BES Greenbook Presentation

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15 Νοε 2013 (πριν από 3 χρόνια και 9 μήνες)

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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 BES

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

Materials 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 Sciences

Biosciences


bioenergetics


biomaterials and biocatalysis


extremophilic organisms


fermentation microbiology


photosynthetic mechanisms


plant and microbial sciences


plant genomics

Geosciences


mineral
-
fluid reactions


rock deformation


rock
-
fluid dynamics

2/23/01

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


2/23/01

Nanostructures

Richard Smalley

http://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


2/23/01

Materials Properties

G. Malcom Stocks

http://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

2/23/01

Shapes in Metal Alloys

Alex Zunger

http://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

2/23/01

Materials Defects

Alex Zunger

http://www.sst.nrel.gov/research/defect.html



Surface Reconstruction



Chemisorption



Physisorption



Chemical Vapor Deposition



STM modelling



Corrosion

2/23/01

Types of Algorithms


Density Functional based on local orbitals


Local Density Approximation (LDA) or
non
-
local (NLDA) methods


Scale roughly as N
3

or N
4

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

2/23/01

Types of Algorithms (II)


Density Functional with Planewaves


LDA
and NLDA


Approximately N
e
*N
a
*N
b
* # of k points where
N
e

is the number of electrons, N
a

is the number
of atoms, and N
b

is the number of basis
functions (planewaves)


Bottleneck for scalability is 3
-
D Fast Fourier
Transform


O(N
e
*N
b
*(logN
b
))


CPU and memory intensive

2/23/01

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)



2/23/01

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

2/23/01

Flame Chemistry


Laminar and Turbulent flow


Autoignition


Diffusion Effects


Structure and Propagation


Chemical Reactions

Jackie Chen

http://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

2/23/01

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

2/23/01

Types of Algorithms (II)


Molecular Mechanics/Molecular Dynamics


O(N)


Bottlenecks for scalability are communication
latency and disk I/O


Load balancing


Eigensolvers


O(N
3
)


Bottlenecks for scalability are communication
bandwidth and latency


Alternate algorithms (second order methods)


Many body methods


O(N
5
) to O(N!)


CPU, memory and I/O intensive


Bottlenecks for scalability are communication
bandwidth and memory (depends on the algorithm)

2/23/01

Types of Algorithms (III)

... MM MD QM/MM DFT HF MP2 MP4 CCSD(T) MRSDCI ...
Scaling
O(N)
O(N
7
)
Accuracy
0.1 kcal
100
Size
10
7
10 atoms
Size
10 000 Basis Functions
1 000 Atoms
3 000 Basis Functions
300 Atoms
1 000 Basis Functions
100 Atoms
5
00 Basis Functions
5 000 000 Configurations
10 - 20 Atoms
10
-15
- 10
-8
Seconds
1 000 000 Atoms
2/23/01

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
8
0.035
0.5
memoryM/F
diskM/F
memoryB/F
diskB/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 Nichols

Pacific 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 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.

2/23/01

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