IBM Researchers Develop Energy Efficient Method to Analyze the Quality of Data at Record Speeds


In a record-breaking experiment, IBM researchers used the fourth most powerful supercomputer in the world -- a Blue Gene/P system at the Forschungszentrum Julich in Germany -- to validate nine terabytes of data (nine million million or a number with 12 zeros) in less than 20 minutes, without compromising accuracy. Ordinarily, using the same system, this would take more than a day. Additionally, the process used just one percent of the energy that would typically be required.

The new method demonstrated by the IBM scientists brings down computational complexity and has very good scaling characteristics that reach to the full scale of the JuGene Supercomputer at the Forschungszentrum Julich with its 72 racks of IBM's Blue Gene/P system, 294,912 processors and a peak performance of one petaflop.

"In the next years supercomputing will provide us with unique insights and will help to create added value with new technologies," says Prof. Dr. Thomas Lippert, Director of the Julich Supercomputing Centre. "A cornerstone for the future will be innovative tools and algorithms helping us to analyze the huge amount of data provided by simulations on the most powerful computers."



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High Performance Computing Workshop at Rice University Advances Case for Education


Tim Mattson, an applications programmer at Intel, delivered an impassioned plea at Rice University Thursday to audience members who may be in the market for high-performance computing resources: Make manufacturers play nice.

"Hardware is marching along, but if you want really great software (portability and tools), I'm telling you folks, it's a train wreck. We are setting up a great train wreck here, and I'm hoping we can avoid it," he said.

"We have to remember we're at many-core solutions because we're limited in our ability to crank the frequency on a chip," Mattson said. "We have a very deep, fundamental -- and from the point of view of a computer company -- a very dangerous mismatch. Parallel hardware is ubiquitous, and it's getting more and more parallel and more and more ubiquitous. Parallel software is rare, and I don't see anything changing that."



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Intel Unveils New Product Plans for High-Performance Computing: Intel® Many Integrated Core Chips to Extend Intel's Role in Accelerating Science and Discovery


NEWS HIGHLIGHTS

• The first product codenamed "Knights Corner" will target Intel's 22nm process and use Moore's Law to scale to more than 50 Intel cores.
  
• Intel® Xeon® processors and Intel® Many Integrated Core architecture-based products to share common tools, software algorithms and programming techniques.
  
• Products build upon Intel's history of many-core related research including Intel's "Larrabee" program and Single-chip Cloud Computer.
  
• The share of the TOP500 list that features Intel processors grows to 408 systems, nearly 82 percent.

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One IBM System z10 Enterprise Class mainframe, the biggest, is equal to 1,500 Intel servers and occupies 85% less space.

The machines range in computational power from smaller models that can manage 26 million instructions per second to the biggest machines that crank through 30 billion instructions per second. And, said Mr Porell, it is theoretically possible to chain 30 of the biggest machines together in one giant cluster.

While he admits that no-one has done that yet, some firms have amassed significant mainframe power. Giant US retail chain WalMart, said Mr Porell, has 54.

"There's one in each distribution centre to manage the assembly line that moves goods from storage out onto the tractor trailers," he said.


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In this video, I interview Andy Keane, NVIDIA General Manager of Tesla Business. He discusses the advantages of GPUs for HPC and gives us his views on power efficiency and Exascale computing.

Learn more about Tesla GPU computing at: http://www.nvidia.com/object/tesla_co...

AMD announced its share of the TOP500 supercomputer list has grown 15 percent in the past six months. The company credits industry trends, upgrade paths, and competitive pricing for the increase. Of the 68 Opteron-based systems on the list, more than half of them use the Opteron 6100 series processors. We covered the launch of Magny-Cours more than a year ago; AMD's current lineup includes the dodeca-core Opteron 6180 SE at 2.5GHz at one end and two low-power parts at the other.

If current trends continue, AMD's share of the supercomputer market will slowly rise. The chart is interesting in its own right. Intel's share of the industry exploded virtually overnight, from a bare footnote in 2001 to a huge slice of the market in 2005. AMD's Opteron debut went extremely well, but topped out in 2006. It fell steadily for several years thereafter, thanks to increased pressure from Intel's Core architecture.


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As I see it, the only system that can hit both the performance goals and the budget limitation is a standard based system. X86 (Intel or AMD) processors and the InfiniBand network might do the job. If only NCSA was clever enough to go for it the first time, I bet that the system would have been already up and running and with the change they could focus on some innovative software development.

The Pleiades Supercomputer at NASA/Ames Research Center is a great example for a cost effective, high-performance system. 184 racks (11,712 nodes), 1.315 Pflop/s peak cluster, 1.09 Pflop/s Linpack, 111,872 total cores (no GPUs), InfiniBand interconnect, partial 11D hypercube topology (SGI in this case, but you can pick any other topology as well). 12 DDN RAIDs, 6.9 Peta byte total, Lustre. Could be a good example to what NCAS needs to do now?


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Flat-out speed, for a long time the measure of a supercomputer's worth, may be going out of style. A recent report from an influential federal panel recommended more emphasis on software and alternative designs rather than computational Ferraris. Still, fast computers attract top faculty—and federal money. "Every con­gressman loves to sign his name to the latest, greatest machine," Mr. Dunning acknowledges. "That's the photo op. You don't get the same photo ops with software."

Think, say advocates, of the folly of a best-car list based only on top speed. So what if a Ferrari is faster than a Volvo station wagon when you have to take two kids to soccer practice?

In November, still another supercomputer ranking was unveiled, at a conference in New Orleans. This one, called Graph500, does produce a ranking, but it is based on how fast supercomputers solve complex problems related to randomly generated graphs, rather than on the simpler computation of the Top 500. Some computers that had ranked well on the Top 500 ran the Graph500, but their operators refused to announce the scores, most likely because they fared less well.


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Intel targets exascale computing with new technologies


The chipmaker has set its sights on building a computer capable of an exaflop — one thousand petaflops, roughly a hundred times faster than the world's leading supercomputer as of June — by 2018. The supercomputer would consume less than 20 megawatts of power; this equates to a power efficiency improvement of about 300 times over today's supercomputers, Justin Rattner, Intel's chief technology officer, said on Thursday at the Intel Developer Forum.

"The challenge here is generating that much computing power within a modest 20 megawatt-power budget. Today a petaflop[-scale] computer is burning something between five and seven megawatts," he said. "If we scaled that up it'd [consume power] in the gigawatt range and I'd need to buy everyone a nuclear reactor."

To achieve its goal Intel will need to bring in new memory, processor and interconnect technologies to drive performance while lowering overall power consumption, Rattner said.


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