Publications

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2019
R. F. da Silva, A. - C. Orgerie, H. Casanova, R. Tanaka, E. Deelman, and F. Suter, "Accurately Simulating Energy Consumption of I/O-intensive Scientific Workflows", Computational Science – ICCS 2019: Springer International Publishing, pp. 138–152, 2019.
E. Deelman, A. Mandal, M. Jiang, and R. Sakellariou, "The role of machine learning in scientific workflows", The International Journal of High Performance Computing Applications, 2019.
2018
T. Estrada, J. Benson, H. Carrillo-Cabada, A. Razavi, M. Cuendet, H. Weinstein, E. Deelman, and M. Taufer, "Graphic Encoding of Macromolecules for Efficient High-Throughput Analysis", 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics, pp. 315-324, 08, 2018.
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", The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC18), Poster, 2018.
E. Deelman, T. Peterka, I. Altintas, C. D. Carothers, K. K. van Dam, K. Moreland, M. Parashar, L. Ramakrishnan, M. Taufer, and J. Vetter, "The future of scientific workflows", The International Journal of High Performance Computing Applications, vol. 32, no. 1, pp. 159–175, 2018.
B. Tovar, R. F. da Silva, G. Juve, E. Deelman, W. Allcock, D. Thain, and M. Livny, "A Job Sizing Strategy for High-Throughput Scientific Workflows", IEEE Transactions on Parallel and Distributed Systems, vol. 29, no. 2, pp. 240–253, 2018.
K. Vahi, M. H. Wang, C. Chang, S. Dodelson, M. Rynge, and E. Deelman, "Workflows using Pegasus: Enabling Dark Energy Survey Pipelines", 28th annual international Astronomical Data Analysis Software & Systems (ADASS), 2018.
2017
E. Deelman, T. Peterka, I. Altintas, C. D. Carothers, K. K. van Dam, K. Moreland, M. Parashar, L. Ramakrishnan, M. Taufer, and J. Vetter, "The future of scientific workflows", The International Journal of High Performance Computing Applications, vol. accepted, 2017.
B. Tovar, R. F. da Silva, G. Juve, E. Deelman, W. Allcock, D. Thain, and M. Livny, "A Job Sizing Strategy for High-Throughput Scientific Workflows", IEEE Transactions on Parallel and Distributed Systems, vol. accepted, 2017.