Simulation and Modeling at the
Exascale for Energy, Ecological Sustainability and Global Security (E3SGS)
Town Hall Meeting

April 17 - 18, 2007

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ORNL Town Hall Meeting

ANL Town Hall Meeting

B1. Improve our understanding of complex biogeochemical (C, N, P, etc.) cycles that underpin global ecosystems functions and control the sustainability of life on Earth.

• Summary
• Draft Write-up

B2. Develop and optimize new pathways for renewable energy production and development of long-term secure nuclear energy sources, through computational nanoscience and physics-based engineering models.

• Summary (Nanoscience)

B3. Enhance our understanding of the roles and functions carried out by microbial life on Earth, and adapt these capabilities for human use, through bioinformatics and computational biology.

• Summary
• E3SGS (Edwards)
• Challenges Facing High-performance Biological Computing (Konerding)
• Rationale for Continuously Increasing Computation Infrastructure (Kyrpides, Ivanova)
• Dealing with the Sequence Data Avalanche (Oehmen)
• Navigating the Proteome Universe (Sjolander)

B4. Develop tools and methods to protect the distributed information technology infrastructure: ensuring network security, preventing disruption of our communications infrastructure, and defending distributed systems against attacks.

• Summary
• Detailed Notes
• High-Performance Computing and Distributed Systems - Some Observations (Catlett)
• Security in E3SGS (Agarwal)

B5. Drive innovation at the frontiers of computer architecture and information technology, preparing the way for ubiquitous adoption of parallel computing, power-efficient systems, and the software and architectures needed for a decade of increased capabilities. Accelerate the development of special-purpose devices that have the potential to change the simulation paradigm for certain science disciplines.

• Summary
• Introduction (Strohmaier)
• Architecture (Gropp, Beckman, Thakur)
• Computational Sciences at ORNL (Poole, Vetter)
• Climate Modeling at the Multi-Petaflop Scale Using Semi-custom Computing (Oliker)
• Exascale Technologies (Asanovic)
• Architecture Paths to Exaflops Computing (Sterling)
• Meeting the Challenge of Massive Parallelism (Shalf)
• Architecture Session Panel (DeBenedictis)
• Technology Uptake: Architecture (Pennington)
• How Can Computer Science Help Enable Exascale Computing? (Snavely)
• Programming Models for Exascale (Yelick)

B6: Develop integrated modeling environments that couple the wealth of observational data and complex models to economic, energy, and resource models that incorporate the human dynamic into large-scale global change analysis.

• Summary

B7. Advance mathematical and algorithmic foundations to support scientific computing in emerging disciplines such as molecular self- assembly, systems biology, behavior of complex systems, agent-based modeling and evolutionary and adaptive computing.

• Advances in Mathematics and Algorithms

B8. Integrate large, complex, and possibly distributed software systems with components derived from multiple applications domains and with distributed data gathering and analysis tools.

• Summary of Goal 8 discussions presented to all the participants
• Presentations on Software Integration and Scientific Data Management during the breakout session
• Presentations on Analytics and Visualization during the breakout session

B9. Develop a “cosmic simulator” capability that integrates increasingly complex astrophysical measurements with simulations of the growth and evolution of structure in the universe, linking the known laws of microphysics to the macro world. Develop large-scale, special-purpose computing devices and innovative algorithm development to achieve this goal.

• Summary
• The Grand Challenges in Physical Cosmology (Abel)
• Computational Nuclear Astrophysics at the Exascale (Calder, Lattimer, Myra, Swesty, Zingale)
• Foundations for a Cosmic Simulator
• Computing The Cosmos - From Big Bang To Black Holes (Borrill)

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