Accelerating Real-Time Imaging for Radiotherapy: Leveraging Multi-GPU Training with PyTorch-Reference-Cited by-同舟云学术

Accelerating Real-Time Imaging for Radiotherapy: Leveraging Multi-GPU Training with PyTorch

Published:2023-12-15 Issue: Volume:9 Page:1727-1734
ISSN:
Container-title:2023 International Conference on Machine Learning and Applications (ICMLA)
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Author:

Obe Ruth¹,Kaufmann Brandt²,Baird Kaelen³,Kadel Sam⁴,Soltani Yasmin⁵,Cham Mostafa⁶,Gobbert Matthias K.⁷,Barajas Carlos A.⁷,Jiang Zhuoran⁸,Sharma Vijay R.⁹,Ren Lei¹⁰,Peterson Stephen W.¹¹,PoIf Jerimy C.¹²

Affiliation:

1. U. of Houston-Clear Lake,Dept. of Computer Science and of Software Engineering,USA

2. U. of San Francisco,Dept. of Mathematics and Statistics,USA

3. Skidmore College,Dept. of Computer Science and of Mathematics,USA

4. Mount Holyoke College,Dept. of Computer Science and of Psychology,USA

5. U. of Houston,Dept. of Biomedical Engineering,USA

6. U. of Maryland,Dept. of Information Systems,Baltimore County

7. U. of Maryland,Dept. of Mathematics and Statistics,Baltimore County

8. Medical Physics Graduate Program, Duke University,USA

9. U. of Maryland School of Medicine,Dept. of Radiation Oncology,USA

10. U. of Maryland School of Medicine,Department of Radiation Oncology,USA

11. U. of Cape Town,Dept. of Physics,South Africa

12. H3D, Inc.,USA

Funder

NSF

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10459339/10459727/10459864.pdf?arnumber=10459864

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4. ThreadPool and the global interpreter lock (gil);Brownlee,2021

5. Introduction to Machine Learning, Neural Networks, and Deep Learning;Choi;Translational Vision Science & Technology,2020