Scientific Discovery through Advanced Computing
The U.S. Department of Energy's Scientific Discovery through Advanced Computing (SciDAC)
program brings together the nation's top researchers to tackle challenging scientific problems.
The Office of Advanced Scientific Computing
Research in DOE's Office of Science supports multidisciplinary SciDAC projects aimed at
developing future energy sources, studying global climate change, accelerating research in
designing new materials,improving environmental cleanup methods, and understanding physics
from the tiniest particles to massive supernovae explosions.
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ComPASS team helps diagnose a CEBAF issue
At Jefferson Lab, scientists use CEBAF (Continuous Electron Beam Accelerator Facility)
and three experimental halls to study quarks, gluons, protons and neutrons inside the nucleus with CEBAF and its three experimental halls. Much like a giant, powerful microscope, CEBAF enables scientists to "see" things a million times smaller than an atom. This unprecedented view of the basic building blocks of ordinary matter and their interactions is allowing us to gain deeper insight into the particles and forces that build our universe.
When researchers encountered an issue with the beam break up (BBU) in the CEBAF accelerator, they turned to Kwok Ko, Cho Ng, and the ComPASS team for assistance.
Utilizing the advanced codes (such as SLAC ACD) developed under the SciDAC program, the ComPASS team was able to accurately model the superconducting cavity configuration installed in Jlab's prototype cryomodule
and, from external measurements, "reverse engineer" what must have happened during assembly. The BBU issue was tracked and attributed to a particular cavity which had a non-standard preparation history, one that resulted in a mechanical distortion of the shape.
The cavity performed well in normal operating mode, but a higher-order mode (HOM) that should have been damped was tilted away from the coupler designed to extract it.
By using the unique and highly accurate algorithms and solvers developed at SLAC, Volkan Akcelik,
Zenghai Li and their colleagues were able to reconstruct the cell-by-cell distortions that must have
occurred. They predicted the cavity variance and examination of inspection records corroborated their
prediction. Beam-based measurements confirmed the effect of this distortion in the dynamics of the CEBAF Linac. With this understanding Jlab is now able to develop improved procedures to check future
cavities to prevent reoccurrance of this undesirable effect.
discovery highlights archive
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Terence Critchlow Inducted as Senior Member of ACM
Terence Critchlow, Associate Director of Scientific Data Management at PNNL, has been elected a Senior Member of the Association for Computing Machinery (ACM).
Terence is one of 395 members inducted into the ACM Senior Member program this year.
The program, initiated in 2006, includes members with at least 10 years of professional experience who have demonstrated performance that sets them apart from their peers through technical leadership, and technical or professional contributions. ACM Senior Member status recognizes the top 25 percent of ACM Professional Members for their demonstrated excellence in the computing field. ACM's Senior Members join a distinguished list of colleagues to whom ACM and its members look for guidance and leadership in computing and information technology.
scientist highlights archive |
SciDAC’s VACET Team Demonstrates Tools for Analyzing Massive Datasets
 | The left image is a volume rendering of supernova simulation data generated by running the VisIt application on 32,000 processors on Franklin, a Cray XT4 supercomputer at NERSC.
The right image is an isosurface rendering of the same data created by running VisIt on JaguarPF, a Cray XT5 supercomputer at the Oak Ridge Leadership Computing Facility at ORNL
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As computational scientists are confronted with increasingly massive datasets from supercomputing simulations and experiments, one of the biggest challenges is having the right tools to gain scientific insight from the data. A team of DOE researchers recently ran a series of experiments to determine whether VisIt, a leading scientific visualization application, is up to the challenge. Running on some of the world’s most powerful supercomputers, VisIt achieved unprecedented levels of performance in these highly parallel environments, tackling data sets far larger than scientists are currently producing.
The team ran VisIt using 8,000 to 32,000 processing cores to tackle datasets ranging from 500 billion to 2 trillion zones, or grid points. The project was a collaboration among leading visualization researchers from Lawrence Berkeley National Laboratory, Lawrence Livermore National Laboratory, and Oak Ridge National Laboratory.
Specifically, the team verified that VisIt could take advantage of the growing number of cores powering the world’s most advanced supercomputers, using them to tackle unprecedentedly large problems. Scientists confronted with massive datasets rely on data analysis and visualization software such as VisIt to “get the science out of the data,” as one researcher said. VisIt, a parallel visualization and analysis tool that won an R&D 100 award in 2005, was developed at LLNL for the National Nuclear Security Administration.
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