The SIAM Conference on Parallel Processing for Scientific Computing (PP18) features an invited presentation on how software ecosystems can help to improve software productivity and sustainability.


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Published March 07, 2018

The Society for Industrial and Applied Mathematics presents the Eighteenth Conference on Parallel Processing for Scientific Computing. This series of conferences has played a key role in promoting parallel scientific computing, algorithms for parallel systems, and parallel numerical algorithms. The conference is unique in its emphasis on the intersection between high performance scientific computing and scalable algorithms, architectures, and software. The conference provides a forum for communication among the applied mathematics, computer science, and computational science and engineering communities.

PP18 Invited Presentation on Software Ecosystems

Toward Community Software Ecosystems for High-Performance Computational Science

Speaker: Lois Curfman McInnes, Argonne National Laboratory

Abstract: Software—crosscutting technology that connects advances in mathematics, computer science, and domain-specific science and engineering—is a cornerstone of long-term collaboration and scientific progress.  As we leverage unprecedented high-performance computing resources to work toward predictive science, software complexity is increasing due to multiphysics and multiscale modeling, the coupling of simulations and data analytics, and the demand for greater reproducibility in the midst of disruptive architectural changes.  Applications increasingly require the combined use of independent software packages, which have diverse sponsors, priorities, and processes for development and release.

These challenges create the unique opportunity to fundamentally change how scientific software is designed, developed, and sustained---with explicit work toward scientific software ecosystems. This presentation will introduce the xSDK, or Extreme-scale Scientific Software Development Kit, where community-defined policies are increasing the quality and interoperability across numerical libraries as needed by the DOE Exascale Computing Project.  We will also discuss complementary efforts to increase scientific software productivity and sustainability.