Understanding the landscape of scientific software used on high-performance computing platforms
Scientific discovery increasingly relies on computation through simulations, analytics, and machine and deep learning. Of these, simulations on high-performance computing (HPC) platforms have been the cornerstone of scientific computing for more than two decades. However, the development of simulation software has, in general, occurred through accretion, with a few exceptions. With an increase in scientific understanding, models have become more complex, rendering an accretion mode untenable to the point where software productivity and sustainability have become active concerns in scientific computing. Here, we examine a modest set of HPC scientific simulation applications that are already using cutting-edge HPC platforms. Several have been in existence for a decade or more. Our objective in this survey is twofold: first, to understand the landscape of scientific computing on HPC platforms in order to distill the currently scattered knowledge about software practices that have helped both developer and software productivity, and second, to understand the kind of tools and methodologies that need attention for continued productivity.
- Research Organization:
- Argonne National Laboratory (ANL), Argonne, IL (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR); USDOE National Nuclear Security Administration (NNSA)
- Grant/Contract Number:
- AC02-06CH11357; 17-SC-20-SC
- OSTI ID:
- 1582735
- Alternate ID(s):
- OSTI ID: 1774616
- Journal Information:
- International Journal of High Performance Computing Applications, Vol. 34, Issue 4; ISSN 1094-3420
- Publisher:
- SAGECopyright Statement
- Country of Publication:
- United States
- Language:
- English
Web of Science
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