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Archive for the ‘supercomputing’ category

Jun 11, 2019

Let’s take an interstellar journey into a Black Hole

Posted by in categories: cosmology, space travel, supercomputing

This video shows what you will see if you fall into a black hole. It is not an artistic impression, but a result of general- relativistic supercomputer simulation by prof. Andrew Hamilton.

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Jun 4, 2019

Bill Gates, NEO, Gigafund backing Luminous in photonics supercomputer moonshot

Posted by in categories: finance, robotics/AI, supercomputing

Luminous Computing, a one-year-old startup, is aiming to build a photonics chip that will handle workloads needed for AI at the speed of light. It’s a moonshot and yet, the young company already has a number of high-profile investors willing to bet on the prospect.

The company has raised $9 million in a seed round led by Bill Gates, NEO’s Ali Partovi and Luke Nosek and Steve Oskoui of Gigafund.

The round also attracted other new investors, including Travis Kalanick’s fund 10100, BoxGroup, Uber CEO Dara Khosrowshahi, and Emil Michael as well as pre-seed investors Class 5 Global, Joshua Browder, Ozmen Ventures, Schox Investments and Third Kind Venture Capital.

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May 24, 2019

Tapping the power of AI and high-performance computing to extend evolution to superconductors

Posted by in categories: robotics/AI, supercomputing

Owners of thoroughbred stallions carefully breed prizewinning horses over generations to eke out fractions of a second in million-dollar races. Materials scientists have taken a page from that playbook, turning to the power of evolution and artificial selection to develop superconductors that can transmit electric current as efficiently as possible.

Perhaps counterintuitively, most applied can operate at high magnetic fields because they contain defects. The number, size, shape and position of the defects within a superconductor work together to enhance the carrying capacity in the presence of a magnetic field. Too many defects, however, can lead to blocking the electric current pathway or a breakdown of the superconducting material, so scientists need to be selective in how they incorporate defects into a material.

In a new study from the U.S. Department of Energy’s (DOE) Argonne National Laboratory, researchers used the power of artificial intelligence and high-performance supercomputers to introduce and assess the impact of different configurations of defects on the performance of a superconductor.

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May 17, 2019

HP Enterprise is acquiring supercomputing giant Cray

Posted by in categories: business, government, supercomputing

Hewlett Packard Enterprise (HPE) has a shiny new toy. The information technology firm announced today that is spending $1.3 billion to acquire supercomputer manufacturer Cray. HPE, which is a business-facing spin-off of the Hewlett Packard company, will instantly become a bigger presence in the world of academia and the federal government, where Cray has a number of significant contracts. It will also enable HPE to start selling supercomputer components to corporate clients and others.

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May 17, 2019

High School Student Uses AI to Detect Gravitational Waves

Posted by in categories: cosmology, education, physics, robotics/AI, supercomputing

Before he could legally drive, high school student Adam Rebei was already submitting jobs on the Blue Waters supercomputer at the National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign (NCSA) to run complex simulations of black holes.

“My first time using Blue Waters, we did a tour first and got to see the computer, which is a very amazing thing because it’s a very powerful machine,” Rebei told the NCSA, “and I just remember thinking, ‘All of the GPUs!’ It’s an insane amount of GPUs, and I’ve never seen anything like it.”

To get there, Rebei first took an astronomy class that led him to his work with the NCSA. Once there, he teamed up with research scientist Eliu Huerta, who leads the group’s Gravity Group.

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May 16, 2019

Researchers discover an unexpected phase transition in the high explosive TATB

Posted by in categories: evolution, particle physics, supercomputing

Lawrence Livermore National Laboratory (LLNL) scientists in collaboration with University of Nevada Las Vegas (UNLV) have discovered a previously unknown pressure induced phase transition for TATB that can help predict detonation performance and safety of the explosive. The research appears in the May 13 online edition of the Applied Physics Letters and it is highlighted as a cover and featured article.

1,3,5-Triamino-2,4,6- trinitrobenzene (TATB), the industry standard for an insensitive high explosive, stands out as the optimum choice when safety (insensitivity) is of utmost importance. Among similar materials with comparable explosive energy release, TATB is remarkably difficult to shock-initiate and has a low friction sensitivity. The causes of this unusual behavior are hidden in the high-pressure structural evolution of TATB. Supercomputer simulations of explosives detonating, running on the world’s most powerful machines at LLNL, depend on knowing the exact locations of the atoms in the crystal structure of an explosive. Accurate knowledge of atomic arrangement under pressure is the cornerstone for predicting the detonation performance and safety of an explosive.

The team performed experiments utilizing a diamond anvil cell, which compressed TATB single crystals to a pressure of more than 25 GPa (250,000 times atmospheric pressure). According to all previous experimental and theoretical studies, it was believed that the atomic arrangement in the crystal structure of TATB remains the same under pressure. The project team challenged the consensus in the field aiming to clarify the high-pressure structural behaviour of TATB.

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May 6, 2019

Razer Is Building a Toaster, Possibly With LED Support

Posted by in category: supercomputing

Razer is building a toaster. Mattel is probably building an exascale supercomputer. I hear Raytheon just got into baby toys. Dogs and cats, living together! Chaos reigns.

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May 6, 2019

MIT Cryptographers Are No Match For A Determined Belgian

Posted by in categories: robotics/AI, supercomputing

Twenty years ago, a cryptographic puzzle was included in the construction of a building on the MIT campus. The structure that houses what is now MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) includes a time capsule designed by the building’s architect, [Frank Gehry]. It contains artifacts related to the history of computing, and was meant to be opened whenever someone solved a cryptographic puzzle, or after 35 years had elapsed.

The puzzle was not expected to be solved early, but [Bernard Fabrot], a developer in Belgium, has managed it using not a supercomputer but a run-of-the-mill Intel i7 processor. The capsule will be opened later in May.

The famous cryptographer, [Ronald Rivest], put together what we now know is a deceptively simple challenge. It involves a successive squaring operation, and since it is inherently sequential there is no possibility of using parallel computing techniques to take any shortcuts. [Fabrot] used the GNU Multiple Precision Arithmetic Library in his code, and took over 3 years of computing time to solve it. Meanwhile another team is using an FPGA and are expecting a solution in months, though have been pipped to the post by the Belgian.

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Apr 25, 2019

A breakthrough in the study of laser/plasma interactions

Posted by in categories: biotech/medical, supercomputing

A new 3D particle-in-cell (PIC) simulation tool developed by researchers from Lawrence Berkeley National Laboratory and CEA Saclay is enabling cutting-edge simulations of laser/plasma coupling mechanisms that were previously out of reach of standard PIC codes used in plasma research. More detailed understanding of these mechanisms is critical to the development of ultra-compact particle accelerators and light sources that could solve long-standing challenges in medicine, industry, and fundamental science more efficiently and cost effectively.

In laser-plasma experiments such as those at the Berkeley Lab Laser Accelerator (BELLA) Center and at CEA Saclay—an international research facility in France that is part of the French Atomic Energy Commission—very large electric fields within plasmas that accelerate particle beams to over much shorter distances when compared to existing accelerator technologies. The long-term goal of these laser-plasma accelerators (LPAs) is to one day build colliders for high-energy research, but many spin offs are being developed already. For instance, LPAs can quickly deposit large amounts of energy into solid materials, creating dense plasmas and subjecting this matter to extreme temperatures and pressure. They also hold the potential for driving free-electron lasers that generate light pulses lasting just attoseconds. Such extremely short pulses could enable researchers to observe the interactions of molecules, atoms, and even subatomic particles on extremely short timescales.

Supercomputer simulations have become increasingly critical to this research, and Berkeley Lab’s National Energy Research Scientific Computing Center (NERSC) has become an important resource in this effort. By giving researchers access to physical observables such as particle orbits and radiated fields that are hard to get in experiments at extremely small time and length scales, PIC simulations have played a major role in understanding, modeling, and guiding high-intensity physics experiments. But a lack of PIC codes that have enough computational accuracy to model laser-matter interaction at ultra-high intensities has hindered the development of novel particle and light sources produced by this interaction.

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Apr 16, 2019

Optimizing network software to advance scientific discovery

Posted by in categories: mathematics, particle physics, supercomputing

High-performance computing (HPC)—the use of supercomputers and parallel processing techniques to solve large computational problems—is of great use in the scientific community. For example, scientists at the U.S. Department of Energy’s (DOE) Brookhaven National Laboratory rely on HPC to analyze the data they collect at the large-scale experimental facilities on site and to model complex processes that would be too expensive or impossible to demonstrate experimentally.

Modern science applications, such as simulating , often require a combination of aggregated computing power, high-speed networks for data transfer, large amounts of memory, and high-capacity storage capabilities. Advances in HPC hardware and software are needed to meet these requirements. Computer and computational scientists and mathematicians in Brookhaven Lab’s Computational Science Initiative (CSI) are collaborating with physicists, biologists, and other domain scientists to understand their data analysis needs and provide solutions to accelerate the scientific discovery process.

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