Supercomputingat the University of Arkansas

Amy Apon, Ph.D.Oklahoma Supercomputing Symposium

October 5, 2005

Amy Apon, Ph.D. ● Oklahoma Supercomputing Symposium ● October 5, 2005 2

Outline of Talk

• What is the status of supercomputing at the University of Arkansas?– Also in relation to other institutions

• Why do supercomputing at our institution?

• How did we get this far?– Acquiring Red Diamond

• What comes next?

Amy Apon, Ph.D. ● Oklahoma Supercomputing Symposium ● October 5, 2005 3

The Status of Supercomputing at the University of Arkansas

• Red Diamond supercomputer– Number 379 on the Top 500 list, June,

2005– 128 node (256 processor)– 1.349 TFlops (trillion floating point

operations/sec)– First supercomputer in Arkansas– $213K from NSF MRI grant, 08/04, Apon PI

• Co-PIs Pulay, Fu, Bellaiche, Deaton, Selvam, Mattioli, Thompsons, Johnston

– Substantial match from the University– Substantial gift from Dell

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Significance of Red Diamond• Places the University of Arkansas among about 40

peer academic institutions, public and private, holding this quality of resource– As measured by the Top 500 list of the fastest

computers in the world, released every June and November

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Other Academic Supercomputing Sites (partial list only – the map shows the Members of the Coalition for Academic Scientific Computation)

… also include sites in Kansas, Nebraska, Missouri, Alabama, South Carolina, Minnesota, Wisconsin, Maryland, Delaware, and Oregon

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Ranking in Top 500 list, academics in the U.S. by state (Source: http://www.top500.org)

State Jun '05 Rank (29) Nov ‘04 Rank (34) Jun ‘04 Rank (39) Nov ’03 (41)Virginia 14 7 3Illinois 20,38,47,48 10, 22 5, 15, 406 4, 35, 195, 259 Penn 33,68,395 34, 222, 480, 484 25, 295, 297 12, 142,

154, 156 California 37,43,63,66,71,108,162 25, 31, 37, 62, 444 23, 43, 44, 276, 387 63, 137, 171 Utah 53 367 141, 230, 313 177, 248 *Oklahoma 54 253Mass 59 473Texas 74,427,441 40, 248, 449 58, 198, 270, 411 26, 198, 260, 355 New York 117,200,242,326 123, 152, 194, 308 95, 147 38, 68Tennessee 129 413 199*Alaska 136,342 76, 203 56, 154 72, 102, 355 *Louisiana 147 82 65 30Maryland 166Arizona 249 159 118 53Minnesota 307 359 442*Mississippi 367 211 160 166*Arkansas 379*Kentucky 373,468 348 221 117, 302 Florida 394,498 221, 296 190 92Indiana 334 218 114Georgia 376 233Ohio 456 274, 344 180*Nebraska 477 292 317New Jersey 333 173Delaware 453 218North Carolina 183, 395 Michigan 295

*EPSCOR States

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Why do supercomputing?An opportunity for funding!

Continuing supercomputing capability and federal funding levels are correlated!!

Federal Research Funding Rank by Year(Source: http://thecenter.ufl.edu/research_data.html)

180

160

140

120

100

80

60

1998 1999 2000 2001 2002

Year

Ran

k

U. Ken, 302/500 in 11/95

Miss St, 359/500 in 11/96

LSU, 400/500 in 11/95

UN-L, 107/500 in 6/02

U. OK, 197/500 in 11/02

Uark, Top 500 in 6/05

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Federal Funding Directions

• President's Information Technology Advisory Panel encourages the growth of "computational science," or the use of computers to complement experiments and theoretical research.

• The panel calls for more federal spending on supercomputing (Source: Chronicle Daily News 04-15-2005)

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Benefits to Campus Users of a Supercomputing Center

• Over time, we can refocus existing resources to a high-quality centrally-managed facility – avoids duplication of resources on campus– Eliminate need for departmental and research

group clusters– Reduce cost for software licenses, startup funds– Be a focus for supercomputing activity on campus

• Can be an attraction in recruiting top faculty and Ph.D. students

• We have infrastructure to support a larger system– We can work on larger problems

• We become more competitive in grant applications

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How did we get this far?Acquiring Red Diamond• MRI – Major Research Instrumentation

grant from the National Science Foundation

• Only three MRI proposals can be submitted from an institution

• The first year we tried we did not make the campus cut– Amazingly, not everyone believes that we

need supercomputing!!

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NSF MRI Proposal

• Funding is granted based on the quality of research

• Geeky computer science types need not apply– Just evaluating the benefits of a high-

performance network, multi-core processors, even compiler optimizations is probably not enough

• Need to demonstrate the need for computing power for science and engineering research

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Computational Research at the University of Arkansas• Development of middleware tools

(Array Files) for managing, locating, and indexing data for large-scale out-of-core computational chemistry applications. – This research is inherently interdisciplinary

and results are applicable to many other projects in this proposal.

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Computational Research at the University of Arkansas• Computational chemistry in two

major areas, including: – The development of a parallel Coupled-

Cluster Singles and Doubles (CC-SD) code which will run efficiently on a distributed memory system, and

– The development of an efficient parallel version of our Fourier Transform Coulomb (FTC) method for large-scale density functional calculations.

New formulas for new drugs!

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Computational Research at the University of Arkansas

• Materials science, using a state-of-art first-principles density-functional theory (DFT) computational approach.

• The research includes the study of novel nanostructure materials that possess unusual properties of technological importance, in particular: – Nanostructures of ferroelectric (FE) and piezoelectric

oxides which exhibit many electrical, mechanical, and structural properties that are not shared by other materials

Semiconductor nanomaterials!

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Computational Research at the University of Arkansas• DNA sequence design and analysis of

large sets of sequences for biotechnology and nanotechnology applications. – The computing equipment proposed here will

accelerate the search for large sets of non-crosshybridizing DNA sequences.

– These sequences will form a large library for use in DNA computations or nanotechnology

New ways to store huge amounts of information!

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Computational Research at the University of Arkansas• Multiscale modeling, including:

– The computation of electronic and optical properties of nanodevices, the investigation of the issues in multiscale modeling

– Multiscale modeling of crack propagation in alloys and metals

Models of tornados!

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Computational Research at the University of ArkansasOther projects• Models of volcanos• Next generation networking• Geospatial databases• Data mining

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Observations from an MRI panel

• Base the equipment request on research drivers

• Request an appropriately sized resource– For the problem– And with appropriate subcomponents

• An error in the resource description is more easily forgiven than perceived deficiencies in the research, but either can kill the proposal

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What Comes Next?UofA Current Challenges• Education of researchers, faculty &

students– Some of our best scientists still need

education on how to use a distributed memory parallel computer, including MPI, compiler tools

• System administration– Don’t underestimate the amount of time to

administrate a large system – it does not scale linearly!!

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What Comes Next?UofA Current Challenges• Supercomputing operations

– Keep the AC on– Power– UPS– Space

• Usage policies, administration– How do you incorporate usage from new

faculty?– How do you partition usage fairly?

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What Comes Next?UofA Current Challenges• Future grant applications

– Lifespan of a supercomputer is about three years!

• Funding models for on-going operations– How will basic systems administration and

project director be funded?

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What Comes Next?

We are • Increasing campus-level support for HPC• Expanding our computational science

and engineering activities – New researchers and domain areas

• Collaborating (via grid computing) – Within the state– Regionally (OU, GPN, SURA)

• Expanding access to National Lambda Rail

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Questions?

Contact information:http://hpc.uark.eduhttp://comp.uark.edu/~aaponaapon@uark.edu