Publications

T. M. A. Do, L. Pottier, R. Ferreira da Silva, S. Caíno-Lores, M. Taufer, and E. Deelman. Performance assessment of ensembles of in situ workflows under resource constraints. In: Concurrency and Computation Practice and Experience (CCPE), 2022. Funding Acknowledgments: NSF 1741040, NSF 1741057, NSF 1841758, DE-AC02-05CH11231, DE-AC05-00OR22725, DE-SC0012636.

T. M. A. Do, L. Pottier, O. Yildiz, K. Vahi, P. Krawczuk, T. Peterka, and E. Deelman. Accelerating Scientific Workflows on HPC Platforms with In Situ Processing. In: IEEE/ACM 22nd International Symposium on Cluster, Cloud and Internet Computing (CCGrid), 2022. Funding Acknowledgments: NSF 1664162, DOE DE-AC02-06CH11357, DE-AC02-05CH11231, DE-SC0012636 and DE-SC0022328.

P. Krawczuk, G. Papadimitriou, R. Tanaka, T. M. A Do, S. Subramany, S. Nagarkar, A. Jain, K. Lam, A. Mandal, L. Pottier, and E. Deelman. Performance Characterization of Scientific Machine Learning Workflows. In: IEEE/ACM Workflows in Support of Large-Scale Science (WORKS), 2021. Funding Acknowledgments: DOE DE-SC0012636, NSF 1664162.

T. M. A. Do, L. Pottier, R. Ferreira da Silva, S. Caíno-Lores, M. Taufer, and E. Deelman. Assessing Resource Provisioning and Allocation of Ensembles of In Situ Workflows. In: International Workshop on Parallel Programming Models and Systems Software for High-End Computing (P2S2), 2021. Funding Acknowledgments: NSF 1741040, NSF 1741057, DOE DE-SC0012636.

T. M. A. Do, L. Pottier, S. Caíno-Lores, R. Ferreira da Silva, M. A. Cuendet, H. Weinstein, T. Estrada, M. Taufer, and E. Deelman. A Lightweight Method for Evaluating In Situ Workflow Efficiency. In: Journal of Computational Science, 48, 101259, 2020. Funding Acknowledgments: NSF 1741040, DOE DE-SC0012636.

T. M. A. Do, L. Pottier, S. Thomas, R. Ferreira da Silva, M. A. Cuendet, H. Weinstein, T. Estrada, M. Taufer, and E. Deelman. A Novel Metric to Evaluate In Situ Workflows. In: International Conference on Computational Science (ICCS), 2020. Funding Acknowledgments: NSF 1741040.

S. Thomas, M. Wyatt, T. M. A. Do, L. Pottier, R. Ferreira da Silva, H. Weinstein, M. A. Cuendet, T. Estrada, E. Deelman, and M. Taufer. Characterization of In Situ and In Transit Analytics of Molecular Dynamics Simulations for Next-generation Supercomputers. In: 15th eScience Conference, 2019. Funding Acknowledgments: NSF 1741040.

R. Ferreira da Silva, S. Callaghan, T. M. A. Do, G. Papadimitriou, and E. Deelman. Measuring the Impact of Burst Buffers on Data-Intensive Scientific Workflows. In: Future Generation Computer Systems, vol. 101, p. 208–220, 2019. Funding Acknowledgments: DOE DE-SC0012636, NSF 1664162, NSF 1741040.

T. M. A. Do, M. Jiang, B. Gallagher, A. Chu, C. Harrison, K. Vahi, and E. Deelman. Enabling Data Analytics Workflows using Node-Local Storage. In: The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC18), 2018. Funding Acknowledgments: LDRD 16-ERD-03, NSF 1741040.

T. M. A. Do, D. Diep, and N. Thoai. Race Condition and Deadlock Detection for Large-Scale Applications. In: 15th International Symposium on Parallel and Distributed Computing (ISPDC), 2016.

T. M. A. Do, D. Diep, and N. Thoai. Message Leak Detection in Debugging Large-Scale Parallel Applications. In: International Conference on Advanced Computing and Applications (ACOMP), 2015.