2/23/01

BES Greenbook Presentation

Theresa L. Windus

Pacific Northwest National Laboratory

2/23/01

The Punch Line

Bigger

Better

More Realistic

2/23/01

Highlights of Research Supported by BESHighlights of Research Supported by BES

Chemical SciencesChemical 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

Materials SciencesMaterials 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

Engineering SciencesEngineering Sciences

BiosciencesBiosciences bioenergetics biomaterials and biocatalysis extremophilic organisms fermentation microbiology photosynthetic mechanisms plant and microbial sciences plant genomics

GeosciencesGeosciences mineral-fluid reactions rock deformation rock-fluid dynamics

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Materials Science

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

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Nanostructures

Richard Smalleyhttp://cnst.rice.edu/pics.html

•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

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Materials Properties

G. Malcom Stockshttp://www. ornl.gov/ORNLReview/v30n3-4/develop.htm

• Magnetic Properties• Local Density Approximation• O(N) Locally Selfconsistent Multiple Scattering (LSMS)

• Superconductivity• Band gaps• Local and non-local Density Approximations

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Shapes in Metal Alloys

Alex Zungerhttp://www.sst.nrel.gov/topics/new_mat.html

• 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

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Materials Defects

Alex Zungerhttp://www.sst.nrel.gov/research/defect.html

• Surface Reconstruction• Chemisorption• Physisorption• Chemical Vapor Deposition• STM modelling• Corrosion

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Types of Algorithms

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

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Types of Algorithms (II)

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

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Types of Algorithms (III)

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)

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Chemical Sciences

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

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Flame Chemistry

Laminar and Turbulent flow Autoignition Diffusion Effects Structure and Propagation Chemical Reactions

Jackie Chenhttp://www.ca.sandia.gov/CRF/staff/Chen.html

2/23/01

Heavy Element Chemistry

• Waste Tank Remediation• Relativistic Effects• Highly Accurate Thermochemistry• Excited State Properties• Solvation Properties

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Types of Algorithms

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

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Types of Algorithms (II)

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)

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Types of Algorithms (III)

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Balanced System

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

1.2

14

80.035

0.5

memoryM/F

diskM/F

memoryB/FdiskB/F

netB/F

B

B

B

B

B J

J

J

IBM (MSCF)

IBM (QCD)

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).

Robert Harrison and Jeff NicholsPacific Northwest National Laboratory

2/23/01

Geosciences

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

Garrison Spositohttp://esd.lbl.gov/sposito

2.5 million-step Monte Carlo simulation shows that Sodium ions (Na+) in the interlayer of montmorillonite are formingouter-sphere complexes.

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Other Computational Needs

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