BES Greenbook Presentation

1. BES Greenbook Presentation Theresa L. Windus Pacific Northwest National Laboratory

2. The Punch Line Bigger Better More Realistic

3. Materials Sciences Engineering Sciences • catalysis • ceramics • condensed matter physics • corrosion • electronic properties of materials • experimental techniques and instrumentation development • intermetallic alloys • magnetism and magnetic materials • materials physics and chemistry • mechanical and physical behavior • metallic glasses • metallurgy • metals forming • neutron and photon scattering • nondestructive evaluation • photovoltaics • polymer science • radiation effects • solid dynamics • structural characterization • superconductivity • surface science • synthesis and processing science • theory, modeling, and computer simulation • welding and joining • data and engineering analysis • system sciences, control and instrumentation Chemical Sciences • analytical chemistry • atomic, molecular, and optical physics • batteries and fuel cells • chemical kinetics • chemical physics • catalysis - homogeneous and heterogeneous phase • combustion dynamics • electrochemistry • heavy element chemistry • interfacial chemistry • organometallic chemistry • photochemistry • photosynthetic mechanisms • radiation effects • separations science • solar energy conversion • thermophysical properties Geosciences • mineral-fluid reactions • rock deformation • rock-fluid dynamics Biosciences • bioenergetics • biomaterials and biocatalysis • extremophilic organisms • fermentation microbiology • photosynthetic mechanisms • plant and microbial sciences • plant genomics Highlights of Research Supported by BES

4. Types of systems (examples) Quantum nanostructures such as wires, dots, films, tubes and boxes – properties vs. size Semiconductors and insulators – band gaps, laser effects Metal clusters – pressure effects, crack propagation Alloys such as with transition metals - impurities Surface phenomena – Chemical Vapor Deposition (CVD), surface reconstruction, chemi- and physi-sorption Ceramics – synthesis, defects, irradiation Materials Science

5. Nanostructures • Tailor materials at the nanoscale for desired structure/function properties • Materials with enhanced physical, mechanical, optical, electrical, tribological, or catalytic properties • Materials with the ability to self assemble, self repair, sense and respond to the environment • Long-term, high-risk, interagency activity -- a unique instance of common scientific and technological frontiers • Combines expertise in materials sciences, chemistry, physics, biology, engineering, and computation • Expected are technological developments to rival the impact of the transistor Richard Smalley http://cnst.rice.edu/pics.html

6. Materials Properties G. Malcom Stocks http://www. ornl.gov/ORNLReview/v30n3-4/develop.htm • Superconductivity • Band gaps • Local and non-local Density Approximations • Magnetic Properties • Local Density Approximation • O(N) Locally Selfconsistent Multiple Scattering (LSMS)

7. Shapes in Metal Alloys • Sizes and shapes of precipitates is needed for understanding of strengthening mechanisms in metal alloys. • Linear Expansion in Geometric Object, LEGO method: basically a cluster expansion • Scan many different alloys in a relatively quick time • Based on “first-principles” calculations Alex Zunger http://www.sst.nrel.gov/topics/new_mat.html

8. Materials Defects • Surface Reconstruction • Chemisorption • Physisorption • Chemical Vapor Deposition • STM modelling • Corrosion Alex Zunger http://www.sst.nrel.gov/research/defect.html

9. Density Functional based on local orbitals – Local Density Approximation (LDA) or non-local (NLDA) methods Scale roughly as N3 or N4 where N is the number of local orbitals (lower for tight-binding methods) Bottlenecks for scalability tend to be either matrix inversion or eigenvalue problems CPU, memory and disk intensive Types of Algorithms

10. Density Functional with Planewaves – LDA and NLDA Approximately Ne*Na*Nb* # of k points where Ne is the number of electrons, Na is the number of atoms, and Nb is the number of basis functions (planewaves) Bottleneck for scalability is 3-D Fast Fourier Transform – O(Ne*Nb*(logNb)) CPU and memory intensive Types of Algorithms (II)

11. Molecular Dynamics, Monte Carlo, or Car-Parrinello Usually bound by the DFT method (with additional force calculation) Update usually causes additional problems for communication (especially latency) Memory intensive Lots of disk (TB) Types of Algorithms (III)

12. Types of systems (examples) Quantum nanostructures such as wires, dots, films, tubes and boxes – properties vs. size Flames – kinetic effects, turbulence Heavy element systems – thermodynamics, kinetics, excited state properties Excited states – photochemistry, optical properties, and radiation Chemical Sciences

13. Laminar and Turbulent flow Autoignition Diffusion Effects Structure and Propagation Chemical Reactions Flame Chemistry Jackie Chen http://www.ca.sandia.gov/CRF/staff/Chen.html

14. Heavy Element Chemistry • Waste Tank Remediation • Relativistic Effects • Highly Accurate Thermochemistry • Excited State Properties • Solvation Properties

15. Direct Numerical Simulation (DNS) How much physics and chemistry? – Navier-Stokes, energy equations, velocity, time steps, amount of chemistry involved Also depends on the number of grid points (mesh size) Bottlenecks are communication and disk latency and bandwidth; need TB of local disk Types of Algorithms

16. Molecular Mechanics/Molecular Dynamics – O(N) Bottlenecks for scalability are communication latency and disk I/O Load balancing Eigensolvers – O(N3) Bottlenecks for scalability are communication bandwidth and latency Alternate algorithms (second order methods) Many body methods – O(N5) to O(N!) CPU, memory and I/O intensive Bottlenecks for scalability are communication bandwidth and memory (depends on the algorithm) Types of Algorithms (II)

17. Types of Algorithms (III)

18. memoryM/F - the ratio of bytes of memory to flops/sec of computing diskM/F – the ratio of bytes of disk to flops/sec of computing memoryB/F – the ratio of bandwidth between memory and processor in bytes/sec to flops/sec of computing diskB/F – the ratio of bandwidth between disk and processor in bytes/sec to flops/sec of computing netB/F – the ratio of network bandwidth (with latency) in bytes/sec to flops/sec of computing Kiviat diagram of the M/F and B/F ratios for a computer configured for molecular electronic structure calculations (MSCF) and one configured for lattice gauge QCD calculations (QCD). Balanced System Robert Harrison and Jeff Nichols Pacific Northwest National Laboratory

19. Surface properties of clays and minerals Colloidal behavior Use of same methods as in materials sciences Transport processes in porous media Dependent on grid size and chemistry involved Geosciences Garrison Sposito http://esd.lbl.gov/sposito 2.5 million-step Monte Carlo simulation shows that Sodium ions (Na+) in the interlayer of montmorillonite are forming outer-sphere complexes.

20. Extra long batch queues Very low-latency communication system (switch) Large network bandwidth from NERSC to remote sites (especially National Labs) Large number of files Reliable C++ compilers Good parallel debuggers New algorithms Data visualization of very large data sets with synchronous data reduction Other Computational Needs