Publications
Hongwei Jin, George Papadimitriou, Krishnan Raghavan, Pawel Zuk, Prasanna Balaprakash, Cong Wang, Anirban Mandal, and Ewa Deelman. Large Language Models for Anomaly Detection in Computational Workflows: from Supervised Fine-Tuning to In-Context Learning. SC24: International Conference for High Performance Computing, Networking, Storage and Analysis. IEEE, 2024.
Imtiaz Mahmud, George Papadimitriou, Cong Wang, Mariam Kiran, Anirban Mandal, and Ewa Deelman. Elephants Sharing the Highway – Studying TCP Fairness in Large Transfers Over High Throughput Links. 2023 IEEE/ACM Innovating the Network for Data-Intensive Science (INDIS).
Jin, H., Raghavan, K., Papadimitriou, G., Wang, C., Mandal, A., Kiran, M., Deelman, E., & Balaprakash, P. (2023). Graph neural networks for detecting anomalies in scientific workflows. The International Journal of High Performance Computing Applications. https://doi.org/10.1177/10943420231172140
Hongwei Jin, Krishnan Raghavan, George Papadimitriou, Cong Wang, Anirban Mandal, Patrycja Krawczuk, Loïc Pottier, Mariam Kiran, Ewa Deelman, Prasanna Balaprakash (2022). Workflow Anomaly Detection with Graph Neural Networks. 2022 IEEE/ACM Workshop on Workflows in Support of Large-Scale Science (WORKS).
Do, T. M. A., Pottier, L., Yildiz, O., Vahi, K., Krawczuk, P., Peterka, T., & Deelman, E. (2022). Accelerating Scientific Workflows on HPC Platforms with In Situ Processing. 2022 IEEE/ACM 22nd International Symposium on Cluster, Cloud and Internet Computing (CCGrid), 1–10. https://doi.org/10.1109/CCGrid54584.2022.00009
Krawczuk, P., Papadimitriou, G., Tanaka, R., Do, T. M. A., Subramany, S., Nagarkar, S., Jain, A., Lam, K., Mandal, A., Pottier, L., & Deelman, E. (2021).
A Performance Characterization of Scientific Machine Learning Workflows. 2021 IEEE/ACM Workflows in Support of Large-Scale Science (WORKS).