- McInnes, Lois Curfman;
- Heroux, Michael A;
- Bernholdt, David E;
- Dubey, Anshu;
- Gonsiorowski, Elsa;
- Gupta, Rinku;
- Marques, Osni;
- Moulton, J David;
- Nam, Hai Ah;
- Norris, Boyana;
- Raybourn, Elaine M;
- Willenbring, Jim;
- Almgren, Ann;
- Bartlett, Roscoe A;
- Cranfill, Kita;
- Fickas, Stephen;
- Frederick, Don;
- Godoy, William F;
- Grubel, Patricia A;
- Hartman-Baker, Rebecca;
- Huebl, Axel;
- Lynch, Rose;
- Malviya-Thakur, Addi;
- Milewicz, Reed;
- Miller, Mark C;
- Mundt, Miranda R;
- Palmer, Erik;
- Parete-Koon, Suzanne;
- Phinney, Megan;
- Riley, Katherine;
- Rogers, David M;
- Sims, Benjamin;
- Stevens, Deborah;
- Watson, Gregory R
Computational and data-enabled science and engineering are revolutionizing advances throughout science and society, at all scales of computing. For example, teams in the U.S. Department of Energy's Exascale Computing Project have been tackling new frontiers in modeling, simulation, and analysis by exploiting unprecedented exascale computing capabilities-building an advanced software ecosystem that supports next-generation applications and addresses disruptive changes in computer architectures. However, concerns are growing about the productivity of the developers of scientific software. Members of the Interoperable Design of Extreme-scale Application Software project serve as catalysts to address these challenges through fostering software communities, incubating and curating methodologies and resources, and disseminating knowledge to advance developer productivity and software sustainability. This article discusses how these synergistic activities are advancing scientific discovery-mitigating technical risks by building a firmer foundation for reproducible, sustainable science at all scales of computing, from laptops to clusters to exascale and beyond.