Optimus-Reference-Cited by-同舟云学术

Optimus

Published:2018-04-23 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Thirteenth EuroSys Conference
language:
Short-container-title:

Author:

Peng Yanghua¹,Bao Yixin¹,Chen Yangrui¹,Wu Chuan¹,Guo Chuanxiong²

Affiliation:

1. The University of Hong Kong

2. Bytedance Inc.

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3190508.3190517

Reference72 articles.

1. 2006. Caltech 256 Dataset. http://www.vision.caltech.edu/Image_Datasets/Caltech256/. (2006). 2006. Caltech 256 Dataset. http://www.vision.caltech.edu/Image_Datasets/Caltech256/. (2006).

2. 2009. The CIFAR-10 Dataset. https://www.cs.toronto.edu/~kriz/cifar.html. (2009). 2009. The CIFAR-10 Dataset. https://www.cs.toronto.edu/~kriz/cifar.html. (2009).

3. 2014. HDFS. https://wiki.apache.org/hadoop/HDFS. (2014). 2014. HDFS. https://wiki.apache.org/hadoop/HDFS. (2014).

4. 2014. Kaggle NDSB1 Dataset. https://www.kaggle.com/c/datasciencebowl/data. (2014). 2014. Kaggle NDSB1 Dataset. https://www.kaggle.com/c/datasciencebowl/data. (2014).

5. 2014. Overfitting and Regularization. https://alliance.seas.upenn.edu/~cis520/dynamic/2017/wiki/index.php?n=Lectures.Overfitting. (2014). 2014. Overfitting and Regularization. https://alliance.seas.upenn.edu/~cis520/dynamic/2017/wiki/index.php?n=Lectures.Overfitting. (2014).

Cited by 258 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. Swift: Expedited Failure Recovery for Large-Scale DNN Training;IEEE Transactions on Parallel and Distributed Systems;2024-09

2. Exploring collaborative decision-making: A quasi-experimental study of human and Generative AI interaction;Technology in Society;2024-09

3. A Data-Loader Tunable Knob to Shorten GPU Idleness for Distributed Deep Learning;ACM Transactions on Architecture and Code Optimization;2024-08-22

4. Elevating optical networks: Machine learning approach for optimal resource scheduling and performance boost;International Journal of Communication Systems;2024-08-18

5. Online Scheduling and Pricing for Multi-LoRA Fine-Tuning Tasks;Proceedings of the 53rd International Conference on Parallel Processing;2024-08-12