Computer
Method May Help Humans Achieve Energy Independence From Fossil
Fuels
Friday, November 7, 2008
A
test run of LS3DF, which took one hour on 17,000 processors
of Franklin, performed electronic structure calculations for
a 3500atom ZnTeO alloy. Isosurface plots (yellow) show the
electron wavefunction squares for the bottom of the
conduction band (left) and the top of the oxygeninduced
band (right). The small grey dots are Zn atoms, the blue
dots are Te atoms, and the red dots are oxygen atoms.

Credit:
Berkeley Lab's Computing Sciences
The key to energy
independence from petroleum, coal and other fossil fuels, could
be tiny materials called nanostructures. At approximately 100,000
times finer than human hair, these structures maybe microscopic
individually, but in groups of thousands, they could
revolutionize solarcell design by providing a costefficient
resource for harvesting solarenergy.
To theoretically understand and
simulate the energy harnessing potential of nanostructures, a
team of researchers in the Berkeley Lab’s Computational
Research Division (CRD) developed the Linear Scaling Three
Dimensional Fragment (LS3DF) method. The computer algorithms in
this method use a “divideandconquer” technique to
efficiently gain insights into how nanostructures function in
systems with 10,000 or more atoms.
“By incorporating the
correct chemical formulas into efficient computer programs,
scientists can learn a lot about the structures and properties of
molecules and solids.… I like to think of computers as
chemistry’s ‘third leg.’ In most cases,
computer simulations complement information obtained by chemical
experiments, but in some cases it can predict unobserved
phenomena,” says Dr. LinWang Wang, a CRD computational
material scientist and leader of the LS3DF project.
The developers of LS3DF are
finalists in the Association for Computing Machinery’s
(ACM) Gordon Bell Prize Competition, which recognizes outstanding
achievement in highperformance computing applications. The
winners will be announced on November 20, 2008 at the SC08
Conference in Austin, Tex.
According to Wang, traditional
methods for calculating the energy potential of nanostructure
systems containing 10,000 or more atoms can be very time
consuming and resource intensive. Because these techniques
calculate the entire structure as a whole system, the compute
time, disk space and memory required to determine the energy
potential of these structures grows to the third power of the
system’s size. That means calculating a 1000atom system
will be a thousand times more expensive than calculating a
100atom system.
He notes that LS3DF offers a
more efficient way for calculating energy potential because it is
based on the observation that the total energy of a large
nanostructure system can be broken down into small pieces, and
each piece can be calculated separately. Wang refers to this
technique as “divideandconquer.”
The total energy of the large
system has two components: electrostatic energy and quantum
mechanical energy. To determine the structure’s total
quantum mechanical energy, the LS3DF method breaks the entire
structure into small fragments, applies its algorithm to each
individual piece, and then combines the results of the pieces to
get a total for the whole system. Scientists say that under the
traditional density functional theory methods, the quantum
mechanical energy calculation typically requires the most compute
time and resources. By breaking up the big problem into small
pieces, LS3DF can solve it a lot more quickly and efficiently,
making the computational cost proportional to the total number of
the atoms in the system.
Meanwhile, the electrostatic
energy of largescale nanostructure systems is not as resource
intensive to solve. Scientists calculate this classical energy by
looking at the whole system, which may contain tens of thousands
of atoms. This problem is solved separately from the quantum
mechanic energy. In the end, both energy results are combined to
get the structure’s total energy potential.
When team members tested the
LS3DF method on supercomputers at the Department of Energy’s
(DOE) National Energy Scientific Research Center (NERSC) in
Oakland, Calif, National Center for Computational Sciences (NCCS)
at Oak Ridge National Laboratory in Oak Ridge, Tenn., and Argonne
Leadership Computing Facility in Argonne, Ill., they found that
the LS3DF method can work hundreds to thousands of times faster
than traditional density functional theory calculations for
systems with tens of thousands of atoms, and yielded essentially
the same results.
“The core of LS3DF is a
novel patching scheme that cancels out the artificial boundary
effects caused by dividing the system into smaller fragments,”
says Wang. “This cancellation is what gets us the same
results as the traditional method.”
Because LS3DF scales almost
perfectly with the number of compute cores, it is the first
electronic structure code that runs efficiently on computer
systems with tens to hundreds of thousands of cores. On 17,280
cores of the dualcore Cray XT4 (Franklin) at NERSC, LS3DF
achieved 32 Tflop/s or 32% of the peak floatingpoint performance
of the machine. On 30,720 cores of the quadcore Cray XT4
(Jaguar) at NCCS, LS3DF reached 60 Tflop/s or 23% of the
theoretical peak. In a later run on the IBM BlueGene/P system
(Intrepid) at Argonne, the code achieved 107.5 Tflop/s on 131,072
cores, or 24.2% of peak.
Energy Independence from Fossil
Fuels
Scientists agree that a
fundamental understanding of nanostructure behaviors and
properties could provide a solution for curbing our dependence on
petroleum, coal, and other fossil fuels.
According to Wang,
nanostructure systems are cheaper to produce than the crystal
thin films used in current solar cell designs, and offer the same
material purity. In addition, nanostructures are extremely
versatile. They can act as electrodes to carry electric currents,
or active materials that absorb sunlight and convert it to
electricity.
One type of nanostructure,
called quantum dots, actually changes color with size. Scientists
say this color, or band gap, affects the type of light that the
structure absorbs, which will be very useful for designing
solarcells.
“We still don't quite
understand how the electron moves around in a nanostructure, and
how such properties depend on the size, geometry, composition,
and surface passivations … Understanding such dependence
will allow us to design nanostructures for desired applications,
and LS3DF can help us to understand and predict these properties
with computers,” says Wang.
Other authors on the Gorden
Bell paper include the Berkeley Lab’s David H. Bailey,
Zhao, Byounghak, Zhengji Lee, Juan Meza, Hongzhang Shan, and
Erich Strohmaier.
Source:
Berkeley Lab's Computing Sciences / Linda Vu

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