I am a first-year Ph.D. student in Computer Science at the University of Chicago.
I work with Dr. Ian Foster and Dr. Kyle Chard as a part of Globus Labs.
I recently completed my Bachelors in Computer Science at the University of Texas at Austin where I worked at the Texas Advanced Computing Center.
Check out my recent projects on GitHub.
You can contact me at jgpauloski (at) uchicago (dot) edu.
My interest lie at the intersection of high-performance computing and machine learning.
In particular, my research is focused on systems for enabling efficient and scalable machine learning training in large, distributed environments.
I am also interested in various optimization methods that can enable large-batch training.
Distributed K-FAC Preconditioner [Paper] [Code]
Distributed Deep Learning for Image Segmentation [Poster]
See more of my latest projects on my GitHub.
- J. Gregory Pauloski, Zhao Zhang, Lei Huang, Weijia Xu, and Ian T. Foster. 2020. Convolutional neural network training with distributed K-FAC. In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC ‘20). IEEE Press, Article 94, 1–14. [Code]
- Z. Zhang, L. Huang, J. G. Pauloski and I. T. Foster, “Efficient I/O for Neural Network Training with Compressed Data,” 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS), New Orleans, LA, USA, 2020, pp. 409-418, doi: 10.1109/IPDPS47924.2020.00050.
- Z. Zhang, L. Huang, J. G. Pauloski and I. Foster, “Aggregating Local Storage for Scalable Deep Learning I/O,” 2019 IEEE/ACM Third Workshop on Deep Learning on Supercomputers (DLS), Denver, CO, USA, 2019, pp. 69-75, doi: 10.1109/DLS49591.2019.00014.
- Gates E., Pauloski J. G., Schellingerhout D., Fuentes D. (2019) Glioma Segmentation and a Simple Accurate Model for Overall Survival Prediction. In: Crimi A., Bakas S., Kuijf H., Keyvan F., Reyes M., van Walsum T. (eds) Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. BrainLes 2018. Lecture Notes in Computer Science, vol 11384. Springer, Cham.
- Pauloski, J. G. (2020, November). Convolutional Neural Network Training with Distributed K-FAC. International Conference for High Performance Computing, Networking, Storage and Analysis (SC20), Atlanta, Georgia.
- Pauloski, J. G. (2018, September). Optimizing Deep Learning Methods for Image Segmentation with Distributed Training. Poster presented at the TACC Symposium for Texas Researchers, Austin, TX.
Page design by Ankit Sultana