Scaling science applications on blue gene

William D. Gropp, Wolfgang Frings, Marc André Hermanns, Ed Jedlicka, Kirk E. Jordan, Fred Mintzer, Boris Orth

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Massively parallel supercomputers like IBM's Blue Gene/L offer exciting new opportunities for scientific discovery by enabling numerical simulations on an unprecedented scale. However, achieving highly scalable performance is often not straightforward as the system's extraordinary level of parallelism and its specialized nodes present challenges to applications in many areas, including: communication efficiency, memory usage, and I/O. This mini-symposium aimed to highlight some of the remarkable scaling and performance results achieved, and bring together users and system experts to discuss possible solutions to yet unresolved issues. It featured speakers whose applications have run at large scale on the 8K node system at John von Neumann Institute for Computing at Forschungszentrum Jülich and the 20K node system at IBM's Watson Research Center. The talks provided a sampling of the different applications and algorithms that have successfully run on Blue Gene. The speakers discussed best practices, particularly with respect to scaling to tens of thousands of processes, and challenges faced in using BlueGene/L to massive scale, and they showcased some of the breakthrough science that has already been achieved.

Original languageEnglish (US)
Title of host publicationParallel Computing
Subtitle of host publicationArchitectures, Algorithms and Applications
PublisherIOS Press BV
Number of pages2
ISBN (Print)9781586037963
StatePublished - 2008
Externally publishedYes

Publication series

NameAdvances in Parallel Computing
ISSN (Print)0927-5452

ASJC Scopus subject areas

  • General Computer Science


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