By Ulrich Rüde, Karen Willcox, Lois Curfman McInnes, and Hans De Sterck
While CSE is rooted in the mathematical and statistical sciences, computer science, the physical sciences, and engineering, today it increasingly pursues its own unique research agenda. The field is now widely recognized as an essential cornerstone that drives scientific and technological progress in conjunction with theory and experiment. Scientific experimentation and theory, the classical paradigms of the scientific method, both strive to describe the physical world. However, high-fidelity predictive capabilities can often be realized only by numerical computation. CSE’s overarching goal of achieving truly predictive scientific capabilities is its distinguishing factor. It accomplishes this through advances that combine modeling, numerical analysis, algorithms, simulation, big data analytics, high performance computing, and scientific software. The development of predictive capabilities lies at the core of CSE as a new discipline in its own right and has already impacted a number of disciplines, including but not limited to simulation-based design in the automotive industry, simulation-based decisions in computational medicine, and simulation-based predictions of global climate. It is also set to catalyze fundamental changes in many more areas of technical, economic, societal, and political decision processes.
The report also highlights a number of specific CSE “success stories” – application examples in which CSE research is significantly impacting the real world. These accounts emphasize both the long-term payoff of investment in fundamental CSE research and the criticality of sustaining that investment to leverage current and future opportunities—as articulated in the report’s recommendations—for CSE research and education over the next decade.
 Rüde, U., Willcox, K., McInnes, L.C., De Sterck, H., Biros, G., Bungartz, H., Corones, J., Cramer, E., Crowley, J., Ghattas, O., Gunzburger, M., Hanke, M., Harrison, R., Heroux, M., Hesthaven, J., Jimack, P., Johnson, C., Jordan, K.E., Keyes, D.E., Krause, R., Kumar, V., Mayer, S., Meza, J., Mørken, K.M., Oden, J.T., Petzold, L., Raghavan, P., Shontz, S.M., Trefethen, A., Turner, P., Voevodin, V., Wohlmuth, B., & Woodward, C.S. (2016). Research and Education in Computational Science and Engineering. Preprint, arXiv.org. https://arxiv.org/abs/1610.02608.
 SIAM Working Group on CSE Education. (2001). Graduate Education in Computational Science and Engineering. SIAM Review, 43(1), 163-177. http://dx.doi.org/10.1137/S0036144500379745.
Ulrich Rüde heads the chair for simulation at the University of Erlangen-Nürnberg and is leader of the Parallel Algorithms Project at the Centre Européen de Recherche et de Formation Avancée en Calcul Scientifique (CERFACS) in Toulouse. He served as editor-in-chief of the SIAM Journal on Scientific Computing from 2005-2010, and is a SIAM Fellow. Karen Willcox is a professor of aeronautics and astronautics and co-director of the Center for Computational Engineering at the Massachusetts Institute of Technology. Lois Curfman McInnes is a senior computational scientist in the Mathematics and Computer Science Division of Argonne National Laboratory. She co-chaired the 2015 SIAM Conference on CSE and is serving as chair of SIAG/CSE from 2015-16. Hans De Sterck is a professor of computational and applied mathematics in the School of Mathematical Sciences at Monash University in Melbourne, Australia. He co-chaired the 2015 SIAM Conference on CSE and currently serves as a section editor for the SIAM Journal on Scientific Computing. Collectively, the authors served as the 2013-2014 officers of SIAG/CSE.