
Features:
NCAR'S SCD RESEARCHES ULTIMATE ALGORITHMS, ARCHITECTURES
by Lynda Lester, Writer/Editor, CISL (NCAR)
The National Center for Atmospheric Research (NCAR) faces big challenges in
its efforts to provide high-end computing for the scientific community.
Researchers have an urgent and ever-increasing need for compute cycles, while
the Mesa Lab Computer Room has been pushed far beyond its original design
limits in its capacity to provide power, air conditioning, and floor space for
modern supercomputers.
New numerical methods for high-performance computing being developed by the
Scientific Computing Division's Computational Science Section (CSS), coupled
with an innovative computer architecture from IBM called Blue Gene/L, may
provide solutions to these challenges.
Computer scientists and applied mathematicians in CSS are building an
accurate, efficient, and scalable general circulation model called the High-
Order Multiscale Modeling Environment (HOMME). HOMME employs advanced
algorithms and computing techniques that will allow it to use tens of
thousands of processors effectively.
The model is currently running at blazing speed on IBM's BlueGene/L, a
densely-packed, massively parallel computer that requires a fraction of the
power and space of most production systems.
Crunch time
"It makes for an interesting story," says CSS computational scientist Steve
Thomas. "Researchers in the geosciences are saying, 'We need one hundred times
the computing power within the next five years.' And we're seeing faster and
faster computers -- speed, of course, meaning a faster clock speed, and thus
chips that generate more heat. But our computing facility is already nearing
the limit -- we're close to maxed out in terms of floor space and the amount of
electricity and cooling we can provide to the Computer Room.
"So it's crunch time, literally. We have to decide, are we going to move to a
new facility, build a new facility, or make do with what we have now? This is
not pie in the sky, it's not looking down the road. This is not the long-term
future, it's here and now."
Faced with this critical situation, Steve, Rich Loft, and Henry Tufo in CSS
have been studying ways to use low-power microprocessors effectively. As
BlueGene/L has been particularly interesting in this regard, CSS, in
collaboration with researchers from CU-Denver and CU-Boulder, submitted a
proposal early in 2004 to the National Science Foundation's Major Research
Infrastructure program. The objective was to acquire a 1,024-node BlueGene/L
system to study the performance of scalable applications on it and to evaluate
BlueGene/L's production capabilities. NSF has funded the proposal, and SCD is
currently negotiating with IBM to obtain a BlueGene/L in Spring 2005.
Running at 5.7 teraflops peak (or 2.8 teraflops in co-processor mode), the
machine would outperform blackforest, NCAR's IBM SP/6000 (1.962 teraflops
peak). It would also occupy a fraction of the floor space and consume far less
power.
Scalability: Key to performance
But to deliver the highest performance, BlueGene/L requires massively parallel
applications that can scale.
And while, for instance, NCAR's Community Climate Systems Model (CCSM) can
scale to a few hundred processors, HOMME can scale to tens of thousands.
"In 2001, we ran HOMME at Lawrence Berkeley Lab on 2,000 processors and got
400 gigaflops sustained at typical climate resolutions slightly higher than
the CCSM," says Steve. "And Mark Taylor of Sandia National Laboratory recently
did some benchmarking with HOMME using 9,000 processors on the ASCI Red
machine. Right now we're running HOMME on 8,000 processors on the prototype
BlueGene/L in Rochester, New York. We've hit 1.5 teraflops, and that's just
the first pass."
HOMME: A unique modeling environment for climate research
HOMME is being developed by Steve Thomas, Amik St. Cyr, Henry Tufo, and John
Dennis of CSS and Theron Voran, a student of Dr. Tufo at the University of
Colorado. Other participants and collaborators are John Clyne and Joey Mendoza
of SCD's Visualization and Enabling Technologies Section; Jim Edwards, IBM's
site analyst at NCAR; and Gyan Bhanot, Bob Walkup, and Andii Wyszogrodzki of
IBM's T. J. Watson Research Center.
HOMME is written in Fortran 90 and contains three components: a dynamical
core, an atmospheric physics component, and a dynamics/physics coupler.
The core. The dynamical core provides the computational foundation for solving
the fluid dynamics equations necessary to study the atmosphere. It supports
several different schemes for modeling spatial and temporal data.
The dynamical core is based on the spectral element numerical method, which
requires fewer communications between processors and runs more efficiently on
a higher number of CPUs than the spherical harmonic method used in many
traditional models. This method allows modelers to add more grid points over
interesting geographic areas or to resolve important aspects of the flow being
modeled. This process, called "adaptive mesh refinement," permits higher
spatial resolutions in selected areas.
The core also employs a new approach to temporal discretization (i.e.,
breaking up data into time periods), allowing modelers to take longer time
steps. The approach -- a combination of semi-implicit with semi-Lagrangian time-
stepping -- potentially more than doubles the integration rate, or the speed at
which a day of climate can be simulated. It also enhances parallelization for
new computer architectures such as BlueGene/L.
However, in order for the dynamical core to be fully useful for atmospheric
scientists, it must be coupled to physics packages employed by the community.
The physics. CSS is now integrating physics from NCAR's Community Atmosphere
Model (CAM) into HOMME. This adds the ability to model moisture and its
profound effects on the atmosphere -- or instance, how clouds interact with
radiation from the to sun affect land, oceans, and ice.
Modelers generally simulate cloud formation using crude parameters, since
directly simulating cloud processes on a global scale requires a massive
increase in computational power. A technique called super-parameterization,
which improves the simulation of cloud processes, is not often used because it
is two to three orders of magnitude more computationally intensive than
traditional techniques. However, with the advent of BlueGene/L, super-
parameterization becomes a reasonable option. CSS and their collaborators have
built a super-parameterization package and are currently coupling it to HOMME.
"A lot has been done this year in terms of adding more realistic physics and
physical processes to HOMME," says Steve. "We're beyond Physics 101. Hopefully
within the next year, we'll have a full climate model."
The coupler. CSS is working with IBM's Jim Edwards to use the Earth System
Modeling Framework (ESMF) to couple HOMME's dynamical core to the physics
component. ESMF is a software infrastructure that allows different weather,
climate, and data-assimilation components to operate together on parallel
supercomputers. The ESMF project is an interagency collaboration, with its
core implementation team based in CSS.
Ultimate algorithms, ultimate architecture
The work with HOMME and BlueGene/L is part of CSS's mission to track computer
technology, extract performance from it, and pioneer new and efficient
numerical methods. The result will be an atmospheric model capable of
exploiting BlueGene/L's scalability and computational power -- and advancing
NCAR's research agenda by leaps and bounds.
As CSS scientist Amik St. Cyr puts it, "We're researching the ultimate
numerical algorithms tied to the ultimate architecture for producing science
faster."
NCAR is operated by the University Corporation for Atmospheric Research (UCAR)
under the primary sponsorship of the National Science Foundation.
For more information
To learn more about SCD's activities in applied computer science and
mathematics, see the computational science research section of SCD's Annual
Scientific Report:
http://www.asr.ucar.edu/2004/SCD/achievements.html#research
Additional information on HOMME is on the web at:
http://www.homme.ucar.edu
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