I/O Characterization and Performance Evaluation of BeeGFS for Deep Learning-Reference-Cited by-同舟云学术

I/O Characterization and Performance Evaluation of BeeGFS for Deep Learning

Published:2019-08-05 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 48th International Conference on Parallel Processing
language:
Short-container-title:

Author:

Chowdhury Fahim¹,Zhu Yue¹,Heer Todd²,Paredes Saul¹,Moody Adam²,Goldstone Robin²,Mohror Kathryn²,Yu Weikuan¹

Affiliation:

1. Florida State University

2. Lawrence Livermore Nat'l Lab

Funder

National Science Foundation

Lawrence Livermore National Laboratory

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3337821.3337902

Reference54 articles.

1. Advanced HPC announces its exclusive platinum partnership with BeeGFS. https://www.hpcwire.com/off-the-wire/advanced-hpc-announces-its-exclusive-platinum-partnership-with-beegfs. Advanced HPC announces its exclusive platinum partnership with BeeGFS. https://www.hpcwire.com/off-the-wire/advanced-hpc-announces-its-exclusive-platinum-partnership-with-beegfs.

2. An Overview of Gradient Descent Optimization Algorithms. http://ruder.io/optimizing-gradient-descent/index.html#minibatchgradientdescent. An Overview of Gradient Descent Optimization Algorithms. http://ruder.io/optimizing-gradient-descent/index.html#minibatchgradientdescent.

3. AWI uses BeeGFS. https://www.hpcwire.com/2016/12/22/awi-uses-new-cray-cluster-earth-sciences-bioinformatics. AWI uses BeeGFS. https://www.hpcwire.com/2016/12/22/awi-uses-new-cray-cluster-earth-sciences-bioinformatics.

4. BeeGFS. https://www.beegfs.io/content. BeeGFS. https://www.beegfs.io/content.

5. BeeGFS as Burst Buffer. https://www.hpcwire.com/off-the-wire/beegfs-based-burst-buffer-enables-world-record-hyperscale-data-distribution. BeeGFS as Burst Buffer. https://www.hpcwire.com/off-the-wire/beegfs-based-burst-buffer-enables-world-record-hyperscale-data-distribution.

Cited by 47 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. An Evaluation of DAOS for Simulation and Deep Learning HPCWorkloads;ACM SIGOPS Operating Systems Review;2024-08-14

2. Viper: A High-Performance I/O Framework for Transparently Updating, Storing, and Transferring Deep Neural Network Models;Proceedings of the 53rd International Conference on Parallel Processing;2024-08-12

3. Capturing Periodic I/O Using Frequency Techniques;2024 IEEE International Parallel and Distributed Processing Symposium (IPDPS);2024-05-27

4. Tarazu: An Adaptive End-to-end I/O Load-balancing Framework for Large-scale Parallel File Systems;ACM Transactions on Storage;2024-04-04

5. Scheduling Distributed I/O Resources in HPC Systems;Lecture Notes in Computer Science;2024