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The Cray-1 supercomputer, the world’s fastest back in the 1970s, does not look like a supercomputer. It looks like a mod version of that carnival ride The Round Up, the one where you stand, strapped in, as it dizzies you up. It’s surrounded by a padded bench that conceals its power supplies, like a cake donut, if the hole was capable of providing insights about nuclear weapons.

After Seymour Cray first built this computer, he gave Los Alamos National Laboratory a six-month free trial. But during that half-year, a funny thing happened: The computer experienced 152 unattributable memory errors. Later, researchers would learn that cosmic-ray neutrons can slam into processor parts, corrupting their data. The higher you are, and the bigger your computers, the more significant a problem this is. And Los Alamos—7,300 feet up and home to some of the world’s swankiest processors—is a prime target.

The world has changed a lot since then, and so have computers. But space has not. And so Los Alamos has had to adapt—having its engineers account for space particles in its hard- and software. “This is not really a problem we’re having,” explains Nathan DeBardeleben of the High Performance Computing Design group. “It’s a problem we’re keeping at bay.”

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This new law was signed just as a partial US government shutdown began.


The new National Quantum Initiative Act will give America a national masterplan for advancing quantum technologies.

The news: The US president just signed into law a bill that commits the government to providing $1.2 billion to fund activities promoting quantum information science over an initial five-year period. The new law, which was signed just as a partial US government shutdown began, will provide a significant boost to research, and to efforts to develop a future quantum workforce in the country.

The background: Quantum computers leverage exotic phenomena from quantum physics to produce exponential leaps in computing power. The hope is that these machines will ultimately be able to outstrip even the most powerful classical supercomputers. Those same quantum phenomena can also be tapped to create highly secure communications networks and other advances.

An international team of physicists and materials scientists from NUST MISIS, Bayerisches Geoinstitut (Germany), Linkoping University (Sweden), and the California Institute of Technology (U.S.) has discovered an “impossible” modification of silica-coesite-IV and coasite-V materials, which seems to defy the generally accepted rules for the formation of chemical bonds in inorganic materials formulated by Linus Pauling, who won the 1954 Nobel Prize in Chemistry for that discovery. The research results were published in Nature Communications on November 15th, 2018.

According to Pauling’s rules, the fragments of the atomic lattice in inorganic materials are connected by vertices, because bonding by faces is the most energy-intensive way to form a chemical connection. Therefore, it does not exist in nature. However, scientists have proved, both experimentally and theoretically, using NUST MISIS’ supercomputer, that it is possible to form such a connections if the materials are at ultra-high pressure conditions. The obtained results show that fundamentally new classes of materials exist at extreme conditions.

“In our work, we have synthesized and described metastable phases of high-pressure silica: coesite-IV and coesite-V. Their crystal structures are drastically different from any of the earlier described models,” says Igor Abrikosov, leader of the theoretical research team. “Two newly discovered coesites contain octahedrons SiO6, that, contrary to Pauling’s rule, are connected through common face, which is the most energy-intensive chemical connection. Our results show that the possible silicate magmas in the lower mantle of the Earth can have , which makes these magmas more compressible than predicted before.”

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Scientists look around the universe and see amazing structure. There are objects and processes of fantastic complexity. Every action in our universe follows exact laws of nature that are perfectly expressed in a mathematical language. These laws of nature appear fine-tuned to bring about life, and in particular, intelligent life. What exactly are these laws of nature and how do we find them?

The universe is so structured and orderly that we compare it to the most complicated and exact contraptions of the age. In the 18th and 19th centuries, the universe was compared to a perfectly working clock or watch. Philosophers then discussed the Watchmaker. In the 20th and 21st centuries, the most complicated object is a computer. The universe is compared to a perfectly working supercomputer. Researchers ask how this computer got its programming.

How does one explain all this structure? Why do the laws seem so perfect for producing life and why are they expressed in such exact mathematical language? Is the universe really as structured as it seems?

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NASA engineers are using some of the most powerful supercomputers in the world to design rotary wing vehicles that combine both piloted and autonomous operations. Urban Air Mobility is a safe and efficient system that can transport a small number of passengers and cargo, without the need for long runways. Check it out: https://go.nasa.gov/2FvGPfH

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NVIDIA’s playing a bigger role in high performance computing than ever, just as supercomputing itself has become central to meeting the biggest challenges of our time.

Speaking just hours ahead of the start of the annual SC18 supercomputing conference in Dallas, NVIDIA CEO Jensen Huang told 700 researchers, lab directors and execs about forces that are driving the company to push both into “scale-up” computing — focused on large supercomputing systems — as well as “scale-out” efforts, for researchers, data scientists and developers to harness the power of however many GPUs they need.

“The HPC industry is fundamentally changing,” Huang told the crowd. “It started out in scientific computing, and the architecture was largely scale up. Its purpose in life was to simulate from first principles the laws of physics. In the future, we will continue to do that, but we have a new tool — this tool is called machine learning.”

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SpiNNaker was built under the leadership of Professor Steve Furber at The University of Manchester, a principal designer of two products that earned the Queen’s Award for Technology —the ARM 32-bit RISC microprocessor, and the BBC Microcomputer.

“The ultimate objective for the project has always been a million cores in a single computer for real time brain modelling applications, and we have now achieved it, which is fantastic.” — Professor Steve Furber, The University of Manchester

Inspired by the human brain, the SpiNNaker is capable of sending billions of small amounts of information simultaneously. The SpiNNaker has a staggering 1 million processors that are able to perform over 200 million actions per second.

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Lattice QCD is not only teaching us how the strong interactions lead to the overwhelming majority of the mass of normal matter in our Universe, but holds the potential to teach us about all sorts of other phenomena, from nuclear reactions to dark matter.

Later today, November 7th, physics professor Phiala Shanahan will be delivering a public lecture from Perimeter Institute, and we&s;ll be live-blogging it right here at 7 PM ET / 4 PM PT. You can watch the talk right here, and follow along with my commentary below. Shanahan is an expert in theoretical nuclear and particle physics and specializes in supercomputer work involving QCD, and I&s;m so curious what else she has to say.

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Imagine building a machine so advanced and precise you need a supercomputer to help design it. That’s exactly what scientists and engineers in Germany did when building the Wendelstein 7-X experiment. The device, funded by the German federal and state governments and the European Union, is a type of fusion device called a stellarator. The new experiment’s goal is to contain a super-heated gas, called plasma, in a donut-shaped vessel using magnets that twist their way around the donut.

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