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Archive for the ‘supercomputing’ category: Page 58

Oct 22, 2020

Million-core neuromorphic supercomputer could simulate an entire mouse brain

Posted by in categories: robotics/AI, supercomputing

Circa 2018


After 12 years of work, researchers at the University of Manchester in England have completed construction of a “SpiNNaker” (Spiking Neural Network Architecture) supercomputer. It can simulate the internal workings of up to a billion neurons through a whopping one million processing units.

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Oct 15, 2020

Nvidia will power world’s fastest AI supercomputer, to be located in Europe

Posted by in categories: robotics/AI, supercomputing

Nvidia is is going to be powering the world’s fastest AI supercomputer, a new system dubbed “Leonardo” that’s being built by the Italian multi-university consortium CINECA, a global supercomputing leader. The Leonardo system will offer as much as 10 exaflops of FP16 AI performance capabilities, and be made up of more than 14,000 Nvidia Ampere-based GPUS once completed.

Leonardo will be one of four new supercomputers supported by a cross-European effort to advance high-performance computing capabilities in the region, which will eventually offer advanced AI capabilities for processing applications across both science and industry. Nvidia will also be supplying its Mellanox HDR InfiniBand networks to the project in order to enable performance across the clusters with low-latency broadband connections.

The other computers in the cluster include MeluXina in Luxembourg and Vega in Slovenia, as well as a new supercooling unit coming online in the Czech Republic. The pan-European consortium also plans four more Supercomputers for Bulgaria, Finland, Portugal and Spain; though, those will follow later and specifics around their performance and locations aren’t yet available.

Oct 12, 2020

Generating Megatesla Magnetic Fields on Earth Using Intense-Laser-Driven Microtube Implosions

Posted by in categories: biotech/medical, engineering, supercomputing

A team of researchers led by Osaka University discovers “microtube implosion,” a novel mechanism that demonstrates the generation of megatesla-order magnetic fields.

Magnetic fields are used in various areas of modern physics and engineering, with practical applications ranging from doorbells to maglev trains. Since Nikola Tesla’s discoveries in the 19th century, researchers have strived to realize strong magnetic fields in laboratories for fundamental studies and diverse applications, but the magnetic strength of familiar examples are relatively weak. Geomagnetism is 0.3−0.5 gauss (G) and magnetic tomography (MRI) used in hospitals is about 1 tesla (T = 104 G). By contrast, future magnetic fusion and maglev trains will require magnetic fields on the kilotesla (kT = 107 G) order. To date, the highest magnetic fields experimentally observed are on the kT order.

Recently, scientists at Osaka University discovered a novel mechanism called a “microtube implosion,” and demonstrated the generation of megatesla (MT = 1010 G) order magnetic fields via particle simulations using a supercomputer. Astonishingly, this is three orders of magnitude higher than what has ever been achieved in a laboratory. Such high magnetic fields are expected only in celestial bodies like neutron stars and black holes.

Oct 12, 2020

The Coming Internet: Secure, Decentralized and Immersive

Posted by in categories: computing, disruptive technology, electronics, information science, internet, open access, supercomputing

The blockchain revolution, online gaming and virtual reality are powerful new technologies that promise to change our online experience. After summarizing advances in these hot technologies, we use the collective intelligence of our TechCast Experts to forecast the coming Internet that is likely to emerge from their application.

Here’s what learned:

Security May Arrive About 2027 We found a sharp division of opinion, with roughly half of our experts thinking there is little or no chance that the Internet would become secure — and the other half thinks there is about a 60% probability that blockchain and quantum cryptography will solve the problem at about 2027. After noting the success of Gilder’s previous forecasts, we tend to accept those who agree with Gilder.

Decentralization Likely About 2028–2030 We find some consensus around a 60% Probability and Most Likely Year About 2028–2030. The critical technologies are thought to focus on blockchain, but quantum, AI, biometrics and the Internet of things (IoT) also thought to offer localizing capabilities.

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Oct 10, 2020

New quantum computing algorithm skips past time limits imposed by decoherence

Posted by in categories: information science, quantum physics, supercomputing

This could be important!


A new algorithm that fast forwards simulations could bring greater use ability to current and near-term quantum computers, opening the way for applications to run past strict time limits that hamper many quantum calculations.

“Quantum computers have a limited time to perform calculations before their useful quantum nature, which we call coherence, breaks down,” said Andrew Sornborger of the Computer, Computational, and Statistical Sciences division at Los Alamos National Laboratory, and senior author on a paper announcing the research. “With a we have developed and tested, we will be able to fast forward quantum simulations to solve problems that were previously out of reach.”

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Oct 2, 2020

Finnish researchers claim quantum computing breakthrough

Posted by in categories: particle physics, quantum physics, supercomputing

Scientists have created a device which could make it easier to harness super-fast quantum computers for real-world applications, a team at Finland’s Aalto University said on Wednesday.

Quantum computers are a new generation of machines powered by energy transfers between so-called “”— a fraction of a millimetre across.

Scientists believe the devices will eventually be able to vastly outperform even the world’s most powerful conventional supercomputers.

Sep 19, 2020

A “Supercomputer” is Deciding the Politics of Australians

Posted by in categories: economics, supercomputing

By Taleed Brown

By decree of an anonymous university “supercomputer,” Victoria’s Dan Andrews has opted to extend stage 4 lockdowns. This is once again stalling the economic recovery of the region and plundering the wealth and liberty of millions across the state.

Sep 17, 2020

Physicists make electrical nanolasers even smaller

Posted by in categories: mobile phones, physics, supercomputing

Researchers from the Moscow Institute of Physics and Technology and King’s College London cleared the obstacle that had prevented the creation of electrically driven nanolasers for integrated circuits. The approach, reported in a recent paper in Nanophotonics, enables coherent light source design on the scale not only hundreds of times smaller than the thickness of a human hair but even smaller than the wavelength of light emitted by the laser. This lays the foundation for ultrafast optical data transfer in the manycore microprocessors expected to emerge in the near future.

Light signals revolutionized information technologies in the 1980s, when optical fibers started to replace copper wires, making data transmission orders of magnitude faster. Since optical communication relies on light— with a frequency of several hundred terahertz—it allows transferring terabytes of data every second through a single fiber, vastly outperforming electrical interconnects.

Fiber optics underlies the modern internet, but light could do much more for us. It could be put into action even inside the microprocessors of supercomputers, workstations, smartphones, and other devices. This requires using optical communication lines to interconnect the purely , such as processor cores. As a result, vast amounts of information could be transferred across the chip nearly instantaneously.

Sep 2, 2020

A Supercomputer Analyzed Covid-19 — and an Interesting New Theory Has Emerged

Posted by in categories: biotech/medical, supercomputing

Aug 28, 2020

Scientists use reinforcement learning to train quantum algorithm

Posted by in categories: chemistry, information science, quantum physics, robotics/AI, supercomputing

Recent advancements in quantum computing have driven the scientific community’s quest to solve a certain class of complex problems for which quantum computers would be better suited than traditional supercomputers. To improve the efficiency with which quantum computers can solve these problems, scientists are investigating the use of artificial intelligence approaches.

In a new study, scientists at the U.S. Department of Energy’s (DOE) Argonne National Laboratory have developed a based on reinforcement learning to find the optimal parameters for the Quantum Approximate Optimization Algorithm (QAOA), which allows a quantum computer to solve certain combinatorial problems such as those that arise in materials design, chemistry and wireless communications.

“Combinatorial optimization problems are those for which the solution space gets exponentially larger as you expand the number of decision variables,” said Argonne scientist Prasanna Balaprakash. “In one traditional example, you can find the shortest route for a salesman who needs to visit a few cities once by enumerating all possible routes, but given a couple thousand cities, the number of possible routes far exceeds the number of stars in the universe; even the fastest supercomputers cannot find the shortest route in a reasonable time.”

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