VizWorld.com

Congratulations to Kitware and Berk Geveci for winning a nice $150k DOE grant to build a new user-friendly data analysis application for the complex worldwide climate science databases.

“ClimatePipes will provide access to data that can have a real impact on global climate changes. It will allow the public to better appreciate climate change and enable industries to use climate data in a variety of unforeseen applications,” said Berk Geveci, director of scienfitic computing at Kitware and principle investigator on this SBIR grant. “Our solution aims to be the platform for user-friendly data access, but not to replace high-end analysis tools for scientists. We are looking forward to a tool that is very simple, intuitive, and that can be used by non-researchers and non-programmers.”

I can’t say for certain, but I suspect this will rely heavily on their already built “ParaViewWeb” system for the visualization parts, but I look forward to seeing what they come up with for data provenance.

via Kitware Awarded Department of Energy Research Grant to aid Access to Data Provided by the Ongoing Efforts of the U.S. Global Change Research Program.

Science climate, doe, kitware, nsf

Researchers at Lawrence Berkeley National Lab (LBNL) collaborated with the Department of Energy Nanoscale Science Research Centers and MIT to create some new hardware and software for imaging nanoscale structures smaller than the wavelength of light.

In parallel with Schuck’s experimental findings, Jeff Neaton, Director of the Molecular Foundry ’s Theory of Nanostructured Materials Facility and Alex McLeod, an undergraduate student working at the Foundry, developed a web-based toolkit, designed to calculate images of plasmonic devices with open-source software developed at Massachusetts Institute of Technology. For this study, the researchers simulated adjusting the structure of a double bowtie antenna by a few nanometers to study how changing the size and symmetry of a plasmonic antenna affects its optical properties.

The article is a bit light on any more details, but they’ve created an interesting looking web-based visualization tool to see the results, combined with some interesting imaging hardware.  They have a paper publishing their results in Physical Review Letters called “Non-perturbative visualization of nanoscale plasmonic field distributions via photon localization microscopy” that you can get here (purchase required).

If you find the paper elsewhere, let me know!

via Berkeley Lab Team Uses New Imaging Concept to Visualize Plasmonic Fields at Nanoscale. and the LBL Website

Science doe, imaging, nanotechnology, research, whitepaper

NPR has an article on Virtual world technology in sue by the Los Alamos National Lab (LANL) to create reconstructions of various nuclear laboratory environments.  The main benefits are that such environments are rare and dangerous, so training is hard to come by.  By training such people in virtual space with photorealistic environments, people can see areas typically reserved for only the most adventurous of personnel.  The project, called VISIBLE (Virtual Simulation Baseline Experience) has been underway for about three years, with their big claim to fame being the virtual version of the Idaho National Lab reactor.

Birch Hayes, the project’s key software expert, says response from the Idaho lab was positive.

“We gave this to them and they’ve used it in a number of ways — for visitors, trainees, new employees. We showed it at a workshop and then the following day took people out to the facility, and they felt like they had been there before, which was exactly the effect that we were looking for,” Hayes says.

via Using Virtual Reality To Make Nuclear Reality Safer : NPR.

Science doe, lanl, training, virtual worlds

Details of the massive VisIt run announced a while back, are starting to come out, and while they still aren’t publishing any concrete details, you can find some interesting details about the systems and testing procedures used:

The VACET team ran the experiments in April and May on six world-class supercomputers (latest TOP500 rankings noted):

• Franklin — a 38,128-core Cray XT4 located at the National Energy Research Scientific Computing Center (NERSC) at Berkeley Lab (No. 11)
• JaguarPF — a 149,504-core Cray XT5 at the Oak Ridge Leadership Computing Facility at ORNL (No. 2)
• Ranger — a 62,976-core x86_64 Linux system at the Texas Advanced Computing Center at the University of Texas at Austin (No. 8 )
• Purple — a 12,288-core IBM Power5 at LLNL (No. 50)
• Juno — an 18,432-core x86_64 Linux system at LLNL (No. 19)
• Dawn — a 147,456-core BlueGene/P system at LLNL (No. 9)

One thing I quickly noticed from this list: Nothing from SGI.  (I would say Nothing from SUN as well, but I think the Ranger system is SUN).  But, aside from “because we can”, why did they do this? First is the following claim from Wes Bethel:

“The results show that visualization research and development efforts have produced technology that is today capable of ingesting and processing tomorrow’s datasets,” said Berkeley Lab’s E. Wes Bethel, who is co-leader of VACET. “These results are the largest-ever problem sizes and the largest degree of concurrency ever attempted within the DOE visualization research community.”

But more to the point is this:

Another purpose of these runs was to prepare for establishing VisIt’s credentials as a “Joule code,” or a code that has demonstrated scalability at a large number of cores. DOE’s Office of Advanced Scientific Computing Research (ASCR) is establishing a set of such codes to serve as a metric for tracking code performance and scalability as supercomputers are built with tens and hundreds of thousands of processor cores. VisIt is the first and only visual data analysis code that is part of the ASCR Joule metric.

via Smashing the Trillion Zone Barrier.

PS: The comment about “nothing from SGI” is meant as a bash against SGI, as in the DoE knows better than to run any SGI’s, not a bash against the credibility of the test.

Science doe, hpc, simulation, vacet, visit, visualization

HPCWire is carrying a story that a group of researchers have pushed VisIt into record-breaking territory by running visualizations of 500billion to 2trillion gridpoint datasets (that’s 2-terapoints in size).

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 (Berkeley Lab), Lawrence Livermore National Laboratory (LLNL) and Oak Ridge National Laboratory (ORNL).

Seems a good portion of the Department of Energy‘s Visualization staff was involved: Wes Bethel, Sean Ahern, Mark Howison, Dave Pugmire, and others.

The test runs created three-dimensional grids ranging from 512 x 512 x 512 “zones” or sample points up to approximately 10,000 x 10,000 x 10,000 samples for 1 trillion zones and approximately 12,500 x 12,500 x 12,500 to achieve 2 trillion grid points.

“This level of grid resolution, while uncommon today, is anticipated to be commonplace in the near future,” said Ahern. “A primary objective for our SciDAC Center is to be well prepared to tackle tomorrow’s scientific data understanding challenges.”

The tests consisted of isosurfaces and volume renderings.  While they don’t mention the results of the tests, they did carefully monitor them and collect benchmarking data that can be used in further development of VisIt.

Click the banner image above for larger Volume Rendering from the test.

via HPCwire: DOE Researchers Test Limits of Visualization Tool.

Science benchmark, doe, extreme, scidac, software, visit

The Department of Energy (DOE) is putting 1.3Billion Processor Hours out to the public for simulation and research of several phenomena.  The hours are split between the Oak Ridge Cray XT “Jaguar” and Argonne IBM BlueGene/P “Intrepid” systems, and are for unclassified open research.

In 2009, 900 million processor hours were up for grabs (a million processing hours would take 1,000 processors 1,000 hours, or around 41 days), but both computers received huge performance boosts this year. Jaguar’s processor count has shot up from 31,328 to 180,832, while Intrepid now boasts 163,840 from 32,768. Jaguar’s peak performance is now a blistering 1.64 petaflops (a quadrillion and a half floating point operations per second), making it the second most powerful supercomputer on Earth.

While the article talks alot about the science the new machines facilitate, I see nothing about how they intend to perform Analysis or Visualization of this scale of data.  An oversight?  I know some DOE folks are watching, care to elaborate?

via Record Amount of Supercomputer Time Means New Science | Wired Science.

Science argonne, doe, government, ornl