Lifeboat Foundation

Nvidia took pretty much everyone by surprise when it announced it was getting into self-driving cars; it’s just not what you expect from a company that’s made its name off selling graphics cards for gamers.

At this year’s CES, it’s taking the focus on autonomous cars even further.

The company today announced the Nvidia Drive PX2. According to CEO Jen-Hsun Huang, it’s basically a supercomputer for your car. Hardware-wise, it’s made up of 12 CPU cores and four GPUs, all liquid-cooled. That amounts to about 8 teraflops of processing power, is as powerful as 6 Titan X graphics cards, and compares to ‘about 150 MacBook Pros’ for self-driving applications.

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A supercomputer simulation of a mere 10 milliseconds in the collapse of a massive star into a neutron star proves that these catastrophic events, often called hypernovae, can generate the enormous magnetic fields needed to explode the star and fire off bursts of gamma rays visible halfway across the universe.

The results of the simulation, published online Nov. 30 in advance of publication in the journal Nature, demonstrate that as a rotating star collapses, the star and its attached magnetic field spin faster and faster, forming a dynamo that revs the magnetic field to a million billion times the magnetic field of Earth.

A field this strong is sufficient to focus and accelerate gas along the rotation axis of the star, creating two jets that ultimately can produce oppositely directed blasts of highly energetic gamma rays.

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It seems evident that Microsoft is joining other top tech companies in betting on quantum computing with a clear business strategy in mind: to become the market leader in software development platforms for quantum computing. If quantum computers become the next supercomputing revolution in 2025, Microsoft stock will take a quantum leap.

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An international team of physicists including theorists from the U.S. Department of Energy’s (DOE) Brookhaven National Laboratory has published the first calculation of direct “CP” symmetry violation—how the behavior of subatomic particles (in this case, the decay of kaons) differs when matter is swapped out for antimatter. Should the prediction represented by this calculation not match experimental results, it would be conclusive evidence of new, unknown phenomena that lie outside of the Standard Model—physicists’ present understanding of the fundamental particles and the forces between them.

The current result—reported in the November 20 issue of Physical Review Letters —does not yet indicate such a difference between experiment and theory, but scientists expect the precision of the calculation to improve dramatically now that they’ve proven they can tackle the task. With increasing precision, such a difference—and new physics—might still emerge.

“This so called ‘direct’ symmetry violation is a tiny effect, showing up in just a few particle decays in a million,” said Brookhaven physicist Taku Izubuchi, a member of the team performing the calculation. Results from the first, less difficult part of this calculation were reported by the same group in 2012. However, it is only now, with completion of the second part of this calculation—which was hundreds of times more difficult than the first—that a comparison with the measured size of direct CP violation can be made. This final part of the calculation required more than 200 million core processing hours on supercomputers, “and would have required two thousand years using a laptop,” Izubuchi said.

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Intel’s new Xeon Phi won’t just power next-generation supercomputers — it’s going to make a debut in workstations as well.

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Intel tries to bring more computing muscle to desks.

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This is the world’s largest nuclear fusion reactor launching this month in Germany. And it was designed by a supercomputer…

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The Blue Brain Project is a vast effort by 82 scientists worldwide to digitally recreate the human brain. While still far from that goal, the team revealed a breakthrough that has already provided insight into sleep, memory and neurological disorders. They created a simulation of a third of a cubic millimeter of a rat’s brain. While that might not sound like much, it involves 30,000 neurons and 37 million synapses. In addition, the simulated level of biological accuracy is far beyond anything so far. It allowed them to reproduce known brain activities — such as how neurons respond to touch — and has already yielded discoveries about the brain that were impossible to get biologically.

To create the simulation, researchers did thousands of experiments on rat brains over a 20 year period, logging each type of synapse and neuron discovered. That led to a set of fundamental rules describing how neurons connect to synapses and form microcircuits. Using the data, they developed an algorithm to pinpoint the synapse locations, simulating the circuitry of a rat’s brain. All of that data was then run through a supercomputer: “It was only with this kind of infrastructure that we could solve the billions of equations needed,” said software lead Felix Schurmann.

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