LBNL Develops Machine Learning Tool for Alloy Research

By John Russell

February 14, 2017

New and interesting uses for machine learning seem to arise daily. Researchers from Lawrence Berkeley National Laboratory recently trained an algorithm to predict structural characteristics of certain metal alloys that slashes computational power usually required for such calculations. The new approach is expected to accelerate research of new advanced alloys for applications spanning automotive to aerospace and much more.

Their work – Predicting defect behavior in B2 intermetallics by merging ab initio modeling and machine learning – is published in a recent issue of Nature Computational Materials. As an extension of this proof-of-concept work, an open source Python toolkit for modeling point defects in semiconductors and insulators (PyCDT) has been developed.

Traditionally, researchers have used a computational quantum mechanical method known as density functional calculations to predict what kinds of defects can be formed in a given structure and how they affect the material’s properties. This approach is computationally challenging and has limited its use, according to an article on the work posted on the NERSC site.

“Density functional calculations work well if you are modeling one small unit, but if you want to make your modeling cell bigger the computational power required to do this increases substantially,” says Bharat Medasani, a former Berkeley Lab postdoc and lead author of the paper. “And because it is computationally expensive to model defects in a single material, doing this kind of brute force modeling for tens of thousands of materials is not feasible.”

Medasani and his colleagues developed and trained machine learning algorithms to predict point defects in intermetallic compounds, focusing on the widely observed B2 crystal structure. Initially, they selected a sample of 100 of these compounds from the Materials Project Database and ran density functional calculations on supercomputers at the National Energy Research Scientific Computing Center (NERSC), a DOE Office of Science User Facility at Berkeley Lab, to identify their defects.

The overall result is it is no longer necessary to run costly first principle calculations to identify defect properties for every new metallic compound, say the researchers.

“This tool enables us to predict metallic defects faster and robustly, which will in turn accelerate materials design,” says Kristin Persson, a Berkeley Lab Scientist and Director of the Materials Project, an initiative aimed at drastically reducing the time needed to invent new materials by providing open web-based access to computed information on known and predicted materials.

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

Deep Learning at 15 PFlops Enables Training for Extreme Weather Identification at Scale

March 19, 2018

Petaflop per second deep learning training performance on the NERSC (National Energy Research Scientific Computing Center) Cori supercomputer has given climate scientists the ability to use machine learning to identify e Read more…

By Rob Farber

Mellanox Reacts to Activist Investor Pressures in Letter to Shareholders

March 16, 2018

Activist investor Starboard Value has been exerting pressure on Mellanox Technologies to increase its returns. In response, the high-performance networking company on Monday, March 12, published a letter to shareholders outlining its proposal for a May 2018 extraordinary general meeting (EGM) of shareholders and highlighting its long-term growth strategy and focus on operating margin improvement. Read more…

By Staff

Quantum Computing vs. Our ‘Caveman Newtonian Brain’: Why Quantum Is So Hard

March 15, 2018

Quantum is coming. Maybe not today, maybe not tomorrow, but soon enough. Within 10 to 12 years, we’re told, special-purpose quantum systems will enter the commercial realm. Assuming this happens, we can also assume that quantum will, over extended time, become increasingly general purpose as it delivers mind-blowing power. Read more…

By Doug Black

HPE Extreme Performance Solutions

Achieve Optimal Performance at Scale with High Performance Fabrics for HPC

High Performance Computing (HPC) is unlocking a new era of speed and productivity to fuel business transformation. Rapid advancements in HPC capabilities are helping organizations operate faster and more effectively than ever, but in today’s fast-paced marketplace, a new generation of technologies is required to reach greater scalability and cost-efficiency. Read more…

How the Cloud Is Falling Short for HPC

March 15, 2018

The last couple of years have seen cloud computing gradually build some legitimacy within the HPC world, but still the HPC industry lies far behind enterprise IT in its willingness to outsource computational power. The m Read more…

By Chris Downing

Deep Learning at 15 PFlops Enables Training for Extreme Weather Identification at Scale

March 19, 2018

Petaflop per second deep learning training performance on the NERSC (National Energy Research Scientific Computing Center) Cori supercomputer has given climate Read more…

By Rob Farber

How the Cloud Is Falling Short for HPC

March 15, 2018

The last couple of years have seen cloud computing gradually build some legitimacy within the HPC world, but still the HPC industry lies far behind enterprise I Read more…

By Chris Downing

Stephen Hawking, Legendary Scientist, Dies at 76

March 14, 2018

Stephen Hawking passed away at his home in Cambridge, England, in the early morning of March 14; he was 76. Born on January 8, 1942, Hawking was an English theo Read more…

By Tiffany Trader

Hyperion Tackles Elusive Quantum Computing Landscape

March 13, 2018

Quantum computing - exciting and off-putting all at once - is a kaleidoscope of technology and market questions whose shapes and positions are far from settled. Read more…

By John Russell

Part Two: Navigating Life Sciences Choppy HPC Waters in 2018

March 8, 2018

2017 was not necessarily the best year to build a large HPC system for life sciences say Ari Berman, VP and GM of consulting services, and Aaron Gardner, direct Read more…

By John Russell

Google Chases Quantum Supremacy with 72-Qubit Processor

March 7, 2018

Google pulled ahead of the pack this week in the race toward "quantum supremacy," with the introduction of a new 72-qubit quantum processor called Bristlecone. Read more…

By Tiffany Trader

SciNet Launches Niagara, Canada’s Fastest Supercomputer

March 5, 2018

SciNet and the University of Toronto today unveiled "Niagara," Canada's most-powerful supercomputer, comprising 1,500 dense Lenovo ThinkSystem SD530 high-perfor Read more…

By Tiffany Trader

Part One: Deep Dive into 2018 Trends in Life Sciences HPC

March 1, 2018

Life sciences is an interesting lens through which to see HPC. It is perhaps not an obvious choice, given life sciences’ relative newness as a heavy user of H Read more…

By John Russell

Inventor Claims to Have Solved Floating Point Error Problem

January 17, 2018

"The decades-old floating point error problem has been solved," proclaims a press release from inventor Alan Jorgensen. The computer scientist has filed for and Read more…

By Tiffany Trader

Japan Unveils Quantum Neural Network

November 22, 2017

The U.S. and China are leading the race toward productive quantum computing, but it's early enough that ultimate leadership is still something of an open questi Read more…

By Tiffany Trader

Researchers Measure Impact of ‘Meltdown’ and ‘Spectre’ Patches on HPC Workloads

January 17, 2018

Computer scientists from the Center for Computational Research, State University of New York (SUNY), University at Buffalo have examined the effect of Meltdown Read more…

By Tiffany Trader

IBM Begins Power9 Rollout with Backing from DOE, Google

December 6, 2017

After over a year of buildup, IBM is unveiling its first Power9 system based on the same architecture as the Department of Energy CORAL supercomputers, Summit a Read more…

By Tiffany Trader

Fast Forward: Five HPC Predictions for 2018

December 21, 2017

What’s on your list of high (and low) lights for 2017? Volta 100’s arrival on the heels of the P100? Appearance, albeit late in the year, of IBM’s Power9? Read more…

By John Russell

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

Russian Nuclear Engineers Caught Cryptomining on Lab Supercomputer

February 12, 2018

Nuclear scientists working at the All-Russian Research Institute of Experimental Physics (RFNC-VNIIEF) have been arrested for using lab supercomputing resources to mine crypto-currency, according to a report in Russia’s Interfax News Agency. Read more…

By Tiffany Trader

Chip Flaws ‘Meltdown’ and ‘Spectre’ Loom Large

January 4, 2018

The HPC and wider tech community have been abuzz this week over the discovery of critical design flaws that impact virtually all contemporary microprocessors. T Read more…

By Tiffany Trader

Leading Solution Providers

GlobalFoundries, Ayar Labs Team Up to Commercialize Optical I/O

December 4, 2017

GlobalFoundries (GF) and Ayar Labs, a startup focused on using light, instead of electricity, to transfer data between chips, today announced they've entered in Read more…

By Tiffany Trader

How Meltdown and Spectre Patches Will Affect HPC Workloads

January 10, 2018

There have been claims that the fixes for the Meltdown and Spectre security vulnerabilities, named the KPTI (aka KAISER) patches, are going to affect applicatio Read more…

By Rosemary Francis

Perspective: What Really Happened at SC17?

November 22, 2017

SC is over. Now comes the myriad of follow-ups. Inboxes are filled with templated emails from vendors and other exhibitors hoping to win a place in the post-SC thinking of booth visitors. Attendees of tutorials, workshops and other technical sessions will be inundated with requests for feedback. Read more…

By Andrew Jones

V100 Good but not Great on Select Deep Learning Aps, Says Xcelerit

November 27, 2017

Wringing optimum performance from hardware to accelerate deep learning applications is a challenge that often depends on the specific application in use. A benc Read more…

By John Russell

Lenovo Unveils Warm Water Cooled ThinkSystem SD650 in Rampup to LRZ Install

February 22, 2018

This week Lenovo took the wraps off the ThinkSystem SD650 high-density server with third-generation direct water cooling technology developed in tandem with par Read more…

By Tiffany Trader

AMD Wins Another: Baidu to Deploy EPYC on Single Socket Servers

December 13, 2017

When AMD introduced its EPYC chip line in June, the company said a portion of the line was specifically designed to re-invigorate a single socket segment in wha Read more…

By John Russell

World Record: Quantum Computer with 46 Qubits Simulated

December 18, 2017

Scientists from the Jülich Supercomputing Centre have set a new world record. Together with researchers from Wuhan University and the University of Groningen, Read more…

New Blueprint for Converging HPC, Big Data

January 18, 2018

After five annual workshops on Big Data and Extreme-Scale Computing (BDEC), a group of international HPC heavyweights including Jack Dongarra (University of Te Read more…

By John Russell

  • arrow
  • Click Here for More Headlines
  • arrow
Share This