Workflows Community Summit: Advancing the State-of-the-art of Scientific Workflows Management Systems Research and Development

Authors: da Silva, Rafael Ferreira, Casanova, Henri, Chard, Kyle, Coleman, Tainã, Laney, Dan, Ahn, Dong, Jha, Shantenu, Howell, Dorran, Soiland-Reys, Stian, Altintas, Ilkay, Thain, Douglas, Filgueira, Rosa, Babuji, Yadu, Badia, Rosa M., Balis, Bartosz, Caino-Lores, Silvina, Callaghan, Scott, Coppens, Frederik, Crusoe, Michael R., De, Kaushik, Di Natale, Frank, Do, Tu M. A., Enders, Bjoern, Fahringer, Thomas, Fouilloux, Anne, Fursin, Grigori, Gaignard, Alban, Ganose, Alex, Garijo, Daniel, Gesing, Sandra, Goble, Carole, Hasan, Adil, Huber, Sebastiaan, Katz, Daniel S., Leser, Ulf, Lowe, Douglas, Ludaescher, Bertram, Maheshwari, Ketan, Malawski, Maciej, Mayani, Rajiv, Mehta, Kshitij, Merzky, Andre, Munson, Todd, Ozik, Jonathan, Pottier, Loïc, Ristov, Sashko, Roozmeh, Mehdi, Souza, Renan, Suter, Frédéric, Tovar, Benjamin, Turilli, Matteo, Vahi, Karan, Vidal-Torreira, Alvaro, Whitcup, Wendy, Wilde, Michael, Williams, Alan, Wolf, Matthew, Wozniak, Justin

Subject Terms: Computer Science - Distributed, Parallel, and Cluster Computing

Access URL: http://arxiv.org/abs/2106.05177

Application of an automated machine learning-genetic algorithm (AutoML-GA) coupled with computational fluid dynamics simulations for rapid engine design optimization.

Authors: Owoyele, Opeoluwa, Pal, Pinaki, Vidal Torreira, Alvaro, Probst, Daniel, Shaxted, Matthew, Wilde, Michael, Senecal, Peter Kelly

Source: International Journal of Engine Research (Sage Publications, Ltd.); Sep2022, Vol. 23 Issue 9, p1586-1601, 16p