Transforming Science Through Software: Improving While Delivering 100×

Journal Article · Tue Jul 16 00:00:00 EDT 2024 · Computing in Science and Engineering

DOI:https://doi.org/10.1109/mcse.2024.3400462· OSTI ID:2499768

Gerber, Richard ^[1]; Gottlieb, Steven ^[2]; Heroux, Michael A. ^[3]; McInnes, Lois Curfman ^[4]

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1. Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
2. Indiana Univ., Bloomington, IN (United States)
3. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
4. Argonne National Laboratory (ANL), Argonne, IL (United States)

The U.S. Department of Energy (DOE) Exascale Computing Project (ECP) funded the development of new (and the transformation of important existing) applications, libraries, and tools that realized improvement in performance and capabilities of often 100 times or more on emerging exascale computers. This exceptional gain inspired the title of this special issue: Transforming Science through Software: Improving while delivering 100X. The term 100X refers to advancing capabilities in modeling, simulation, and analysis by a factor of 100 or more using some combination of new algorithms, optimization techniques, software libraries, and programming models, coupled with the next generation of hardware for high-performance computing (HPC). The papers in this issue share experiences with the practice and science of scientific software development, with an emphasis on developing a coherent, portable, and sustainable HPC software ecosystem for next-generation computational science. Finally, we hope to foster expanded community efforts related to the fundamental role of sustainable scientific software ecosystems in advancing the computing sciences.

• Research Organization: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
• Sponsoring Organization: USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities (SUF)
• Grant/Contract Number: AC02-05CH11231
• OSTI ID: 2499768
• Journal Information: Computing in Science and Engineering, Journal Name: Computing in Science and Engineering Journal Issue: 1 Vol. 26; ISSN 1521-9615
• Publisher: IEEE Computer Society
• Country of Publication: United States
• Language: English

Related Subjects

97 MATHEMATICS AND COMPUTING
ecosystems
exascale computing
scientific computing
software development management