CSE is devoted to the development and use of computational methods for scientific discovery in all branches of the sciences, for the advancement of innovation in engineering and technology, and for the support of decision-making across a spectrum of societally important application areas. CSE is widely recognized as an essential driver of scientific and technological progress in conjunction with theory and experiment.
The broad impact of CSE and next-generation opportunities are summarized in the article: Research and Education in Computational Science and Engineering, U. Rüde, K. Willcox, L.C. McInnes, H. De Sterck, SIAM Review, 2018, led by the SIAM Activity Group on CSE.
Why Is CSE Software So Important?
Software is the key crosscutting technology that connects advances in applied mathematics, computer science, and domain-specific science and engineering for advanced discovery and analysis in CSE. While software is becoming more complex because of multiphysics and multiscale modeling, the coupling of data analytics, and disruptive changes in computer hardware, software itself has not traditionally received focused attention in the CSE community.
The Better Scientific Software community is working to enable software to fulfill its critical role as an essential cornerstone of long-term CSE collaboration and discovery.
What Are Unique Aspects of CSE Software?
Compared with larger software communities for whom much of the software improvement literature has been written, the CSE community has a number of distinct characteristics. In particular:
- Most CSE software developers have an advanced degree and many years of experience in their domain, but little if any formal training in software engineering.
- Many CSE software products are used by the developers and a small group of colleagues.
- Because of the nature of scientific research, CSE software requirements often change as understanding evolves and next steps of research are determined.
CSE software challenges are discussed in the following community reports:
- Software Productivity for Extreme-Scale Science, H. Johansen, L.C. McInnes, et al., 2014, DOE Office of Science.
- Computational Science and Engineering Software Sustainability and Productivity Challenges (CSESSP) Workshop Report, M. Heroux, G. Allen, et al., 2016, Networking and Information Technology Research and Development (NITRD) Program.