Quentin Anthony

I am a PhD student under Dr. DK Panda’s NOWLAB at The Ohio State University. My research is focused on the intersection of deep learning frameworks and high performance computing. Specifically, my research focuses on resolving distributed deep learning training bottlenecks such as checkpointing, model/optimizer compression, and deep/machine learning framework co-design. I actively contribute to the MVAPICH2 project and its subprojects such as MVAPICH2-GDR (High Performance MPI for GPU clusters), and HiDL (High Performance Deep Learning).

Selected Publications

* denotes equal contribution

MCR-DL: Mix-and-Match Communication Runtime for Deep Learning

Anthony, Q., Awan, A., Rasley, J., He, Y., Shafi, A., Abduljabbar, M., Subramoni, H., and Panda, D.

In 2023 IEEE International Parallel and Distributed Processing Symposium (IPDPS) May 2023
Efficient training of semantic image segmentation on summit using horovod and mvapich2-gdr

Anthony, Quentin, Awan, Ammar Ahmad, Jain, Arpan, Subramoni, Hari, and Panda, Dhabaleswar K DK

In 2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW) May 2020
Accelerating GPU-based Machine Learning in Python using MPI Library: A Case Study with MVAPICH2-GDR

Ghazimirsaeed, S Mahdieh*, Anthony, Quentin*, Shafi, Aamir, Subramoni, Hari, and Panda, Dhabaleswar K DK

In 2020 IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments (MLHPC) and Workshop on Artificial Intelligence and Machine Learning for Scientific Applications (AI4S) May 2020
Scaling Single-Image Super-Resolution Training on Modern HPC Clusters: Early Experiences

Anthony, Quentin, Xu, Lang, Subramoni, Hari, and Panda, Dhabaleswar K DK

In 2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW) May 2021
Evaluating Multi-Level Checkpointing for Distributed Deep Neural Network Training

Anthony, Quentin, and Dai, Donglai

In SC Workshops Supplementary Proceedings (SCWS) May 2021