Ginsburg, and Kurt Keutzer. Spatially parallel convolutions, 2018.

4. Amir Gholami , Ariful Azad , Peter Jin , Kurt Keutzer , and Aydin Buluc . Integrated model, batch and domain parallelism in training neural networks . 2017 . Amir Gholami, Ariful Azad, Peter Jin, Kurt Keutzer, and Aydin Buluc. Integrated model, batch and domain parallelism in training neural networks. 2017.

5. Improving Strong-Scaling of CNN Training by Exploiting Finer-Grained Parallelism

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