2011-12: Extreme-scale Algorithms and Software Institute
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.
- Office of Advanced Scientific Computing Research, Office of Science, U.S. Department of Energy
Symbols: Abstract, Publication, Presentation, BibTeX Citation, DOI Link
- 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.
- 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.