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Primeur weekly 2019-09-02

Quantum computing

DOE announces $21,4 million for quantum information science research ...

Quantum criticality could be a boon for qubit designers ...

DOE announces $60,7 million to advance quantum computing and networking ...

Atos delivers Quantum-Learning-as-a-Service to Xofia to enable artificial intelligence solutions ...

Entanglement sent over 50 km of optical fiber ...

Focus on Europe

MIPT physicists create device for imitating biological memory ...

Supercomputer Puhti at CSC Finland is now available for researchers ...

Hardware

Micron and WekaIO win Best of Show Award at the Flash Memory Summit 2019 ...

Tachyum joins CXL High-Speed Interconnect Consortium to advance breakthrough data centre performance ...

OSNEXUS announces QuantaStor 5.4 featuring scale-out NAS, IBM Key Protect integration, and storage firewall management ...

DIY: How to build a supercomputer ...

NVIDIA vComputeServer with NGC containers brings GPU virtualization to AI, Deep Learning and Data Science ...

Mellanox works with VMware and NVIDIA to enable high performance virtualized machine learning solutions ...

Mellanox introduces revolutionary ConnectX-6 Dx and BlueField-2 secure Cloud SmartNICs and I/O Processing Unit solutions ...

New modular supercomputing facility opens at NASA's Ames Research Center ...

Supermicro extends vSAN system portfolio for hyper-converged infrastructure and launches new high-performance vSAN solution ...

Applications

IBM gives artificial intelligence computing at MIT a lift ...

Break in temporal symmetry produces molecules that can encode information ...

Smarter experiments for faster materials discovery ...

Seagate and UC Santa Cruz collaboration poised to accelerate genomics data analysis ...

ORNL-Veterans Affiars collaboration targets veteran suicide epidemic ...

Messi versus Ronaldo: who's the GOAT? Computer model may help to settle the debate ...

Supercomputers pave the way for new machine learning approach ...

Altair expands AI data science solutions ...

The Cloud

Supercomputing in the Open Telekom Cloud ...

Supercomputers pave the way for new machine learning approach


New deep learning models predict the interactions between atoms in organic molecules. These models, which were generated using supercomputers at the San Diego Supercomputer Center and the Los Alamos National Laboratory, help computational biologists and drug development researchers better understand and treat disease. Credit: Los Alamos National Laboratory.
28 Aug 2019 San Diego - According to a release issued by the Los Alamos National Laboratory (LANL), researchers have developed a machine learning approach called transfer learning that lets them model novel materials by learning from data collected about millions of other compounds. The new approach can be applied to new molecules in milliseconds, enabling research into a far greater number of compounds over much longer timescales.

The new technique, called ANI-1ccx potential, promises to advance the capabilities of researchers in many fields and improve the accuracy of machine learning-based potentials in future studies of metal alloys and detonation physics.

"Our quantum mechanical calculations to create ANI-1ccx potential were conducted over two years with time split on the Comet supercomputer at the San Diego Supercomputer Center and the ­­­Badger supercomputer at LANL", stated Olexandr Isayev, paper author and a pharmacy professor at the University of North Carolina at Chapel Hill. "We chose these two supercomputers to train our neural networks as there are few machines that can run these - due to the high memory and core requirements."

Olexandr Isayev and colleagues from the University of Florida and LANL recently published their research in aNature Communicationspaper called " Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning ". The paper details how quantum mechanical (QM) algorithms, used on classical computers, can accurately describe the mechanical motions of a compound in its operational environment.

However, QM scales very poorly with varying molecular sizes, severely limiting the scope of possible simulations. Even a slight increase in molecular size within a simulation can dramatically increase the computational burden. So practitioners often resort to using empirical information, which describes the motion of atoms in terms of classical physics and Newton's Laws, enabling simulations that scale to billions of atoms or millions of chemical compounds.

Traditionally, similar models have had to strike a trade-off between accuracy and transferability. When the many parameters of the potential are finely tuned for one compound, the accuracy decreases on other compounds.

"This means we can now model materials and molecular dynamics billions of times faster compared to conventional quantum methods, while retaining the same level of accuracy", explained Justin Smith, LANL Physicist and Metropolis Fellow in the laboratory's Theoretical Division. Understanding how molecules move is critical to tapping their potential value for drug development, protein simulations and reactive chemistry, for example, and both quantum mechanics and experimental (empirical) methods feed into the simulations.

The researchers acknowledge support of the U.S. Department of Energy (DOE) and the National Science Foundation (NSF) grants CHE-1802789 and CHE-1802831. The authors also acknowledge Extreme Science and Engineering Discovery Environment (XSEDE) award DMR110088, which is supported by NSF grant ACI-1053575. This research in part was done using resources provided by the Open Science Grid, which is supported by NSF award 1148698 and the U.S. DOE Office of Science.
Source: San Diego Supercomputer Center - SDSC

Back to Table of contents

Primeur weekly 2019-09-02

Quantum computing

DOE announces $21,4 million for quantum information science research ...

Quantum criticality could be a boon for qubit designers ...

DOE announces $60,7 million to advance quantum computing and networking ...

Atos delivers Quantum-Learning-as-a-Service to Xofia to enable artificial intelligence solutions ...

Entanglement sent over 50 km of optical fiber ...

Focus on Europe

MIPT physicists create device for imitating biological memory ...

Supercomputer Puhti at CSC Finland is now available for researchers ...

Hardware

Micron and WekaIO win Best of Show Award at the Flash Memory Summit 2019 ...

Tachyum joins CXL High-Speed Interconnect Consortium to advance breakthrough data centre performance ...

OSNEXUS announces QuantaStor 5.4 featuring scale-out NAS, IBM Key Protect integration, and storage firewall management ...

DIY: How to build a supercomputer ...

NVIDIA vComputeServer with NGC containers brings GPU virtualization to AI, Deep Learning and Data Science ...

Mellanox works with VMware and NVIDIA to enable high performance virtualized machine learning solutions ...

Mellanox introduces revolutionary ConnectX-6 Dx and BlueField-2 secure Cloud SmartNICs and I/O Processing Unit solutions ...

New modular supercomputing facility opens at NASA's Ames Research Center ...

Supermicro extends vSAN system portfolio for hyper-converged infrastructure and launches new high-performance vSAN solution ...

Applications

IBM gives artificial intelligence computing at MIT a lift ...

Break in temporal symmetry produces molecules that can encode information ...

Smarter experiments for faster materials discovery ...

Seagate and UC Santa Cruz collaboration poised to accelerate genomics data analysis ...

ORNL-Veterans Affiars collaboration targets veteran suicide epidemic ...

Messi versus Ronaldo: who's the GOAT? Computer model may help to settle the debate ...

Supercomputers pave the way for new machine learning approach ...

Altair expands AI data science solutions ...

The Cloud

Supercomputing in the Open Telekom Cloud ...