Sunspots Revealed In Striking Detail By Supercomputers

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ScienceDaily (June 18, 2009) — In a breakthrough that will help scientists unlock mysteries of the Sun and its impacts on Earth, an international team of scientists led by the National Center for Atmospheric Research (NCAR) has created the first-ever comprehensive computer model of sunspots. The resulting visuals capture both scientific detail and remarkable beauty.

The high-resolution simulations of sunspot pairs open the way for researchers to learn more about the vast mysterious dark patches on the Sun's surface. Sunspots are associated with massive ejections of charged plasma that can cause geomagnetic storms and disrupt communications and navigational systems. They also contribute to variations in overall solar output, which can affect weather on Earth and exert a subtle influence on climate patterns.
The research, by scientists at NCAR and the Max Planck Institute for Solar System Research (MPS) in Germany, is being published June 18 in Science Express.
"This is the first time we have a model of an entire sunspot," says lead author Matthias Rempel, a scientist at NCAR's High Altitude Observatory. "If you want to understand all the drivers of Earth's atmospheric system, you have to understand how sunspots emerge and evolve. Our simulations will advance research into the inner workings of the Sun as well as connections between solar output and Earth's atmosphere."
Ever since outward flows from the center of sunspots were discovered 100 years ago, scientists have worked toward explaining the complex structure of sunspots, whose number peaks and wanes during the 11-year solar cycle. Sunspots encompass intense magnetic activity that is associated with solar flares and massive ejections of plasma that can buffet Earth's atmosphere. The resulting damage to power grids, satellites, and other sensitive technological systems takes an economic toll on a rising number of industries.
Creating such detailed simulations would not have been possible even as recently as a few years ago, before the latest generation of supercomputers and a growing array of instruments to observe the Sun. The model enables scientists to capture the convective flow and movement of energy that underlie the sunspots, which is not directly detectable by instruments.
The work was supported by the National Science Foundation, NCAR's sponsor. The research team improved a computer model, developed at MPS, that built upon numerical codes for magnetized fluids that had been created at the University of Chicago.
Computer model provides a unified physical explanation
The new simulations capture pairs of sunspots with opposite polarity. In striking detail, they reveal the dark central region, or umbra, with brighter umbral dots, as well as webs of elongated narrow filaments with flows of mass streaming away from the spots in the outer penumbral regions.
The model suggests that the magnetic fields within sunspots need to be inclined in certain directions in order to create such complex structures. The authors conclude that there is a unified physical explanation for the structure of sunspots in umbra and penumbra that is the consequence of convection in a magnetic field with varying properties.
The simulations can help scientists decipher the mysterious, subsurface forces in the Sun that cause sunspots. Such work may lead to an improved understanding of variations in solar output and their impacts on Earth.
Supercomputing at 76 trillion calculations per second
To create the model, the research team designed a virtual, three-dimensional domain that simulates an area on the Sun measuring about 31,000 miles by 62,000 miles and about 3,700 miles in depth - an expanse as long as eight times Earth's diameter and as deep as Earth's radius. The scientists then used a series of equations involving fundamental physical laws of energy transfer, fluid dynamics, magnetic induction and feedback, and other phenomena to simulate sunspot dynamics at 1.8 billion points within the virtual expanse, each spaced about 10 to 20 miles apart. For weeks, they solved the equations on NCAR's new bluefire supercomputer, an IBM machine that can perform 76 trillion calculations per second.
The work drew on increasingly detailed observations from a network of ground- and space-based instruments to verify that the model captured sunspots realistically.
The new model is far more detailed and realistic than previous simulations that failed to capture the complexities of the outer penumbral region. The researchers noted, however, that even their new model does not accurately capture the lengths of the filaments in parts of the penumbra. They can refine the model by placing the grid points even closer together, but that would require more computing power than is currently available.
"Advances in supercomputing power are enabling us to close in on some of the most fundamental processes of the Sun," says Michael Knoelker, director of NCAR's High Altitude Observatory and a co-author of the paper. "With this breakthrough simulation, an overall comprehensive physical picture is emerging for everything that observers have associated with the appearance, formation, dynamics, and the decay of sunspots on the Sun's surface."
The University Corporation for Atmospheric Research manages the National Center for Atmospheric Research under sponsorship by the National Science Foundation.
Adapted from materials provided by National Center for Atmospheric Research/University Corporation for Atmospheric Research.

Human Eye Inspires Advance In Computer Vision From Boston College Researchers

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ScienceDaily (June 18, 2009) — Inspired by the behavior of the human eye, Boston College computer scientists have developed a technique that lets computers see objects as fleeting as a butterfly or tropical fish with nearly double the accuracy and 10 times the speed of earlier methods.

The linear solution to one of the most vexing challenges to advancing computer vision has direct applications in the fields of action and object recognition, surveillance, wide-base stereo microscopy and three-dimensional shape reconstruction, according to the researchers, who will report on their advance at the upcoming annual IEEE meeting on computer vision.
BC computer scientists Hao Jiang and Stella X. Yu developed a novel solution of linear algorithms to streamline the computer's work. Previously, computer visualization relied on software that captured the live image then hunted through millions of possible object configurations to find a match. Further compounding the challenge, even more images needed to be searched as objects moved, altering scale and orientation.
Rather than combing through the image bank – a time- and memory-consuming computing task – Jiang and Yu turned to the mechanics of the human eye to give computers better vision.
"When the human eye searches for an object it looks globally for the rough location, size and orientation of the object. Then it zeros in on the details," said Jiang, an assistant professor of computer science. "Our method behaves in a similar fashion, using a linear approximation to explore the search space globally and quickly; then it works to identify the moving object by frequently updating trust search regions."
Trust search regions act as visual touchstones the computer returns to again and again. Jiang and Yu's solution focuses on the mathematically-generated template of an image, which looks like a constellation when lines are drawn to connect the stars. Using the researchers' new algorithms, computer software identifies an object using the template of a trust search region. The program then adjusts the trust search regions as the object moves and finds its mathematical matches, relaying that shifting image to a memory bank or a computer screen to record or display the object.
Jiang says using linear approximation in a sequence of trust regions enables the new program to maintain spatial consistency as an object moves and reduces the number of variables that need to be optimized from several million to just a few hundred. That increased the speed of image matching 10 times over compared with previous methods, he said.
The researchers tested the software on a variety of images and videos – from a butterfly to a stuffed Teddy Bear – and report achieving a 95 percent detection rate at a fraction of the complexity. Previous so-called "greedy" methods of search and match achieved a detection rate of approximately 50 percent, Jiang said.
Jiang will present the team's findings at the IEEE Conference on Computer Vision and Pattern Recognition 2009, which takes place June 20-25 in Miami.
Adapted from materials provided by Boston College, via EurekAlert!, a service of AAAS.

Hybrid System Of Human-Machine Interaction Created

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ScienceDaily (June 17, 2009) — Scientists at FAU have created a "hybrid" system to examine real-time interactions between humans and machines (virtual partners). By pitting human against machine, they open up the possibility of exploring and understanding a wide variety of interactions between minds and machines, and establishing the first step toward a much friendlier union of man and machine, and perhaps even creating a different kind of machine altogether.

For more than 25 years, scientists in the Center for Complex Systems and Brain Sciences (CCSBS) in Florida Atlantic University’s Charles E. Schmidt College of Science, and others around the world, have been trying to decipher the laws of coordinated behavior called “coordination dynamics”.
Unlike the laws of motion of physical bodies, the equations of coordination dynamics describe how the coordination states of a system evolve over time, as observed through special quantities called collective variables. These collective variables typically span the interaction of organism and environment. Imagine a machine whose behavior is based on the very equations that are supposed to govern human coordination. Then imagine a human interacting with such a machine whereby the human can modify the behavior of the machine and the machine can modify the behavior of the human.
In a groundbreaking study published in the June 3 issue of PLoS One and titled “Virtual Partner Interaction (VPI): exploring novel behaviors via coordination dynamics,” an interdisciplinary group of scientists in the CCSBS created VPI, a hybrid system of a human interacting with a machine. These scientists placed the equations of human coordination dynamics into the machine and studied real-time interactions between the human and virtual partners. Their findings open up the possibility of exploring and understanding a wide variety of interactions between minds and machines. VPI may be the first step toward establishing a much friendlier union of man and machine, and perhaps even creating a different kind of machine altogether.
“With VPI, a human and a ‘virtual partner’ are reciprocally coupled in real-time,” said Dr. J. A. Scott Kelso, the Glenwood and Martha Creech Eminent Scholar in Science at FAU and the lead author of the study. “The human acquires information about his partner’s behavior through perception, and the virtual partner continuously detects the human’s behavior through the input of sensors. Our approach is analogous to the dynamic clamp used to study the dynamics of interactions between neurons, but now scaled up to the level of behaving humans.”
In this first ever study of VPI, machine and human behaviors were chosen to be quite simple. Both partners were tasked to coordinate finger movements with one another. The human executed the task with the intention of performing in-phase coordination with the machine, thereby trying to synchronize his/her flexion and extension movements with those of the virtual partner’s.
The machine, on the other hand, executed the task with the competing goal of performing anti-phase coordination with the human, thereby trying to extend its finger when the human flexed and vice versa. Pitting machine against human through opposing task demands was a way the scientists chose to enhance the formation of emergent behavior, and also allowed them to examine each partner’s individual contribution to the coupled behavior. An intriguing outcome of the experiments was that human subjects ascribed intentions to the machine, reporting that it was “messing” with them.
“The symmetry between the human and the machine, and the fact that they carry the same laws of coordination dynamics, is a key to this novel scientific framework,” said co-author Dr. Gonzalo de Guzman, a physicist and research associate professor at the FAU center. “The design of the virtual partner mirrors the equations of motion of the human neurobehavioral system. The laws obtained from accumulated studies describe how the parts of the human body and brain self-organize, and address the issue of self-reference, a condition leading to complexity.”
One ready application of VPI is the study of the dynamics of complex brain processes such as those involved in social behavior. The extended parameter range opens up the possibility of systematically driving functional process of the brain (neuromarkers) to better understand their roles. The scientists in this study anticipate that just as many human skills are acquired by observing other human beings; human and machine will learn novel patterns of behavior by interacting with each other.
“Interactions with ever proliferating technological devices often place high skill demands on users who have little time to develop these skills,” said Kelso. “The opportunity presented through VPI is that equally useful and informative new behaviors may be uncovered despite the built-in asymmetry of the human-machine interaction.”
While stable and intermittent coordination behaviors emerged that had previously been observed in ordinary human social interactions, the scientists also discovered novel behaviors or strategies that have never previously been observed in human social behavior. The emergence of such novel behaviors demonstrates the scientific potential of the VPI human-machine framework.
Modifying the dynamics of the virtual partner with the purpose of inducing a desired human behavior, such as learning a new skill or as a tool for therapy and rehabilitation, are among several applications of VPI.
“The integration of complexity in to the behavioral and neural sciences has just begun,” said Dr. Emmanuelle Tognoli, research assistant professor in FAU’s CCSBS and co-author of the study. “VPI is a move away from simple protocols in which systems are ‘poked’ by virtue of ‘stimuli’ to understanding more complex, reciprocally connected systems where meaningful interactions occur.”
Research for this study was supported by the National Science Foundation program “Human and Social Dynamics,” the National Institute of Mental Health’s “Innovations Award,” “Basic and Translational Research Opportunities in the Social Neuroscience of Mental Health,” and the Office of Naval Research Code 30. Kelso’s research is also supported by the Pierre de Fermat Chaire d’Excellence and Tognoli’s research is supported by the Davimos Family Endowment for Excellence in Science.
Adapted from materials provided by Florida Atlantic University, via Newswise.

Computer Graphics Researchers Simulate The Sounds Of Water And Other Liquids

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ScienceDaily (June 4, 2009) — Splash, splatter, babble, sploosh, drip, drop, bloop and ploop!

Those are some of the sounds that have been missing from computer graphic simulations of water and other fluids, according to researchers in Cornell's Department of Computer Science, who have come up with new algorithms to simulate such sounds to go with the images.
The work by Doug James, associate professor of computer science, and graduate student Changxi Zheng will be reported at the 2009 ACM SIGGRAPH conference Aug. 3-7 in New Orleans. It is the first step in a broader research program on sound synthesis supported by a $1.2 million grant from the Human Centered Computing Program of the National Science Foundation (NSF) to James, assistant professor Kavita Bala and associate professor Steve Marschner.
In computer-animated movies, sound can be added after the fact from recordings or by Foley artists. But as virtual worlds grow increasingly interactive and immersive, the researchers point out, sounds will need to be generated automatically to fit events that can't be predicted in advance. Recordings can be cued in, but can be repetitive and not always well matched to what's happening.
"We have no way to efficiently compute the sounds of water splashing, paper crumpling, hands clapping, wind in trees or a wine glass dropped onto the floor," the researchers said in their research proposal.
Along with fluid sounds, the research also will simulate sounds made by objects in contact, like a bin of Legos; the noisy vibrations of thin shells, like trash cans or cymbals; and the sounds of brittle fracture, like breaking glass and the clattering of the resulting debris.
All the simulations will be based on the physics of the objects being simulated in computer graphics, calculating how those objects would vibrate if they actually existed, and how those vibrations would produce acoustic waves in the air. Physics-based simulations also can be used in design, just as visual simulation is now, James said. "You can tell what it's going to sound like before you build it," he explained, noting that a lot of effort often goes into making things quieter.
In their SIGGRAPH paper, Zheng and James report that most of the sounds of water are created by tiny air bubbles that form as water pours and splashes. Moving water traps air bubbles on the scale of a millimeter or so. Surface tension contracts the bubbles, compressing the air inside until it pushes back and expands the bubble. The repeated expansion and contraction over milliseconds generates vibrations in the water that eventually make its surface vibrate, acting like a loudspeaker to create sound waves in the air.
The simulation method developed by the Cornell researchers starts with the geometry of the scene, figures out where the bubbles would be and how they're moving, computes the expected vibrations and finally the sounds they would produce. The simulation is done on a highly parallel computer, with each processor computing the effects of multiple bubbles. The researchers have fine-tuned the results by comparing their simulations with real water sounds.
Demonstration videos of simulations of falling, pouring, splashing and babbling water are available at http://www.cs.cornell.edu/projects/HarmonicFluids.
The current methods still require hours of offline computing time, and work best on compact sound sources, the researchers noted, but they said further development should make possible the real-time performance needed for interactive virtual environments and deal with larger sound sources such as swimming pools or perhaps even Niagara Falls. They also plan to approach the more complex collections of bubbles in foam or plumes.
The research reported in the SIGGRAPH paper was supported in part by an NSF Faculty Early Career Award to James, and by the Alfred P. Sloan Foundation, Pixar, Intel and Autodesk.
Adapted from materials provided by Cornell University. Original article written by Bill Steele.

The Future of The Web:Mozilla Labs Aurora - Concept Browser (Video by Adaptive Path, Internet Browser )

Faster Computers, Electronic Devices Possible After Scientists Create Large-area Graphene On Copper

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ScienceDaily (May 11, 2009) — The creation of large-area graphene using copper may enable the manufacture of new graphene-based devices that meet the scaling requirements of the semiconductor industry, leading to faster computers and electronics, according to a team of scientists and engineers at The University of Texas at Austin.

"Graphene could lead to faster computers that use less power, and to other sorts of devices for communications such as very high-frequency (radio-frequency-millimeter wave) devices," said Professor and physical chemist Rod Ruoff, one of the corresponding authors on the Science article. "Graphene might also find use as optically transparent and electrically conductive films for image display technology and for use in solar photovoltaic electrical power generation."
Graphene, an atom-thick layer of carbon atoms bonded to one another in a "chickenwire" arrangement of hexagons, holds great potential for nanoelectronics, including memory, logic, analog, opto-electronic devices and potentially many others. It also shows promise for electrical energy storage for supercapacitors and batteries, for use in composites, for thermal management, in chemical-biological sensing and as a new sensing material for ultra-sensitive pressure sensors.
"There is a critical need to synthesize graphene on silicon wafers with methods that are compatible with the existing semiconductor industry processes," Ruoff said. "Doing so will enable nanoelectronic circuits to be made with the exceptional efficiencies that the semiconductor industry is well known for."
Graphene can show very high electron- and hole-mobility; as a result, the switching speed of nanoelectronic devices based on graphene can in principle be extremely high. Also, graphene is "flat" when placed on a substrate (or base material) such as a silicon wafer and, thus, is compatible with the wafer-processing approaches of the semiconductor industry. The exceptional mechanical properties of graphene may also enable it to be used as a membrane material in nanoelectromechanical systems, as a sensitive pressure sensor and as a detector for chemical or biological molecules or cells.
The university researchers, including post-doctoral fellow Xuesong Li, and Luigi Colombo, a TI Fellow from Texas Instruments, Inc., grew graphene on copper foils whose area is limited only by the furnace used. They demonstrated for the first time that centimeter-square areas could be covered almost entirely with mono-layer graphene, with a small percentage (less than five percent) of the area being bi-layer or tri-layer flakes. The team then created dual-gated field effect transistors with the top gate electrically isolated from the graphene by a very thin layer of alumina, to determine the carrier mobility. The devices showed that the mobility, a key metric for electronic devices, is significantly higher than that of silicon, the principal semiconductor of most electronic devices, and comparable to natural graphite.
"We used chemical-vapor deposition from a mixture of methane and hydrogen to grow graphene on the copper foils," said Ruoff. "The solubility of carbon in copper being very low, and the ability to achieve large grain size in the polycrystalline copper substrate are appealing factors for its use as a substrate --along with the fact that the semiconductor industry has extensive experience with the use of thin copper films on silicon wafers. By using a variety of characterization methods we were able to conclude that growth on copper shows significant promise as a potential path for high quality graphene on 300-millimeter silicon wafers."
The university's effort was funded in part by the state of Texas, the South West Academy for Nanoelectronics (SWAN) and the DARPA CERA Center. Electrical and computer engineering Professor Sanjay Banerjee, a co-author of the Science paper, directs both SWAN and the DARPA Center.
"By having a materials scientist of Colombo's caliber with such extensive knowledge about all aspects of semiconductor processing and now co-developing the materials science of graphene with us, I think our team exemplifies what collaboration between industrial scientists and engineers with university personnel can be," said Ruoff, who holds the Cockrell Family Regents Chair #7. "This industry-university collaboration supports both the understanding of the fundamental science as well its application."
Other co-authors of the work not previously mentioned include: research associate Richard Piner of the Department of Mechanical Engineering; Assistant Professor Emanuel Tutuc of the Department of Electrical and Computer Engineering; post-doctoral fellows Jinho An, Weiwei Cai, Inhwa Jung, Aruna Velamakanni and Dongxing Yang in the Department of Mechanical Engineering; and graduate students Seyoung Kim and Junghyo Nah in the Department of Electrical and Computer Engineering.
Journal reference:
Li et al. Large-Area Synthesis of High-Quality and Uniform Graphene Films on Copper Foils. Science, 2009; DOI: 10.1126/science.1171245
Adapted from materials provided by University of Texas at Austin, via EurekAlert!, a service of AAAS.

Computers With 'Common Sense'

Source:

http://www.sciencedaily.com/releases/2007/10/071017174328.htm

ScienceDaily (Oct. 18, 2007) — Using a little-known Google Labs widget, computer scientists from UC San Diego and UCLA have brought common sense to an automated image labeling system. This common sense is the ability to use context to help identify objects in photographs.

For example, if a conventional automated object identifier has labeled a person, a tennis racket, a tennis court and a lemon in a photo, the new post-processing context check will re-label the lemon as a tennis ball.
“We think our paper is the first to bring external semantic context to the problem of object recognition,” said computer science professor Serge Belongie from UC San Diego.
The researchers show that the Google Labs tool called Google Sets can be used to provide external contextual information to automated object identifiers.
Google Sets generates lists of related items or objects from just a few examples. If you type in John, Paul and George, it will return the words Ringo, Beatles and John Lennon. If you type “neon” and “argon” it will give you the rest of the noble gasses.
“In some ways, Google Sets is a proxy for common sense. In our paper, we showed that you can use this common sense to provide contextual information that improves the accuracy of automated image labeling systems,” said Belongie.
The image labeling system is a three step process. First, an automated system splits the image up into different regions through the process of image segmentation. In the photo above, image segmentation separates the person, the court, the racket and the yellow sphere.
Next, an automated system provides a ranked list of probable labels for each of these image regions.
Finally, the system adds a dose of context by processing all the different possible combinations of labels within the image and maximizing the contextual agreement among the labeled objects within each picture.
It is during this step that Google Sets can be used as a source of context that helps the system turn a lemon into a tennis ball. In this case, these “semantic context constraints” helped the system disambiguate between visually similar objects.
In another example, the researchers show that an object originally labeled as a cow is (correctly) re-labeled as a boat when the other objects in the image – sky, tree, building and water – are considered during the post-processing context step. In this case, the semantic context constraints helped to correct an entirely wrong image label. The context information came from the co-occurrence of object labels in the training sets rather than from Google Sets.
The computer scientists also highlight other advances they bring to automated object identification. First, instead of doing just one image segmentation, the researchers generated a collection of image segmentations and put together a shortlist of stable image segmentations. This increases the accuracy of the segmentation process and provides an implicit shape description for each of the image regions.
Second, the researchers ran their object categorization model on each of the segmentations, rather than on individual pixels. This dramatically reduced the computational demands on the object categorization model.
In the two sets of images that the researchers tested, the categorization results improved considerably with inclusion of context. For one image dataset, the average categorization accuracy increased more than 10 percent using the semantic context provided by Google Sets. In a second dataset, the average categorization accuracy improved by about 2 percent using the semantic context provided by Google Sets. The improvements were higher when the researchers gleaned context information from data on co-occurrence of object labels in the training data set for the object identifier.
Right now, the researchers are exploring ways to extend context beyond the presence of objects in the same image. For example, they want to make explicit use of absolute and relative geometric relationships between objects in an image – such as “above” or “inside” relationships. This would mean that if a person were sitting on top of an animal, the system would consider the animal to be more likely a horse than a dog.
Reference: “Objects in Context,” by Andrew Rabinovich, Carolina Galleguillos, Eric Wiewiora and Serge Belongie from the Department of Computer Science and Engineering at the UCSD Jacobs School of Engineering. Andrea Vedaldi from the Department of Computer Science, UCLA.
The paper will be presented on Thursday 18 October 2007 at ICCV 2007 – the 11th IEEE International Conference on Computer Vision in Rio de Janeiro, Brazil.
Funders: National Science Foundation, Afred P. Sloan Research Fellowship, Air Force Office of Scientific Research, Office of Naval Research.
Adapted from materials provided by University of California - San Diego.

Fausto Intilla

www.oloscience.com

I.B.M. Researchers Advancing Computer Processing Ability

Source: http://www.nytimes.com/2007/08/31/technology/31ibm.html?ref=science

By JOHN MARKOFF
Published: August 31, 2007

SAN FRANCISCO, Aug. 30 — Researchers at I.B.M. laboratories say they have made progress toward storing information and computing at the level of individual atoms.
The scientists documented their work in two papers appearing on Friday in the journal Science. Both papers are focused on new understanding of the behavior of magnetism at the tiny scale of nanotechnology, where scientists hope to develop electronics made from components that are far smaller than today’s transistors and wires.
In one paper the researchers describe a technique for reading and writing digital ones and zeroes onto a handful of atoms, or even individual atoms. The second paper describes the ability to use a single molecule as a switch, replicating the behavior of today’s transistors.
The papers are the latest indication that computing technology is beginning to emerge that could replace today’s microelectronics materials in the next decade.
R. Stanley Williams, a Hewlett-Packard physicist, said this week that his group had begun manufacturing prototypes of a silicon chip that combines both conventional microelectronics and molecular scale components. Their first hybrid device is a circuit called a field programmable gate array, or F.P.G.A., using molecular-scale components as the configuration circuitry, an approach that will save tremendous space in the chip design.
A team of I.B.M. researchers at the company’s Almaden Research Center in San Jose, Calif., were able to use a scanning tunneling microscope to observe the magnetic orientation of iron and manganese atoms at low temperatures. Controlling magnetic direction is a crucial technique that is used in reading and writing digital information on magnetic storage disks like standard hard drives.
In addition to the potential storage applications, the researchers noted that atomic-scale magnetic structures are also of scientific interest because they may be harnessed for quantum computing, a technology that would be far faster than current computers for some specialized uses.
A second group of I.B.M. scientists in Zurich were able to place two hydrogen atoms in an ultrathin insulating film and switch them back and forth between two states, creating the equivalent of the ones and zeroes used in standard chips. They were also able to use the same switching process to inject an electric charge into one molecule and link the effect to a neighboring molecule. That suggests it might be possible to extend the effect into a fabric of trillions of atom-size switches in the future.
The laboratory advances are far from being ready to commercialize, but they provide hope for the electronics industry, which has grown steadily because of the continuous shrinking in size and falling cost of components for more than four decades.

Fausto Intilla

www.oloscience.com

World's Highest-resolution Computer Display Reaches 220 Million Pixels In Resolution

Source:

http://www.sciencedaily.com/releases/2007/08/070823122253.htm

Science Daily — Engineers at the University of California, San Diego have constructed the highest-resolution computer display in the world – with a screen resolution up to 220 million pixels.

The system located at the UCSD division of the California Institute for Telecommunications and Information Technology (Calit2) is also linked via optical fiber to Calit2’s building at UC Irvine, which boasts the previous record holder. The combination – known as the Highly Interactive Parallelized Display Space (HIPerSpace) – can deliver real-time rendered graphics simultaneously across 420 million pixels to audiences in Irvine and San Diego.
“We don’t intend to stop there,” said Falko Kuester, Calit2 professor for visualization and virtual reality and associate professor of structural engineering in UCSD’s Jacobs School of Engineering. “HIPerSpace provides a unique environment for visual analytics and cyberinfrastructure research and we are now seeking funding to double the size of the system at UC San Diego alone to reach half a billion pixels with a one gigapixel distributed display in sight.”
Kuester is the chief architect of the systems deployed in both Calit2 buildings. Until last week, UC Irvine’s Highly Interactive Parallelized Display Wall (HIPerWall) – built in 2005 with funding from the National Science Foundation (NSF) – held the record of 200 million pixels for a tiled display system. It is located in the Calit2 Center of Graphics, Visualization and Imaging Technology (GRAVITY), which Kuester directs. When Kuester’s group moved to UCSD in 2006 they began work on the next generation of massively tiled display walls, which now serve as a prototype for ultra-high resolution OptIPortal tiled displays developed by the NSF-funded OptIPuter project (led by Calit2 director Larry Smarr).
The new HIPerSpace system between Irvine and San Diego is joined together via high-performance, dedicated optical networking that clocks in at up to two gigabits per second (2Gbps). The systems use the same type of graphics rendering technology, from industry partner NVIDIA. The “graphics super cluster” being developed at UCSD consists of 80 NVIDIA Quadro FX 5600 graphics processing units (GPUs). “The graphics and computational performance of these cards is quite astounding,” said Kuester. “Putting the theoretical computational performance of the cluster at almost 40 teraflops. To put that into context, the top-rated supercomputer in the world five years ago was operating at that same speed. While these are purely theoretical numbers, the comparison clearly hints at capabilities of this new cluster that go far beyond generating impressive visual information.”
The processing power will come in handy for the kinds of large-scale applications that are likely to make use of the HIPerSpace system. Calit2 will make the displays available to teams of scientists or engineers dealing with very large data sets, from multiple gigabytes to terabytes, notably in the Earth sciences, climate prediction, biomedical engineering, genomics, and brain imaging. “The higher-resolution displays allow researchers to take in both the broad view of the data and the minutest details, all at the same time,” said Kuester. “HIPerSpace also allows us to experiment on the two campuses with distributed teams that can collaborate and share insights derived from a better understanding of complex results. This capability will allow researchers at two UC campuses to collaborate more intensively with each other, and eventually with other campuses, thanks to the rapid rollout of OptIPortals outside of California.”
In San Diego, the OptIPortal is deployed on the second floor of Atkinson Hall, next to the offices of the NEES Cyberinfrastructure Center (NEESit), which supports the NSF-funded George E. Brown, Jr. Network for Earthquake Engineering Simulation (NEES) and its 15 sites around the country. “Structural engineering simulations require a massive amount of data processing and visualization, especially if you need to crunch data coming in from all of the NEES participating sites,” said Kuester. “We are also using the system for a large-scale, global seismicity visualization using data collected over the past thirty years.”
“I am excited that UC Irvine’s HIPerWall is now networked to its larger sibling,” said Stephen Jenks, professor of electrical engineering and computer science at UC Irvine and a participant in Calit2 at UCI. “With the high-speed OptIPuter network between the two Calit2 buildings, we will be able to virtually join the display walls at a distance of nearly 100 miles, so they can work together to show different parts of a huge data set or each can replicate parts of the other. We look forward to exploring remote collaboration technology and how the two systems can help researchers understand data better than ever before.”
UCSD’s HIPerSpace OptIPortal is similar to the HIPerWall because both are tiled display systems, but with different hardware. Irvine’s version is constructed with 50 Apple 30-inch Cinema Displays, powered by 25 Power Mac G5s running the Mac OS X operating system. UCSD’s Linux-based OptIPortal consists of 55 Dell displays driven by 18 Dell XPS personal computers. The system at UCSD uses the San Diego Supercomputer Center’s new 64-bit version of grid-computing middleware known as ROCKS released in early August and Calit2’s Cluster GL for heterogeneous systems (CGLX) framework, which is capable of supporting both systems concurrently.
"The usability of high-performance visualization clusters such as HiPerSpace is bound tightly to the accessibility of its resources, so cumbersome script configuration and specially-written software are no longer viable,” said Calit2 postdoctoral researcher Kai-Uwe Doerr. “The visualization software developed here at Cailt2 was designed to provide an efficient and transparent mechanism to grant access to available graphics resources and make the transition of a desktop application to a cluster seamless and uncomplicated – with minimal or no changes to the original code." Doerr and Kuester are part of a large team making HIPerSpace a reality. Others at UC San Diego include So Yamaoka; Daniel Knoblauch; Jason Kimball; Kevin Ponto; Tung-Ju Hsieh; Andres Fernandez Munuera; Tom DeFanti; Greg Dawe; Stephen Jenks; and Duy-Quoc Lai, who will start graduate school at UC Irvine this fall. Other UCI researchers on the HIPerWall end of the project include Harry Mangalam, Frank Wessel, Charlie Zender, Soroosh Sorooshian, Jean-Luc Gaudiot and Sung-Jin Kim.
Note: This story has been adapted from a news release issued by University of California, San Diego.

Fausto Intilla

www.oloscience.com

MIT aims to optimize chip designs (Model could reduce fabrication costs)

Source:

http://web.mit.edu/newsoffice/2007/circuit-0816.html

Anne Trafton,

News Office, August 16, 2007

The computer chips inside high-speed communication devices have become so small that tiny variations that appear during chip fabrication can make a big difference in performance.
Those variations can cause fluctuations in circuit speed and power so the chips don't meet their original design specifications, says MIT Professor Duane Boning, whose research team is working to predict the variation in circuit performance and maximize the number of chips working within the specifications.
The researchers have recently developed a model to characterize the variation in one kind of chip. The model could be used to estimate the ability to manufacture a circuit early in the development stages, helping to optimize chip designs and reduce costs.
"We're getting closer and closer to some of the limits on size, and variations are increasing in importance," says Boning, a professor of electrical engineering and computer science (EECS) and associate head of the department. "It's becoming much more difficult to reduce variation in the manufacturing process, so we need to be able to deal with variation and compensate for it or correct it in the design."
Boning and EECS graduate student Daihyun Lim's model characterizes variation in radio frequency integrated circuits (RFICs), which are used in devices that transfer large amounts of data very rapidly, such as high-definition TV receivers.
The researchers published their results in two papers in February and June. They also presented a paper on the modeling of variation in integrated circuits at this year's International Symposium on Quality Electronic Design.
RFIC chips are essential in many of today's high-speed communication and imaging devices. Shrinking the size of a chip's transistors to extremely small dimensions (65 nanometers, or billionths of a meter), improves the speed and power consumption of the RFIC chips, but the small size also makes them more sensitive to small and inevitable variations produced during manufacturing.
"The extremely high speeds of these circuits make them very sensitive to both device and interconnect parameters," said Boning, who is also affiliated with MIT's Microsystems Technology Laboratories. "The circuit may still work, but with the nanometer-scale deviations in geometry, capacitance or other material properties of the interconnect, these carefully tuned circuits don't operate together at the speed they're supposed to achieve."
Every step of chip manufacturing can be a source of variation in performance, said Lim. One source that has become more pronounced as chips have shrunk is the length of transistor channels, which are imprinted on chips using lithography.
"Lithography of very small devices has its optical limitation in terms of resolution, so the variation of transistor channel length is inevitable in nano-scale lithography," said Lim.
The researchers' model looks at how variation affects three different properties of circuits--capacitance, resistance and transistor turn-on voltage. Those variations cannot be measured directly, so Lim took an indirect approach: He measured the speed of the chip's circuits under different amounts of applied current and then used a mathematical model to estimate the electrical parameters of the circuits.
To the researchers' surprise, they found correlations between some of the variations in each of the three properties, but not in others. For example, when capacitance was high, resistance was low. However, the transistor threshold voltage was nearly independent of the parasitic capacitance and resistance. The different degrees of correlation should be considered in the statistical simulation of the circuit performance during design for more accurate prediction of manufacturing yield, said Lim.
The research was funded by the MARCO/DARPA Focus Center Research Program's Interconnect Focus Center and Center for Circuits and Systems Solutions, and by IBM, National Semiconductor and Samsung Electronics.

Fausto Intilla

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