The supercomputer at the DOE Oak Ridge National Laboratory will be renamed "Titan" after it is beefed up with speedy, powerful chips from California companies NVIDIA and Advanced Micro Devices.

"All areas of science can benefit from this substantial increase in computing power, opening the doors for new discoveries that so far have been out of reach," said associate lab director for computing Jeff Nichols.

"Titan will be used for a variety of important research projects, including the development of more commercially viable biofuels, cleaner burning engines, safer nuclear energy and more efficient solar power."

NVIDIA specializes in GPU (graphics processing unit) chips used to enable seamless, rich graphics and smooth action in videogames by processing myriad tasks simultaneously through parallel computing.

Rival company AMD will provide powerful chips that process data in sequence as is standard in home or work computers.

"Oak Ridge's decision to base Titan on Tesla GPUs underscores the growing belief that GPU-based heterogeneous computing is the best approach to reach exascale computing levels within the next decade," said NVIDIA chief technology officer Steve Scott.

Cray valued the multi-year contract at more than $97 million and said that Titan will be at least twice as fast and three times as energy efficient as today's fastest supercomputer, which is located in Japan.

]]> Wed, 08 FEB 2012 08:47:35 AEST Santa Cruz CA (SPX) Oct 04, 2011 - "Bolshoi" supercomputer simulation provides new benchmark for cosmological studies. The Bolshoi supercomputer simulation, the most accurate and detailed large cosmological simulation run to date, gives physicists and astronomers a powerful new tool for understanding such cosmic mysteries as galaxy formation, dark matter, and dark energy.

The simulation traces the evolution of the large-scale structure of the universe, including the evolution and distribution of the dark matter halos in which galaxies coalesced and grew. Initial studies show good agreement between the simulation's predictions and astronomers' observations.

"In one sense, you might think the initial results are a little boring, because they basically show that our standard cosmological model works," said Joel Primack, distinguished professor of physics at the University of California, Santa Cruz.

"What's exciting is that we now have this highly accurate simulation that will provide the basis for lots of important new studies in the months and years to come."

Primack and Anatoly Klypin, professor of astronomy at New Mexico State University, lead the team that produced the Bolshoi simulation. Klypin wrote the computer code for the simulation, which was run on the Pleiades supercomputer at NASA Ames Research Center. "These huge cosmological simulations are essential for interpreting the results of ongoing astronomical observations and for planning the new large surveys of the universe that are expected to help determine the nature of the mysterious dark energy," Klypin said.

Primack, who directs the University of California High-Performance Astrocomputing Center (UC-HIPACC), said the initial release of data from the Bolshoi simulation began in early September.

"We've released a lot of the data so that other astrophysicists can start to use it," he said. "So far it's less than one percent of the actual output, because the total output is so huge, but there will be additional releases in the future."

The previous benchmark for large-scale cosmological simulations, known as the Millennium Run, has been the basis for some 400 papers since 2005. But the fundamental parameters used as the input for the Millennium Run are now known to be inaccurate. Produced by the Virgo Consortium of mostly European scientists, the Millennium simulation used cosmological parameters based on the first release of data from NASA's Wilkinson Microwave Anisotropy Probe (WMAP).

WMAP provided a detailed map of subtle variations in the cosmic microwave background radiation, the primordial radiation left over from the Big Bang. But the initial WMAP1 parameters have been superseded by subsequent releases: WMAP5 (five-year results released in 2008) and WMAP7 (seven-year results released in 2010).

The Bolshoi simulation is based on WMAP5 parameters, which are consistent with the later WMAP7 results. "The WMAP1 cosmological parameters on which the Millennium simulation is based are now known to be wrong," Primack said.

"Moreover, advances in supercomputer technology allow us to do a much better simulation with higher resolution by almost an order of magnitude. So I expect the Bolshoi simulation will have a big impact on the field."

The standard explanation for how the universe evolved after the Big Bang is known as the Lambda Cold Dark Matter model, and it is the theoretical basis for the Bolshoi simulation. According to this model, gravity acted initially on slight density fluctuations present shortly after the Big Bang to pull together the first clumps of dark matter.

These grew into larger and larger clumps through the hierarchical merging of smaller progenitors. Although the nature of dark matter remains a mystery, it accounts for about 82 percent of the matter in the universe. As a result, the evolution of structure in the universe has been driven by the gravitational interactions of dark matter.

The ordinary matter that forms stars and planets has fallen into the "gravitational wells" created by clumps of dark matter, giving rise to galaxies in the centers of dark matter halos.

A principal purpose of the Bolshoi simulation is to compute and model the evolution of dark matter halos. The characteristics of the halos and subhalos in the Bolshoi simulation are presented in a paper that has been accepted for publication in the Astrophysical Journal and is now available online. The authors are Klypin, NMSU graduate student Sebastian Trujillo-Gomez, and Primack.

A second paper, also accepted for publication in the Astrophysical Journal and available online, presents the abundance and properties of galaxies predicted by the Bolshoi simulation of dark matter. The authors are Klypin, Trujillo-Gomez, Primack, and UCSC postdoctoral researcher Aaron Romanowsky. A comparison of the Bolshoi predictions with galaxy observations from the Sloan Digital Sky Survey showed very good agreement, according to Primack.

The Bolshoi simulation focused on a representative section of the universe, computing the evolution of a cubic volume measuring about one billion light-years on a side and following the interactions of 8.6 billion particles of dark matter. It took 6 million CPU-hours to run the full computation on the Pleiades supercomputer, recently ranked as the seventh fastest supercomputer in the world.

A variant of the Bolshoi simulation, known as BigBolshoi or MultiDark, was run on the same supercomputer with the same number of particles, but this time in a volume 64 times larger. BigBolshoi was run to predict the properties and distribution of galaxy clusters and other very large structures in the universe, as well as to help with dark energy projects such as the Baryon Oscillation Spectroscopic Survey (BOSS).

Another variant, called MiniBolshoi, is currently being run on the Pleiades supercomputer. MiniBolshoi focuses on a smaller portion of the universe and provides even higher resolution than Bolshoi.

The Bolshoi simulation and its two variants will be made publicly available to astrophysical researchers worldwide in phases via the MultiDark Database, hosted by the Potsdam Astrophysics Institute in Germany and supported by grants from Spain and Germany.

Primack, Klypin, and their collaborators are continuing to analyze the results of the Bolshoi simulation and submit papers for publication. Among their findings are results showing that the simulation correctly predicts the number of galaxies as bright as the Milky Way that have satellite galaxies as bright as the Milky Way's major satellites, the Large and Small Magellanic Clouds.

"A lot more papers are on the way," Primack said.

]]> Wed, 08 FEB 2012 08:47:35 AEST Oak Ridge, Tenn. (UPI) Mar 23, 2011 - A supercomputer commissioned by the U.S. Department of Energy means the United States will again be home to the fastest computer in the world, researchers say.

The computer, dubbed "Titan," is predicted to achieve a computation speed 20,000 trillion calculations (20 petaflops) per second, PhysOrg.com reported Wednesday.

If successful, it will surpass China's Tianhe-1A, unveiled last October by the country's National University of Defense and boasting a speed of 2.5 petaflops.

The Titan, to be built by Cray Computer, will become part of a collection of some of the fastest computers in the world at the Oak Ridge National Laboratory facility in Tennessee, joining the National Oceanographic and Atmospheric Administration's Gaea, the National Science Foundation's Kraken and the Department of Energy's current workhorse, the Jaguar.

The Titan is expected to be used by the Energy Department to calculate complex energy systems and will cost the U.S. government approximately $100 million.

The first stage of the Titan computing array is expected to be delivered by the end of this year with the second stage scheduled for sometime next year.

]]> Wed, 08 FEB 2012 08:47:35 AEST London (UPI) Jan 13, 2011 - A replica of the world's first modern computer, first run more than 60 years ago, will be built at a former U.K. code-breaking center, engineers say.

The Electronic Delay Storage Automatic Calculator was a room-sized giant built at Cambridge University that first ran in 1949.

Creation of the replica of EDSAC at Bletchley Park, has been commissioned by the United Kingdom's Computer Conservation Society, the BBC reported Thursday.

Visitors to The National Museum of Computing at Bletchley will get to watch the computer take shape over the next three years.

EDSAC was conceived and created by Sir Maurice Wilkes to carry out many different kinds of calculations for Cambridge researchers and scientists.

"EDSAC was the first to go into regular service to help the people Sir Maurice saw in Cambridge, researchers struggling with computation using desk calculators," said David Hartley, the society's chairman.

During its nine-year lifespan, EDSAC helped two Cambridge researchers win a Nobel Prize and pioneered may computer uses.

Preliminary work on the project will involve scouring archives and talking to surviving EDSAC engineers to get a better idea of how the machine worked, Hartley said.

]]> Wed, 08 FEB 2012 08:47:35 AEST Cleveland (UPI) Nov 30, 2010 - The U.S. Air Force used 1,760 Sony Playstation 3 video game consoles to create a supercomputer at about a tenth the normal cost for such a setup, officials say.

Named the Condor Cluster and to be unveiled Wednesday, it's the fastest interactive computer the Defense Department has, the Air Force said.

Researchers under the command of Wright Patterson Air Force Base near Dayton, Ohio, harnessed the computing power of off-the-shelf PlayStation 3 consoles linked to more traditional graphical processing computer components, The (Cleveland) Plain Dealer reported.

The Condor Cluster can be used to solve image-matching problems and assist in surveillance situations, using radar enhancement and pattern recognition capabilities, the Air Force said.

The total cost of $2 million is about 10 to 20 times cheaper than what a tradition supercomputer system would cost, Air Force officials said.

Harnessing video gaming technology for super computing may seem unusual but "unusual is a relative term," said Larry Merkle, assistant chairman of the Department of Computer Science and Engineering at Wright State University.

Video game consoles were developed with cutting-edge graphics capabilities and the ability to handle extensive numerical computations, he said.

]]> Wed, 08 FEB 2012 08:47:35 AEST Berkeley CA (SPX) Nov 24, 2010 - The Department of Energy's National Energy Research Scientific Computing Center (NERSC), already one of the world's leading centers for scientific productivity, is now home to the fifth most powerful supercomputer in the world and the second most powerful in the United States, according to the latest edition of the TOP500 list, the definitive ranking of the world's top computers.

NERSC's newest supercomputer, a 153,408 processor-core Cray XE6 system, posted a performance of 1.05 petaflops (quadrillions of calculations per second) running the Linpack benchmark.

In keeping with NERSC's tradition of naming computers for renowned scientists, the system is named Hopper in honor of Admiral Grace Hopper, a pioneer in software development and programming languages. The system, installed d in September 2010, is funded by DOE's Office of Advanced Scientific Computing Research.

Established in 1974, NERSC is located at Lawrence Berkeley National Laboratory in California and provides computing systems and services to more than 3,000 researchers supported by the Department of Energy (DOE).

NERSC's users, located at universities, national laboratories, and other research institutions around the country, report producing more than 1,500 scientific publications each year as a result of calculations run at NERSC.

"While we are elated to have entered the petascale performance arena, we are especially excited by the computational science potential offered by Hopper," said Kathy Yelick, Director of the NERSC Division and Associate Laboratory Director of Computing Sciences at Berkeley Lab.

"We selected Cray as the system vendor after a competitive procurement based in large part on how proposed systems performed running our application benchmarks.

"Now that the system is installed and operational, we will begin our acceptance testing in which we run some of the most demanding scientific applications to ensure that Hopper will meet the day-to-day demands of our users."

NERSC serves one of the largest research communities of all supercomputing centers in the United States.

The center's supercomputers are used to tackle a wide range of scientific challenges, including global climate change, combustion, clean energy, new materials, astrophysics, genomics, particle physics and chemistry. The more than 400 projects being addressed by NERSC users represent the research mission areas of DOE's Office of Science.

The increasing power of supercomputers helps scientists study problems in greater detail and with greater accuracy, such as increasing the resolution of climate models and creating models of new materials with thousands of atoms.

Supercomputers are increasingly used to compliment scientific experimentation by allowing researchers to test theories using computational models and analyzed large scientific data sets. NERSC is also home to Franklin, a 38,128 core Cray XT4 supercomputer with a Linpack performance of 266 teraflops (trillions of calculations per second). Franklin is ranked number 27 on the newest TOP500 list.

]]> Wed, 08 FEB 2012 08:47:35 AEST Warwick, UK (SPX) Nov 16, 2010 - New research from the University of Warwick, to be presented at the World's largest supercomputing conference next week, pits China's new No. 1 supercomputer against alternative US designs. The work provides crucial new analysis that will benefit the battle plans of both sides, in an escalating war between two competing technologies.

Professor Stephen Jarvis, Royal Society Industry Fellow at the University of Warwick's Department of Computer Science, will tell some of the 15,000 delegates in New Orleans next week, how general-purpose GPU (GPGPU) designs used in China's 2.5 Petaflops Tianhe-1A fare against alternative supercomputing designs employed in the US; these use relatively simpler processing cores brought together in parallel by highly-effective and scalable interconnects, as seen in the IBM BlueGene architectures.

Professor Jarvis says that: "The 'Should I buy GPGPUs or BlueGene' debate ticks all the boxes for a good fight. No one is quite sure of the design that is going to get us to Exascale computing, the next milestone in 21st-century computing, one quintillion floating-point operations per second (10^18).

"It's not simply an architectural decision either - you could run a small town on the power required to run one of these supercomputers and even if you plump for a design and power the thing up, programming it is currently impossible."

Professor Jarvis' research uses mathematical models, benchmarking and simulation to determine the likely performance of these future computing designs at scale:

"At Supercomputing in New Orleans we directly compare GPGPU designs with that of the BlueGene. If you are investing billions of Dollars or Yuan in supercomputing programmes, then it is worth standing back and calculating what designs might realistically get you to Exascale, and once you have that design, mitigating for the known risks - power, resilience and programmability."

Professor Jarvis' paper uses mathematical modeling to highlight some of the biggest challenges in the supercomputing war. The first of these is a massive programming/engineering gap, where even the best computer programmers are struggling to use even a small fraction of the computing power that the latest supercomputing designs have and, which will continue to be a problem without significant innovation. Professor Jarvis says:

"If your application fits, then GPGPU solutions will outgun BlueGene designs on peak performance" - but he also illustrates potential pitfalls in this approach - "the Tianhe-1A has a theoretical peak performance of 4.7 Petaflops, yet our best programming code-based measures can only deliver 2.5 Petaflops of that peak, that's a lot of unused computer that you are powering. Contrast this with the Dawn BlueGene/P at Lawrence Livermore National Laboratory in the US, it's a small machine at 0.5 Petaflops peak [performance], but it delivers 0.415 Petaflops of that peak. In many ways this is not surprising, as our current programming models are designed around CPUs."

But the story doesn't end there. "The BlueGene design is not without its own problems. In our paper we show that BlueGenes can require many more processing elements than a GPU-based system to do the same work. Many of our scientific algorithms - the recipes for doing the calculations - just do not scale to this degree, so unless we invest in this area we are just going to end up with fantastic machines that we can not use."

Another key problem identified by the University of Warwick research is the fact that in the rush to use excitingly powerful GPGPUs, researchers have not yet put sufficient energy into devising the best technologies to actually link them together in parallel at massive scales.

Professor Jarvis' modeling found that small GPU-based systems solved problems between 3 and 7 times faster than traditional CPU-based designs. However he also found that as you increased the number of processing elements linked together, the performance of the GPU-based systems improved at a much slower rate than the BlueGene-style machines.

Professor Jarvis concludes that: "Given the crossroads at which supercomputing stands, and the national pride at stake in achieving Exascale, this design battle will continue to be hotly contested. It will also need the best modelling techniques that the community can provide to discern good design from bad."

The paper, to be presented on the 15th of November, is entitled 'Performance Analysis of a Hybrid MPI/CUDA Implementation of the NAS-LU Benchmark' and is by S.J. Pennycook, S.D. Hammond, G.R. Mudalige and S.A. Jarvis (all of whom were at the University of Warwick's Department of Computer Science when this work was undertaken). The paper will be presented in the technical track of SC 10, at the Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computing Systems (PMBS 10).

]]> Wed, 08 FEB 2012 08:47:35 AEST Albuquerque NM (SPX) Nov 16, 2010 - A new supercomputer rating system will be released by an international team led by Sandia National Laboratories at the Supercomputing Conference 2010 in New Orleans.

The rating system, Graph500, tests supercomputers for their skill in analyzing large, graph-based structures that link the huge numbers of data points present in biological, social and security problems, among other areas.

"By creating this test, we hope to influence computer makers to build computers with the architecture to deal with these increasingly complex problems," Sandia researcher Richard Murphy said.

Rob Leland, director of Sandia's Computations, Computers, and Math Center, said, "The thoughtful definition of this new competitive standard is both subtle and important, as it may heavily influence computer architecture for decades to come."

The group isn't trying to compete with Linpack, the current standard test of supercomputer speed, Murphy said. "There have been lots of attempts to supplant it, and our philosophy is simply that it doesn't measure performance for the applications we need, so we need another, hopefully complementary, test," he said.

Many scientists view Linpack as a "plain vanilla" test mechanism that tells how fast a computer can perform basic calculations, but has little relationship to the actual problems the machines must solve.

The impetus to achieve a supplemental test code came about at "an exciting dinner conversation at Supercomputing 2009," said Murphy. "A core group of us recruited other professional colleagues, and the effort grew into an international steering committee of over 30 people." (See www.graph500.org.)

Many large computer makers have indicated interest, said Murphy, adding there's been buy-in from Intel, IBM, AMD, NVIDIA, and Oracle corporations. "Whether or not they submit test results remains to be seen, but their representatives are on our steering committee."

Each organization has donated time and expertise of committee members, he said.

While some computer makers and their architects may prefer to ignore a new test for fear their machine will not do well, the hope is that large-scale demand for a more complex test will be a natural outgrowth of the greater complexity of problems.

Studies show that moving data around (not simple computations) will be the dominant energy problem on exascale machines, the next frontier in supercomputing, and the subject of a nascent U.S. Department of Energy initiative to achieve this next level of operations within a decade, Leland said. (Petascale and exascale represent 10 to the 15th and 18th powers, respectively, operations per second.)

Part of the goal of the Graph500 list is to point out that in addition to more expense in data movement, any shift in application base from physics to large-scale data problems is likely to further increase the application requirements for data movement, because memory and computational capability increase proportionally. That is, an exascale computer requires an exascale memory.

"In short, we're going to have to rethink how we build computers to solve these problems, and the Graph500 is meant as an early stake in the ground for these application requirements," said Murphy.

How does it work?

Large data problems are very different from ordinary physics problems.

Unlike a typical computation-oriented application, large-data analysis often involves searching large, sparse data sets performing very simple computational operations.

To deal with this, the Graph 500 benchmark creates two computational kernels: a large graph that inscribes and links huge numbers of participants and a parallel search of that graph.

"We want to look at the results of ensembles of simulations, or the outputs of big simulations in an automated fashion," Murphy said. "The Graph500 is a methodology for doing just that. You can think of them being complementary in that way - graph problems can be used to figure out what the simulation actually told us."

Performance for these applications is dominated by the ability of the machine to sustain a large number of small, nearly random remote data accesses across its memory system and interconnects, as well as the parallelism available in the machine.

Five problems for these computational kernels could be cybersecurity, medical informatics, data enrichment, social networks and symbolic networks:

+ Cybersecurity: Large enterprises may create 15 billion log entries per day and require a full scan.

+ Medical informatics: There are an estimated 50 million patient records, with 20 to 200 records per patient, resulting in billions of individual pieces of information, all of which need entity resolution: in other words, which records belong to her, him or somebody else.

+ Data enrichment: Petascale data sets include maritime domain awareness with hundreds of millions of individual transponders, tens of thousands of ships, and tens of millions of pieces of individual bulk cargo. These problems also have different types of input data.

+ Social networks: Almost unbounded, like Facebook.

+ Symbolic networks: Often petabytes in size. One example is the human cortex, with 25 billion neurons and approximately 7,000 connections each.

"Many of us on the steering committee believe that these kinds of problems have the potential to eclipse traditional physics-based HPC [high performance computing] over the next decade," Murphy said.

While general agreement exists that complex simulations work well for the physical sciences, where lab work and simulations play off each other, there is some doubt they can solve social problems that have essentially infinite numbers of components. These include terrorism, war, epidemics and societal problems.

"These are exactly the areas that concern me," Murphy said. "There's been good graph-based analysis of pandemic flu. Facebook shows tremendous social science implications. Economic modeling this way shows promise.

"We're all engineers and we don't want to over-hype or over-promise, but there's real excitement about these kinds of big data problems right now," he said. "We see them as an integral part of science, and the community as a whole is slowly embracing that concept.

"However, it's so new we don't want to sound as if we're hyping the cure to all scientific ills. We're asking, 'What could a computer provide us?' and we know we're ignoring the human factors in problems that may stump the fastest computer. That'll have to be worked out."

]]> Wed, 08 FEB 2012 08:47:35 AEST Beijing (AFP) Nov 15, 2010 - China overtook the United States at the head of the world of supercomputing on Sunday when a survey ranked one of its machines the fastest on the planet.

Tianhe-1, meaning Milky Way, achieved a computing speed of 2,570 trillion calculations per second, earning it the number one spot in the Top 500 (www.top500.org) survey of supercomputers.

The Jaguar computer at a US government facility in Tennessee, which had held the top spot, was ranked second with a speed of 1,750 trillion calculations per second.

Tianhe-1 does its warp-speed "thinking" at the National Centre for Supercomputing in the northern port city of Tianjin -- using mostly chips designed by US companies.

Another Chinese system, the Nebulae machine at the National Supercomputing Centre in the southern city of Shenzhen, came in third.

The United States still dominates, with more than half of the entries in the Top 500 list, but China now boasts 42 systems in the rankings, putting it ahead of Japan, France, Germany and Britain.

It is not the first time that the United States has had its digital crown stolen by an Asian upstart. In 2002, Japan made a machine with more power than the top 20 American computers put together.

The supercomputers on the Top 500 list, which is produced twice a year, are rated based on speed of performance in a benchmark test by experts from Germany and the United States.

]]> Wed, 08 FEB 2012 08:47:35 AEST Baltimore MD (SPX) Nov 03, 2010 - Imagine a tool that is a cross between a powerful electron microscope and the Hubble Space Telescope, allowing scientists from disciplines ranging from medicine and genetics to astrophysics, environmental science, oceanography and bioinformatics to examine and analyze enormous amounts of data from both "little picture" and "big picture" perspectives.

Using a $2.1 million grant from the National Science Foundation, a group led by computer scientist and astrophysicist Alexander Szalay of Johns Hopkins' Institute for Data Intensive Engineering and Science is designing and developing such a tool, dubbed the Data-Scope.

Once built, the Data-Scope, which is actually a cluster of sophisticated computers capable of handling colossal sets of information, will enable the kind of data analysis tasks that simply are not otherwise possible today, according to Szalay, the Alumni Centennial Professor in the Krieger School's Henry A. Rowland Department of Physics and Astronomy.

"Computer science has drastically changed the way we do science and the science that we do, and the Data-Scope is a crucial step in this process," Szalay said. "At this moment, the huge data sets are here, but we lack an integrated software and hardware infrastructure to analyze them. Data-Scope will bridge that gap."

Data-Scope will be able to handle five petabytes of data. That's the equivalent of 100 million four-drawer file cabinets filled with text. (Fifty petabytes would equal the entire written work of humankind, from the beginning of history until now, in all languages.)

The new apparatus will allow Szalay and a host of other Johns Hopkins researchers (not to mention those at other institutions, including universities and national laboratories such as Los Alamos in New Mexico and Oak Ridge in Tennessee) to conduct research directly in the database, which is where Szalay contends that more and more science is being done.

"The Data-Scope will allow us to mine out relationships among data that already exist but that we can't yet handle and to sift discoveries from what seems like an overwhelming flow of information," he said. "New discoveries will definitely emerge this way. There are relationships and patterns that we just cannot fathom buried in that onslaught of data. Data-Scope will tease these out."

According to Szalay, there are at least 20 research groups within Johns Hopkins that are grappling with data problems totaling three petabytes. (Three petabytes is equal to about 20 billion photos on Facebook.) Without Data-Scope, "they would have to wait years in order to analyze that amount of data," Szalay said.

The two-year NSF grant, to be supplemented with almost $1 million from Johns Hopkins, will underwrite the design and building of the new instrument and its first year of operation, expected to begin in May 2011. Szalay said that the range of material that the Data-Scope will handle will be "breathtakingly large, from genomics to ocean circulation, turbulence, astrophysics, environmental science, public health and beyond."

"There really is nothing like this at any university right now," Szalay said. "Such systems usually take many years to build up, but we are doing it much more quickly. It's similar to what Google is doing-of course on a thousand-times-larger scale than we are. This instrument will be the best in the academic world, bar none."

Zeger said he is excited about the research possibilities and collaborations that the new instrument will make possible.

"The NSF funding of a high-performance computing system, specially designed by Dr. Szalay and his team to solve large computational problems, will contribute to Johns Hopkins' remaining in the forefront of many areas, including biomedicine, where I work," he said.

"The new genomic data are voluminous. Their analysis requires machines faster than are currently available. Dr. Szalay's machine will enable our biomedical and computational scientists to work together to solve problems that would have been beyond them otherwise."

Jonathan Bagger, vice provost for graduate and postdoctoral programs and special projects, said he believes that the Data-Scope positions Johns Hopkins to play a crucial role in the next revolution in science: data analysis.

"The Data-Scope is specially designed to bring large amounts of data literally under the microscope," he said.

"By manipulating data in new ways, Johns Hopkins researchers will be able to advance their science in ways never before possible. I am excited that Johns Hopkins is in the forefront of this new field of inquiry: developing the calculus of the 21st century."

The instrument will be part of a new energy-efficient computing center that is being constructed in the basement of the Bloomberg Center for Physics and Astronomy on the Homewood campus. The house-sized room once served as a mission control center for the Far Ultraviolet Spectroscopic Explorer, a NASA satellite. This computing center is being built using a $1.3 million federal stimulus grant from the National Science Foundation.

Co-investigators on the Data-Scope project, all from Johns Hopkins, are Kenneth Church, chief scientist for the Human Language Technology Center of Excellence, a Department of Defense-funded center dedicated to advancing technology for the analysis of speech, text and document data; Andreas Terzis, associate professor in the Department of Computer Science at the Whiting School of Engineering; Sarah Wheelan, assistant professor of oncology bioinformatics in the School of Medicine; and Scott Zeger, professor of biostatistics in the Bloomberg School of Public Health and the university's vice provost for research.

]]> Wed, 08 FEB 2012 08:47:35 AEST Subscribe to our daily selection of space, military, environment and energy newsletters responseText http://visitor.constantcontact.com/manage/optin/ea?v=0016gbbKsaiGSpQFojVO8ZoHw%3D%3D