Fahim Chowdhury

According to our database, Fahim Chowdhury authored at least 9 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Auto-WLM: Machine Learning Enhanced Workload Management in Amazon Redshift.

Gaurav Saxena, Mohammad Rahman, Naresh Chainani, Chunbin Lin, George Caragea, Fahim Chowdhury, Ryan Marcus, Tim Kraska, Ippokratis Pandis, Balakrishnan (Murali) Narayanaswamy

Proceedings of the Companion of the 2023 International Conference on Management of Data, 2023

A Comparison of LSTM and GRU for Bengali Speech-to-Text Transformation.

Nusrat Jahan, Zakia Sultana Shahid, Fahim Chowdhury, Sajjad Ahmed, Mohammad Zavid Parvez, Prabal Datta Barua, Subrata Chakraborty

Proceedings of the 2023 International Conference on Advances in Computing Research, 2023

2022

DFMan: A Graph-based Optimization of Dataflow Scheduling on High-Performance Computing Systems.

Fahim Chowdhury, Francesco Di Natale, Adam Moody, Kathryn M. Mohror, Weikuan Yu

Proceedings of the 2022 IEEE International Parallel and Distributed Processing Symposium, 2022

2021

O(1) Communication for Distributed SGD through Two-Level Gradient Averaging.

Subhadeep Bhattacharya, Weikuan Yu, Fahim Tahmid Chowdhury, Kathryn M. Mohror

Proceedings of the IEEE International Conference on Cluster Computing, 2021

2020

O(1) Communication for Distributed SGD through Two-Level Gradient Averaging.

Subhadeep Bhattacharya, Weikuan Yu, Fahim Tahmid Chowdhury

CoRR, 2020

Emulating I/O Behavior in Scientific Workflows on High Performance Computing Systems.

Fahim Chowdhury, Yue Zhu, Francesco Di Natale, Adam Moody, Elsa Gonsiorowski, Kathryn M. Mohror, Weikuan Yu

Proceedings of the Fifth IEEE/ACM International Parallel Data Systems Workshop, 2020

2019

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

Fahim Chowdhury, Yue Zhu, Todd Heer, Saul Paredes, Adam Moody, Robin Goldstone, Kathryn M. Mohror, Weikuan Yu

Proceedings of the 48th International Conference on Parallel Processing, 2019

Efficient User-Level Storage Disaggregation for Deep Learning.

Yue Zhu, Weikuan Yu, Bing Jiao, Kathryn M. Mohror, Adam Moody, Fahim Chowdhury

Proceedings of the 2019 IEEE International Conference on Cluster Computing, 2019

2018

Entropy-Aware I/O Pipelining for Large-Scale Deep Learning on HPC Systems.

Yue Zhu, Fahim Chowdhury, Huansong Fu, Adam Moody, Kathryn M. Mohror, Kento Sato, Weikuan Yu

Proceedings of the 26th IEEE International Symposium on Modeling, 2018