2011-12: Extreme-scale Algorithms and Software Institute

November 20th, 2013

The Extreme-scale Algorithms and Software Institute (EASI), formed by Oak Ridge National Laboratory, Sandia National Laboratories and the Universities of Illinois, Tennessee, and California Berkeley, focuses on closing the “application-architecture performance gap” through architecture-aware algorithms and libraries, and the supporting runtime capabilities to achieve scalable performance and resilience on heterogeneous architectures. Specifically, EASI aims at: (1) studying and characterize the application-architecture performance gaps that we can address in the near-term and identify architecture features that future systems may want to incorporate; (2) developing multi-precision and architecture-aware implementations of Krylov, Poisson and Helmholtz solvers, and dense factorizations for heterogeneous multi-core systems; (3) exploring new methods of algorithm resilience, and develop new algorithms with these capabilities; (4) developing runtime support for adaptable algorithms dealing with resilience, scalability, and performance; (5) demonstrating architecture-aware algorithms in full U.S. Department of Energy (DOE) applications on large-scale DOE architectures; (6) distributing the new algorithms and supporting runtime capabilities through widely used software packages; and (7) establishing a strong outreach program to disseminate results, interact with colleagues and train students and junior members of our community.

Solutions

Participating Institutions

Funding Sources

Important Publications

Symbols: Abstract Abstract, Publication Publication, Presentation Presentation, BibTeX Citation BibTeX Citation, DOI Link DOI Link

  1. Christian Engelmann. Scaling To A Million Cores And Beyond: Using Light-Weight Simulation to Understand The Challenges Ahead On The Road To Exascale. Future Generation Computer Systems (FGCS), volume 30, number 0, pages 59-65, 2014. Elsevier B.V, Amsterdam, The Netherlands. ISSN 0167-739X. Abstract Publication BibTeX Citation DOI Link
  2. Christian Engelmann. Investigating Operating System Noise in Extreme-Scale High-Performance Computing Systems using Simulation. In Proceedings of the 11th IASTED International Conference on Parallel and Distributed Computing and Networks (PDCN) 2013, Innsbruck, Austria, February 11-13, 2013. ACTA Press, Calgary, AB, Canada. ISBN 978-0-88986-943-1. Abstract Publication Presentation BibTeX Citation

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