Integrating Deep Learning in Domain Sciences at Exascale-Reference-Cited by-同舟云学术

Integrating Deep Learning in Domain Sciences at Exascale

Published:2020 Issue: Volume: Page:35-50
ISSN:1865-0929
Container-title:Communications in Computer and Information Science
language:
Short-container-title:

Author:

Archibald Rick,Chow Edmond,D’Azevedo Eduardo,Dongarra Jack,Eisenbach Markus,Febbo Rocco,Lopez Florent,Nichols Daniel,Tomov Stanimire,Wong Kwai,Yin Junqi

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-63393-6_3

Reference67 articles.

1. Ise, T., Oba, Y.: Forecasting climatic trends using neural networks: an experimental study using global historical data. Front. Robot. AI 6, 32 (2019)

2. Wang, J., Balaprakash, P., Kotamarthi, R.: Fast domain-aware neural network emulation of a planetary boundary layer parameterization in a numerical weather forecast model. Geosci. Model Dev. 12(10), 4261–4274 (2019)

3. Agrawal, A., Choudhary, A.: Deep materials informatics: applications of deep learning in materials science. MRS Commun. 9(3), 779–792 (2019)

4. Feng, S., Zhou, H., Dong, H.: Using deep neural network with small dataset to predict material defects. Mater. Des. 162, 300–310 (2019). Citation Key: FENG2019300

5. Ye, W., Chen, C., Wang, Z., Chu, I.-H., Ong, S.P.: Deep neural networks for accurate predictions of crystal stability. Nat. Commun. 9, 3800 (2018)

Cited by 3 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. A study on the performance of distributed training of data-driven CFD simulations;The International Journal of High Performance Computing Applications;2023-05-04

2. Towards Seamless Execution of Deep Learning Application on Heterogeneous HPC Systems;Studies in Computational Intelligence;2023

3. An AI-Accelerated CFD Application on a Benchmark Device: FDA Nozzle;2022 Medical Technologies Congress (TIPTEKNO);2022-10-31