An anonymous reader writes "If you have a fascination with old supercomputers, like I do, this project might tickle your interest: A functional simulation of a Cray X-MP supercomputer, which can boot to its old batch operating system, called COS. It's complete with hard drive and tape simulation (no punch card readers, sorry) and consoles. Source code and binaries are available. You can also read about the journey that got me there, like recovering the OS image from a 30 year old hard drive or reverse-engineering CRAY machine code to understand undocumented tape drive operation and disk file-systems."

Nerval's Lobster writes "Breaking the exaflops barrier remains a development goal for many who research high-performance computing. Some developers predicted that China's new Tianhe-2 supercomputer would be the first to break through. Indeed, Tianhe-2 did pretty well when it was finally revealed — knocking the U.S.-based Titan off the top of the Top500 list of the world's fastest supercomputers. Yet despite sustained performance of 33 petaflops to 35 petaflops and peaks ranging as high as 55 petaflops, even the world's fastest supercomputer couldn't make it past (or even close to) the big barrier. Now, the HPC market is back to chattering over who'll first build an exascale computer, and how long it might take to bring such a platform online. Bottom line: It will take a really long time, combined with major breakthroughs in chip design, power utilization and programming, according to Nvidia chief scientist Bill Dally, who gave the keynote speech at the 2013 International Supercomputing Conference last week in Leipzig, Germany. In a speech he called 'Future Challenges of Large-scale Computing' (and in a blog post covering similar ground), Dally described some of the incredible performance hurdles that need to be overcome in pursuit of the exaflops barrier."

nk497 writes "Are you more likely to die from cancer or be wiped out by a malevolent computer? That thought has been bothering one of the co-founders of Skype so much he teamed up with Oxbridge researchers in the hopes of predicting what machine super-intelligence will mean for the world, in order to mitigate the existential threat of new technology – that is, the chance it will destroy humanity. That idea is being studied at the University of Oxford's Future of Humanity Institute and the newly launched Centre for the Study of Existential Risk at the University of Cambridge, where philosophers look more widely at the possible repercussions of nanotechnology, robotics, artificial intelligence and other innovations — and to try to avoid being outsmarted by technology."

dcblogs writes "Unlike China and Europe, the U.S. has yet to adopt and fund an exascale development program, and concerns about what that means to U.S. security are growing darker and more dire. If the U.S. falls behind in HPC, the consequences will be 'in a word, devastating,' Selmer Bringsford, chair of the Department. of Cognitive Science at Rensselaer Polytechnic Institute, said at a U.S. House forum this week. 'If we were to lose our capacity to build preeminently smart machines, that would be a very dark situation, because machines can serve as weapons.' The House is about to get a bill requiring the Dept. of Energy to establish an exascale program. But the expected funding level, about $200 million annually, 'is better than nothing, but compared to China and Europe it's at least 10 times too low,' said Earl Joseph, an HPC analyst at IDC. David McQueeney, vice president of IBM research, told lawmakers that HPC systems now have the ability to not only deal with large data sets but 'to draw insights out of them.' The new generation of machines are being programmed to understand what the data sources are telling them, he said."

MojoKid writes "Intel announced a set of new enterprise products today aimed at furthering its strengths in the TOP500 supercomputing market. As of today, the Chinese Tiahne-2 supercomputer (aka Milky Way 2) is now the fastest supercomputer on the planet at roughly ~54PFLOPs. Intel is putting its own major push behind heterogeneous computing with the Tianhe-2. Each node contains two Ivy Bridge sockets and three Xeon Phi cards. Each node, therefore, contains 422.4GFLOP/s in Ivy Bridge performance — but 3.43TFLOPs/s worth of Xeon Phi. In addition, we'll see new Xeons based on this technology later this year, in the 22nm E5-2600 V2 family, with up to 12 cores. The new chips will be built on Ivy Bridge technology and will offer up to 12 cores / 24 threads. The new Xeons, however, aren't really the interesting part of the story. Today, Intel is adding cards to the current Xeon Phi lineup — the 7120P, 3120P, 3120A, and 5120D. The 3120P and 3120A are the same card — the 'P' is passively cooled, while the "A" integrates a fan. Both of these solutions have 57 CPUs and 6GB of RAM. Intel states that they offer ~1TFLOP of performance, which puts them on par with the 5110P that launched last year, but with slightly less memory and presumably a lower price point. At the top of the line, Intel is introducing the 7120P and 7120X — the 7120P comes with an integrated heat spreader, the 7120X doesn't. Clock speeds are higher on this card, it has 61 cores instead of 60, 16GB of GDDR5, and 352GBps of memory bandwidth. Customers who need lots of cores and not much RAM can opt for one of the cheaper 3100 cards, while the 7100 family allows for much greater data sets."

An anonymous reader writes "China's Tianhe-2 is the world's fastest supercomputer, according to the latest semiannual Top 500 list of the 500 most powerful computer systems in the world. Developed by China's National University of Defense Technology, the system appeared two years ahead of schedule and will be deployed at the National Supercomputer Center in Guangzho, China, before the end of the year."

aarondubrow writes "Researchers recently created OpenfMRI, a web-based, supercomputer-powered tool that makes it easier for researchers to process, share, compare and rapidly analyze fMRI brain scans from many different studies. Applying supercomputing to the fMRI analysis allows researchers to conduct larger studies, test more hypotheses, and accommodate the growing spatial and time resolution of brain scans. The ultimate goal is to collect enough brain data to develop a bottom-up understanding of brain function."

aarondubrow writes "For more than 50 years, linguists and computer scientists have tried to get computers to understand human language by programming semantics as software, with mixed results. Enabled by supercomputers at the Texas Advanced Computing Center, University of Texas researchers are using new methods to more accurately represent language so computers can interpret it. Recently, they were awarded a grant from DARPA to combine distributional representation of word meanings with Markov logic networks to better capture the human understanding of language."

New submitter DeathGrippe sends in an article from Wired about a new take on distributed computing efforts like SETI@Home. From Wired: "By inserting a bit of JavaScript into a webpage, Pethiyagoda says, a site owner could distribute a problem amongst all the site's visitors. Visitors' computers or phones would be running calculations in the background while they read a page. With enough visitors, he says, a site could farm out enough small calculations to solve some difficult problems. ... With this year's run on the value of Bitcoins — the popular digital currency — security expert Mikko Hyppönen thinks that criminals might soon start experimenting with this type of distributed computing too. He believes that crooks could infect websites with JavaScript code that would turn visitors into unsuspecting Bitcoin miners. As long as you're visiting the website, you're mining coins for someone else."

An anonymous reader writes "With help from a draft report (PDF) from Oak Ridge National Laboratory's Jack Dongarra, who also spearheads the process of verifying the top of the pack supercomputer, we get a detailed look at China's Tianhe-2 system. As noted previously, the system will be housed at the National Supercomputer Center in Guangzhou and has been aimed at providing an open platform for research and education and to provide a high performance computing service for southern China. From Jack's details: '... was sent results showing a run of HPL benchmark using 14,336 nodes, that run was made using 50 GB of the memory of each node and achieved 30.65 petaflops out of a theoretical peak of 49.19 petaflops, or an efficiency of 62.3% of theoretical peak performance taking a little over 5 hours to complete.The fastest result shown was using 90% of the machine. They are expecting to make improvements and increase the number of nodes used in the test.'"

Nerval's Lobster writes "The Texas Advanced Computing Center (TACC) at The University of Texas at Austin is going to get a major speed boost this summer, and it won't come from new CPUs. Internet2, the research project that acts as a test bed for new Internet technologies, will take TACC's massive computing system from 10GB to 100GB of Ethernet throughput. TACC supercomputers are regularly found near the top of the Top 500 supercomputer list, which ranks the world's fastest supercomputers. But while the supercomputers were fast, the connectivity wasn't quite up to snuff. So TACC began the emigration to the Internet2 network. TACC is a key partner in the UT Research Cyberinfrastructure, which provides a combination of advanced computing, high-bandwidth network connectivity, and large data storage to all 15 of the UT system schools. So not only is TACC upgraded to Internet2s 100GB and 8.8 terabit-per-second optical network, platform, services and technologies, so is the entire UT system. 'This Internet2 bandwidth upgrade will enable researchers to achieve a tenfold increase in moving data to/from TACC's supercomputing, visualization and data storage systems, greatly increasing their productivity and their ability to make new discoveries,' TACC director Jay Boisseau wrote in a statement."

An anonymous reader writes "Commodity ARM CPUs are poised to to replace x86 CPUs in modern supercomputers just as commodity x86 CPUs replaced vector CPUs in early supercomputers. An analysis by the EU Mountblanc Project (PDF) (using Nvidia Tegra 2/3, Samsung Exynos 5 & Intel Core i7 CPUs) highlights the suitability and energy efficiency of ARM-based solutions. They finish off by saying, 'Current limitations [are] due to target market condition — not real technological challenges. ... A whole set of ARM server chips is coming — solving most of the limitations identified.'"

gbrumfiel writes "Last week, Google and NASA announced a partnership to buy a new quantum computer from Canadian firm D-Wave Systems. But NPR news reports that many scientists are still questioning whether new machine really is quantum. Long-time critic and computer scientist Scott Aaronson has a long post detailing the current state of affairs. At issue is whether the 512 quantum bits at the processor's core are 'entangled' together. Measuring that entanglement directly destroys it, so D-Wave has had a hard time convincing skeptics. As with all things quantum mechanical, the devil is in the details. Still it may not matter: D-Wave's machine appears to be far faster at solving certain kinds of problems (PDF), regardless of how it works."

riverat1 writes "After being embarrassed when the Europeans did a better job forecasting Sandy than the National Weather Service Congress allocated $25 million ($23.7 after sequestration) in the Sandy relief bill for upgrades to forecasting and supercomputer resources. The NWS announced that their main forecasting computer will be upgraded from the current 213 TeraFlops to 2,600 TFlops by fiscal year 2015, over a twelve-fold increase. The upgrade is expected to increase the horizontal grid scale by a factor of 3 allowing more precise forecasting of local features of weather. The some of the allocated funds will also be used to hire some contract scientists to improve the forecast model physics and enhance the collection and assimilation of data."

ananyo writes "D-Wave, the small company that sells the world's only commercial quantum computer, has just bagged an impressive new customer: a collaboration between Google, NASA and the non-profit Universities Space Research Association. The three organizations have joined forces to install a D-Wave Two, the computer company's latest model, in a facility launched by the collaboration — the Quantum Artificial Intelligence Lab at NASA's Ames Research Center. The lab will explore areas such as machine learning — useful for functions such as language translation, image searches and voice-command recognition. The Google-led collaboration is only the second customer to buy computer from D-Wave — Lockheed Martin was the first."

An anonymous reader sends this excerpt from Wired: "[Henry] Markram was proposing a project that has bedeviled AI researchers for decades, that most had presumed was impossible. He wanted to build a working mind from the ground up. ... The self-assured scientist claims that the only thing preventing scientists from understanding the human brain in its entirety — from the molecular level all the way to the mystery of consciousness — is a lack of ambition. If only neuroscience would follow his lead, he insists, his Human Brain Project could simulate the functions of all 86 billion neurons in the human brain, and the 100 trillion connections that link them. And once that's done, once you've built a plug-and-play brain, anything is possible. You could take it apart to figure out the causes of brain diseases. You could rig it to robotics and develop a whole new range of intelligent technologies. You could strap on a pair of virtual reality glasses and experience a brain other than your own."

anzha writes "Horst Simon, Deputy Director of Lawrence Berkeley National Laboratory, has stood up at conferences of late and said the unthinkable: supercomputing is hitting a wall and will not build an exaFLOPS HPC system by 2020. This is defined as one that passes linpack with a performance of one exaFLOPS sustained or better. He's even placed money on it. You can read the original presentation here."

Nerval's Lobster writes "Japan has thrown its hat into the ring for exascale computing, reported the country's newspapers. The goal: achieve one exaFLOPS of performance by 2020. Japan's finance ministry has agreed to begin work next fiscal year on a supercomputer with a performance capability 100 times that of the K computer, a 10-petaFLOPS computer that debuted as the most powerful supercomputer in the world in 2011. The midterm report for the new supercomputer was concluded Thursday, the Asahi Shimbun business daily reported. The Japan Times was slightly more conservative, reporting that the Education, Culture, Sports, Science and Technology Ministry will seek funding to design the new machine in its fiscal 2014 budget request — implying that the project has not necessarily been approved. The science ministry is hoping to keep the cost of the new supercomputer below the ¥110 billion mark ($1.08 billion) that was required to develop the K computer, the paper reported. (Slashdot couldn't find any evidence that the project had been approved on the ministry Webpage, although the K computer was mentioned several times in a discussion of public-private partnerships.)"

Nerval's Lobster writes "The 'Sequoia' Blue Gene/Q supercomputer at the Lawrence Livermore National Laboratory (LLNL) has topped a new HPC record, helped along by a new 'Time Warp' protocol and benchmark that detects parallelism and automatically improves performance as the system scales out to more cores. Scientists at the Rensselaer Polytechnic Institute and LLNL said Sequoia topped 504 billion events per second, breaking the previous record of 12.2 billion events per second set in 2009. The scientists believe that such performance enables them to reach so-called "planetary"-scale calculations, enough to factor in all 7 billion people in the world, or the billions of hosts found on the Internet. 'We are reaching an interesting transition point where our simulation capability is limited more by our ability to develop, maintain, and validate models of complex systems than by our ability to execute them in a timely manner,' Chris Carothers, director of the Computational Center for Nanotechnology Innovations at RPI, wrote in a statement."

Lank writes "A team of computer scientists from Lawrence Livermore National Laboratory and Rensselaer Polytechnic Institute have managed to coordinate nearly 2 million cores to achieve a blistering 504 billion events per second, over 40 times faster than the previous record. This result was achieved on Sequoia, a 120-rack IBM Blue Gene/Q normally used to run classified nuclear simulations. Note: I am a co-author of the coming paper to appear in PADS 2013."