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  • richardmitnick 1:17 pm on May 9, 2018 Permalink | Reply
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    From Argonne National Laboratory ALCF: “E3SM provides powerful, new Earth system model for supercomputers” 

    Argonne Lab
    News from Argonne National Laboratory

    From Argonne National Laboratory ALCF

    May 8, 2018
    Andrea Manning

    1
    Argonne scientists helped create a comprehensive new model that draws on supercomputers to simulate how various aspects of the Earth — its atmosphere, oceans, land, ice — move. This earth simulation project emerged from Argonne and other U.S. DOE national laboratories, including Brookhaven, Lawrence Livermore, Lawrence Berkeley, Los Alamos, Oak Ridge, Pacific Northwest, and Sandia, as well as several universities. Credit: E3SM.org

    The Earth — with its myriad shifting atmospheric, oceanic, land, and ice components — presents an extraordinarily complex system to simulate using computer models.

    But a new Earth modeling system, the Energy Exascale Earth System Model (E3SM), is now able to capture and simulate all these components together. Released on April 23, after four years of development, E3SM features weather-scale resolution — i.e., enough detail to capture fronts, storms, and hurricanes — and uses advanced computers to simulate aspects of the Earth’s variability. The system can help researchers anticipate decadal-scale changes that could influence the U.S. energy sector in years to come.

    The E3SM project is supported by the U.S. Department of Energy’s (DOE) Office of Biological and Environmental Research. “One of E3SM’s purposes is to help ensure that DOE’s climate mission can be met — including on future exascale systems,” said Robert Jacob, a computational climate scientist in the Environmental Science division of DOE’s Argonne National Laboratory and one of 15 project co-leaders.

    To support this mission, the project’s goal is to develop an Earth system model that increases prediction reliability. This objective has historically been limited by constraints in computing technologies and uncertainties in theory and observations. Enhancing prediction reliability requires advances on two frontiers: (1) improved simulation of Earth system processes by developing new models of physical processes, increasing model resolution, and enhancing computational performance; and (2) representing the two-way interactions between human activities and natural processes more realistically, especially where these interactions affect U.S. energy needs.

    “This model adds a much more complete representation between interactions of the energy system and the Earth system,” said David Bader, a computational scientist at Lawrence Livermore National Laboratory and overall E3SM project lead. “With this new system, we’ll be able to more realistically simulate the present, which gives us more confidence to simulate the future.”

    The long view

    Simulating the Earth involves solving approximations of physical, chemical, and biological governing equations on spatial grids at the highest resolutions possible.

    In fact, increasing the number of Earth-system days simulated per day of computing time at varying levels of resolution is so important that it is a prerequisite for achieving the E3SM project goal. The new release can simulate 10 years of the Earth system in one day at low resolution or one year of the Earth system at high resolution in one day (a sample movie is available at the project website). The goal is for E3SM to support simulation of five years of the Earth system on a single computing day at its highest possible resolution by 2021.

    This objective underscores the project’s heavy emphasis on both performance and infrastructure — two key areas of strength for Argonne. “Our researchers have been active in ensuring that the model performs well with many threads,” said Jacob, who will lead the infrastructure group in Phase II, which — with E3SM’s initial release — starts on July 1. Singling out the threading expertise of performance engineer Azamat Mametjanov of Argonne’s Mathematics and Computer Science division, Jacob continued: “We’ve been running and testing on Theta, our new 10-petaflops system at the Argonne Leadership Computing Facility, and will conduct some of the high-res simulations on that platform.”

    Researchers using the E3SM can employ variable resolution on all model components (atmosphere, ocean, land, ice), allowing them to focus computing power on fine-scale processes in different regions. The software uses advanced mesh-designs that smoothly taper the grid-scale from the coarser outer region to the more refined region.

    Adapting for exascale

    E3SM’s developers — more than 100 scientists and software engineers — have a longer-term aim: to use the exascale machines that the DOE Advanced Scientific Computing Research Office expects to procure over the next five years. Thus, E3SM development is proceeding in tandem with the Exascale Computing Initiative. (Exascale refers to a computing system capable of carrying out a billion [1018] calculations per second — a thousand-fold increase in performance over the most advanced computers from a decade ago.)

    Another key focus will be on software engineering, which includes all of the processes for developing the model; designing the tests; and developing the required infrastructure, including input/output libraries and software for coupling the models. E3SM uses Argonne’s Model Coupling Toolkit (MCT), as do other leading climate models (e.g., Community Earth System Model [CESM]) to couple the atmosphere, ocean, and other submodels. (A new version of MCT [2.10] was released along with E3SM.)

    Additional Argonne-specific contributions in Phase II will center on:

    Crop modeling: Efforts will focus on better emulating crops such as corn, wheat, and soybeans, which will improve simulated influences of crops on carbon, nutrient, energy, and water cycles, as well as capturing the implications of human-Earth system interactions
    Dust and aerosols: These play a major role in the atmosphere, radiation, and clouds, as well as various chemical cycles.

    Collaboration among – and beyond – national laboratories

    The E3SM project has involved researchers at multiple DOE laboratories including Argonne, Brookhaven, Lawrence Livermore, Lawrence Berkeley, Los Alamos, Oak Ridge, Pacific Northwest, and Sandia national laboratories, as well as several universities.

    The project also benefits from collaboration within DOE, including with the Exascale Computing Project and programs in Scientific Discovery through Advanced Computing, Climate Model Development and Validation, Atmospheric Radiation Measurement, Program for Climate Model Diagnosis and Intercomparison, International Land Model Benchmarking Project, Community Earth System Model, and Next-Generation Ecosystem Experiments for the Arctic and the Tropics.

    The code is available on GitHub, the host for the project’s open-source repository. For additional information, visit the E3SM website: http://e3sm.org.

    ANL ALCF Cetus IBM supercomputer

    ANL ALCF Theta Cray supercomputer

    ANL ALCF Cray Aurora supercomputer

    ANL ALCF MIRA IBM Blue Gene Q supercomputer at the Argonne Leadership Computing Facility

    See the full article here .

    Please help promote STEM in your local schools.
    STEM Icon
    Stem Education Coalition

    Argonne National Laboratory seeks solutions to pressing national problems in science and technology. The nation’s first national laboratory, Argonne conducts leading-edge basic and applied scientific research in virtually every scientific discipline. Argonne researchers work closely with researchers from hundreds of companies, universities, and federal, state and municipal agencies to help them solve their specific problems, advance America’s scientific leadership and prepare the nation for a better future. With employees from more than 60 nations, Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science. For more visit http://www.anl.gov.

    About ALCF

    The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing facilities in partnership with the computational science community.

    We help researchers solve some of the world’s largest and most complex problems with our unique combination of supercomputing resources and expertise.

    ALCF projects cover many scientific disciplines, ranging from chemistry and biology to physics and materials science. Examples include modeling and simulation efforts to:

    Discover new materials for batteries
    Predict the impacts of global climate change
    Unravel the origins of the universe
    Develop renewable energy technologies

    Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science

    Argonne Lab Campus

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  • richardmitnick 11:21 am on May 2, 2018 Permalink | Reply
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    From Argonne National Laboratory ALCF: “ALCF supercomputers advance earthquake modeling efforts” 

    Argonne Lab
    News from Argonne National Laboratory

    ALCF

    May 1, 2018
    John Spizzirri

    Southern California defines cool. The perfect climes of San Diego, the glitz of Hollywood, the magic of Disneyland. The geology is pretty spectacular, as well.

    “Southern California is a prime natural laboratory to study active earthquake processes,” says Tom Jordan, a professor in the Department of Earth Sciences at the University of Southern California (USC). “The desert allows you to observe the fault system very nicely.”

    The fault system to which he is referring is the San Andreas, among the more famous fault systems in the world. With roots deep in Mexico, it scars California from the Salton Sea in the south to Cape Mendocino in the north, where it then takes a westerly dive into the Pacific.

    Situated as it is at the heart of the San Andreas Fault System, Southern California does make an ideal location to study earthquakes. That it is home to nearly 24-million people makes for a more urgent reason to study them.

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    San Andreas Fault System. Aerial photo of San Andreas Fault looking northwest onto the Carrizo Plain with Soda Lake visible at the upper left. John Wiley User:Jw4nvcSanta Barbara, California

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    USGS diagram of San Andreas Fault. http://nationalatlas.gov/articles/geology/features/sanandreas.html

    Jordan and a team from the Southern California Earthquake Center (SCEC) are using the supercomputing resources of the Argonne Leadership Computing Facility (ALCF), a U.S. Department of Energy Office of Science User Facility, to advance modeling for the study of earthquake risk and how to reduce it.

    Headquartered at USC, the center is one of the largest collaborations in geoscience, engaging over 70 research institutions and 1,000 investigators from around the world.

    The team relies on a century’s worth of data from instrumental records as well as regional and seismic national hazard models to develop new tools for understanding earthquake hazards. Working with the ALCF, they have used this information to improve their earthquake rupture simulator, RSQSim.

    RSQ is a reference to rate- and state-dependent friction in earthquakes — a friction law that can be used to study the nucleation, or initiation, of earthquakes. RSQSim models both nucleation and rupture processes to understand how earthquakes transfer stress to other faults.

    ALCF staff were instrumental in adapting the code to Mira, the facility’s 10-petaflops supercomputer, to allow for the larger simulations required to model earthquake behaviors in very complex fault systems, like San Andreas, and which led to the team’s biggest discovery.

    Shake, rattle, and code

    The SCEC, in partnership with the U.S. Geological Survey, had already developed the Uniform California Earthquake Rupture Forecast (UCERF), an empirically based model that integrates theory, geologic information, and geodetic data, like GPS displacements, to determine spatial relationships between faults and slippage rates of the tectonic plates that created those faults.

    Though more traditional, the newest version, UCERF3, is considered the best representation of California earthquake ruptures, but the picture it portrays is still not as accurate as researchers would hope.

    “We know a lot about how big earthquakes can be, how frequently they occur, and where they occur, but we cannot predict them precisely in time,” notes Jordan.

    The team turned to Mira to run RSQSim to determine whether they could achieve more accurate results more quickly. A physics-based code, RSQSim produces long-term synthetic earthquake catalogs that comprise dates, times, locations, and magnitudes for predicted events.

    Using simulation, researchers impose stresses upon some representation of a fault system, which changes the stress throughout much of the system and thus changes the way future earthquakes occur. Trying to model these powerful stress-mediated interactions is particularly difficult with complex systems and faults like San Andreas.

    “We just let the system evolve and create earthquake catalogs for a hundred thousand or a million years. It’s like throwing a grain of sand in a set of cogs to see what happens,” explains Christine Goulet, a team member and executive science director for special projects with SCEC.

    The end result is a more detailed picture of the possible hazard, which forecasts a sequence of earthquakes of various magnitudes expected to occur on the San Andreas Fault over a given time range.

    The group tried to calibrate RSQSim’s numerous parameters to replicate UCERF3, but eventually decided to run the code with its default parameters. While the initial intent was to evaluate the magnitude of differences between the models, they discovered, instead, that both models agreed closely on their forecasts of future seismologic activity.

    “So it was an a-ha moment. Eureka,” recalls Goulet. “The results were a surprise because the group had thought carefully about optimizing the parameters. The decision not to change them from their default values made for very nice results.”

    The researchers noted that the mutual validation of the two approaches could prove extremely productive in further assessing seismic hazard estimates and their uncertainties.

    Information derived from the simulations will help the team compute the strong ground motions generated by faulting that occurs at the surface — the characteristic shaking that is synonymous with earthquakes. To do this, the team couples the earthquake rupture forecasts, UCERF and RSQSim, with different models that represent the way waves propagate through the system. Called ground motion prediction equations, these are standard equations used by engineers to calculate the shaking levels from earthquakes of different sizes and locations.

    One of those models is the dynamic rupture and wave propagation code Waveqlab3D (Finite Difference Quake and Wave Laboratory 3D), which is the focus of the SCEC team’s current ALCF allocation.

    “These experiments show that the physics-based model RSQSim can replicate the seismic hazard estimates derived from the empirical model UCERF3, but with far fewer statistical assumptions,” notes Jordan. “The agreement gives us more confidence that the seismic hazard models for California are consistent with what we know about earthquake physics. We can now begin to use these physics to improve the hazard models.”

    This project was awarded computing time and resources at the ALCF through DOE’s Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program. The team’s research is also supported by the National Science Foundation, the U.S. Geological Survey, and the W.M. Keck Foundation.

    ANL ALCF Cetus IBM supercomputer

    ANL ALCF Theta Cray supercomputer

    ANL ALCF Cray Aurora supercomputer

    ANL ALCF MIRA IBM Blue Gene Q supercomputer at the Argonne Leadership Computing Facility

    See the full article here .

    Earthquake Alert

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    Earthquake Alert

    Earthquake Network projectEarthquake Network is a research project which aims at developing and maintaining a crowdsourced smartphone-based earthquake warning system at a global level. Smartphones made available by the population are used to detect the earthquake waves using the on-board accelerometers. When an earthquake is detected, an earthquake warning is issued in order to alert the population not yet reached by the damaging waves of the earthquake.

    The project started on January 1, 2013 with the release of the homonymous Android application Earthquake Network. The author of the research project and developer of the smartphone application is Francesco Finazzi of the University of Bergamo, Italy.

    Get the app in the Google Play store.

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    Smartphone network spatial distribution (green and red dots) on December 4, 2015

    Meet The Quake-Catcher Network

    QCN bloc

    Quake-Catcher Network

    The Quake-Catcher Network is a collaborative initiative for developing the world’s largest, low-cost strong-motion seismic network by utilizing sensors in and attached to internet-connected computers. With your help, the Quake-Catcher Network can provide better understanding of earthquakes, give early warning to schools, emergency response systems, and others. The Quake-Catcher Network also provides educational software designed to help teach about earthquakes and earthquake hazards.

    After almost eight years at Stanford, and a year at CalTech, the QCN project is moving to the University of Southern California Dept. of Earth Sciences. QCN will be sponsored by the Incorporated Research Institutions for Seismology (IRIS) and the Southern California Earthquake Center (SCEC).

    The Quake-Catcher Network is a distributed computing network that links volunteer hosted computers into a real-time motion sensing network. QCN is one of many scientific computing projects that runs on the world-renowned distributed computing platform Berkeley Open Infrastructure for Network Computing (BOINC).

    The volunteer computers monitor vibrational sensors called MEMS accelerometers, and digitally transmit “triggers” to QCN’s servers whenever strong new motions are observed. QCN’s servers sift through these signals, and determine which ones represent earthquakes, and which ones represent cultural noise (like doors slamming, or trucks driving by).

    There are two categories of sensors used by QCN: 1) internal mobile device sensors, and 2) external USB sensors.

    Mobile Devices: MEMS sensors are often included in laptops, games, cell phones, and other electronic devices for hardware protection, navigation, and game control. When these devices are still and connected to QCN, QCN software monitors the internal accelerometer for strong new shaking. Unfortunately, these devices are rarely secured to the floor, so they may bounce around when a large earthquake occurs. While this is less than ideal for characterizing the regional ground shaking, many such sensors can still provide useful information about earthquake locations and magnitudes.

    USB Sensors: MEMS sensors can be mounted to the floor and connected to a desktop computer via a USB cable. These sensors have several advantages over mobile device sensors. 1) By mounting them to the floor, they measure more reliable shaking than mobile devices. 2) These sensors typically have lower noise and better resolution of 3D motion. 3) Desktops are often left on and do not move. 4) The USB sensor is physically removed from the game, phone, or laptop, so human interaction with the device doesn’t reduce the sensors’ performance. 5) USB sensors can be aligned to North, so we know what direction the horizontal “X” and “Y” axes correspond to.

    If you are a science teacher at a K-12 school, please apply for a free USB sensor and accompanying QCN software. QCN has been able to purchase sensors to donate to schools in need. If you are interested in donating to the program or requesting a sensor, click here.

    BOINC is a leader in the field(s) of Distributed Computing, Grid Computing and Citizen Cyberscience.BOINC is more properly the Berkeley Open Infrastructure for Network Computing, developed at UC Berkeley.

    Earthquake safety is a responsibility shared by billions worldwide. The Quake-Catcher Network (QCN) provides software so that individuals can join together to improve earthquake monitoring, earthquake awareness, and the science of earthquakes. The Quake-Catcher Network (QCN) links existing networked laptops and desktops in hopes to form the worlds largest strong-motion seismic network.

    Below, the QCN Quake Catcher Network map
    QCN Quake Catcher Network map

    ShakeAlert: An Earthquake Early Warning System for the West Coast of the United States

    The U. S. Geological Survey (USGS) along with a coalition of State and university partners is developing and testing an earthquake early warning (EEW) system called ShakeAlert for the west coast of the United States. Long term funding must be secured before the system can begin sending general public notifications, however, some limited pilot projects are active and more are being developed. The USGS has set the goal of beginning limited public notifications in 2018.

    Watch a video describing how ShakeAlert works in English or Spanish.

    The primary project partners include:

    United States Geological Survey
    California Governor’s Office of Emergency Services (CalOES)
    California Geological Survey
    California Institute of Technology
    University of California Berkeley
    University of Washington
    University of Oregon
    Gordon and Betty Moore Foundation

    The Earthquake Threat

    Earthquakes pose a national challenge because more than 143 million Americans live in areas of significant seismic risk across 39 states. Most of our Nation’s earthquake risk is concentrated on the West Coast of the United States. The Federal Emergency Management Agency (FEMA) has estimated the average annualized loss from earthquakes, nationwide, to be $5.3 billion, with 77 percent of that figure ($4.1 billion) coming from California, Washington, and Oregon, and 66 percent ($3.5 billion) from California alone. In the next 30 years, California has a 99.7 percent chance of a magnitude 6.7 or larger earthquake and the Pacific Northwest has a 10 percent chance of a magnitude 8 to 9 megathrust earthquake on the Cascadia subduction zone.

    Part of the Solution

    Today, the technology exists to detect earthquakes, so quickly, that an alert can reach some areas before strong shaking arrives. The purpose of the ShakeAlert system is to identify and characterize an earthquake a few seconds after it begins, calculate the likely intensity of ground shaking that will result, and deliver warnings to people and infrastructure in harm’s way. This can be done by detecting the first energy to radiate from an earthquake, the P-wave energy, which rarely causes damage. Using P-wave information, we first estimate the location and the magnitude of the earthquake. Then, the anticipated ground shaking across the region to be affected is estimated and a warning is provided to local populations. The method can provide warning before the S-wave arrives, bringing the strong shaking that usually causes most of the damage.

    Studies of earthquake early warning methods in California have shown that the warning time would range from a few seconds to a few tens of seconds. ShakeAlert can give enough time to slow trains and taxiing planes, to prevent cars from entering bridges and tunnels, to move away from dangerous machines or chemicals in work environments and to take cover under a desk, or to automatically shut down and isolate industrial systems. Taking such actions before shaking starts can reduce damage and casualties during an earthquake. It can also prevent cascading failures in the aftermath of an event. For example, isolating utilities before shaking starts can reduce the number of fire initiations.

    System Goal

    The USGS will issue public warnings of potentially damaging earthquakes and provide warning parameter data to government agencies and private users on a region-by-region basis, as soon as the ShakeAlert system, its products, and its parametric data meet minimum quality and reliability standards in those geographic regions. The USGS has set the goal of beginning limited public notifications in 2018. Product availability will expand geographically via ANSS regional seismic networks, such that ShakeAlert products and warnings become available for all regions with dense seismic instrumentation.

    Current Status

    The West Coast ShakeAlert system is being developed by expanding and upgrading the infrastructure of regional seismic networks that are part of the Advanced National Seismic System (ANSS); the California Integrated Seismic Network (CISN) is made up of the Southern California Seismic Network, SCSN) and the Northern California Seismic System, NCSS and the Pacific Northwest Seismic Network (PNSN). This enables the USGS and ANSS to leverage their substantial investment in sensor networks, data telemetry systems, data processing centers, and software for earthquake monitoring activities residing in these network centers. The ShakeAlert system has been sending live alerts to “beta” users in California since January of 2012 and in the Pacific Northwest since February of 2015.

    In February of 2016 the USGS, along with its partners, rolled-out the next-generation ShakeAlert early warning test system in California joined by Oregon and Washington in April 2017. This West Coast-wide “production prototype” has been designed for redundant, reliable operations. The system includes geographically distributed servers, and allows for automatic fail-over if connection is lost.

    This next-generation system will not yet support public warnings but does allow selected early adopters to develop and deploy pilot implementations that take protective actions triggered by the ShakeAlert notifications in areas with sufficient sensor coverage.

    Authorities

    The USGS will develop and operate the ShakeAlert system, and issue public notifications under collaborative authorities with FEMA, as part of the National Earthquake Hazard Reduction Program, as enacted by the Earthquake Hazards Reduction Act of 1977, 42 U.S.C. §§ 7704 SEC. 2.

    For More Information

    Robert de Groot, ShakeAlert National Coordinator for Communication, Education, and Outreach
    rdegroot@usgs.gov
    626-583-7225

    Learn more about EEW Research

    ShakeAlert Fact Sheet

    ShakeAlert Implementation Plan

    Please help promote STEM in your local schools.
    STEM Icon
    Stem Education Coalition

    Argonne National Laboratory seeks solutions to pressing national problems in science and technology. The nation’s first national laboratory, Argonne conducts leading-edge basic and applied scientific research in virtually every scientific discipline. Argonne researchers work closely with researchers from hundreds of companies, universities, and federal, state and municipal agencies to help them solve their specific problems, advance America’s scientific leadership and prepare the nation for a better future. With employees from more than 60 nations, Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science. For more visit http://www.anl.gov.

    About ALCF

    The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing facilities in partnership with the computational science community.

    We help researchers solve some of the world’s largest and most complex problems with our unique combination of supercomputing resources and expertise.

    ALCF projects cover many scientific disciplines, ranging from chemistry and biology to physics and materials science. Examples include modeling and simulation efforts to:

    Discover new materials for batteries
    Predict the impacts of global climate change
    Unravel the origins of the universe
    Develop renewable energy technologies

    Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science

    Argonne Lab Campus

     
  • richardmitnick 1:39 pm on October 31, 2017 Permalink | Reply
    Tags: ANL-ALCF, , , , ,   

    From ALCF: “The inner secrets of planets and stars” 

    Argonne Lab
    News from Argonne National Laboratory

    ALCF

    October 31, 2017
    Jim Collins

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    Top image: As part of the team’s research on Jupiter’s dynamo, they performed planetary atmospheric dynamics simulations of rotating, deep convection in a 3D spherical shell, with shallow stable stratification. This image is a snapshot from a video that shows the evolution of radial vorticity near the outer boundary from a north polar perspective view. Intense anticyclones (blue) drift westward and undergo multiple mergers, while the equatorial jet flows rapidly to the east. Displayed simulation time and radial vorticity in units of planetary rotation (radial vorticity of 2 is equal to the planetary rotation rate). The video, which shows over 5,300 planetary rotations, can be viewed here: https://www.youtube.com/watch?v=OUICRNiFhpU. (Credit: Moritz Heimpel, University of Alberta)

    Middle image: A 3D rendering of simulated solar convection realized at different rotation rates. Regions of upflow and downflow are rendered in red and blue, respectively. As rotational influence increases from left (non-rotating) to right (rapidly-rotating), convective patterns become increasingly more organized and elongated (Featherstone & Hindman, 2016, ApJ Letters, 830 L15). Understanding the Sun’s location along this spectrum represents a major step toward understanding how it sustains a magnetic field. (Credit: Nick Featherstone and Bradley Hindman, University of Colorado Boulder)

    Bottom image: Radial velocity field (red = positive; blue = negative) on the equatorial plane of a numerical simulation of Earth’s core dynamo. These small-scale convective flows generate a strong planetary-scale magnetic field. (Credit: Rakesh Yadav, Harvard University)

    Using Argonne’s Mira supercomputer, researchers are developing advanced models to study magnetic field generation on the Earth, Jupiter, and the Sun at an unprecedented level of detail. A better understanding of this process will provide new insights into the birth and evolution of the solar system.

    After a five-year, 1.74 billion-mile journey, NASA’s Juno spacecraft entered Jupiter’s orbit in July 2016, to begin its mission to collect data on the structure, atmosphere, and magnetic and gravitational fields of the mysterious planet.

    NASA/Juno

    For UCLA geophysicist Jonathan Aurnou, the timing could not have been much better.

    Just as Juno reached its destination, Aurnou and his colleagues from the Computational Infrastructure for Geodynamics (CIG) had begun carrying out massive 3D simulations at the Argonne Leadership Computing Facility (ALCF), a U.S. Department of Energy (DOE) Office of Science User Facility, to model and predict the turbulent interior processes that produce Jupiter’s intense magnetic field.

    While the timing of the two research efforts was coincidental, it presents an opportunity to compare the most detailed Jupiter observations ever captured with the highest-resolution Jupiter simulations ever performed.

    Aurnou, lead of the CIG’s Geodynamo Working Group, hopes that the advanced models they are creating with Mira, the ALCF’s 10-petaflops supercomputer, will complement the NASA probe’s findings to reveal a full understanding of the Jupiter’s internal dynamics.

    “Even with Juno, we’re not going to be able to get a great physical sampling of the turbulence occurring in Jupiter’s deep interior,” he said. “Only a supercomputer can help get us under that lid. Mira is allowing us to develop some of the most accurate models of turbulence possible in extremely remote astrophysical settings.”

    But Aurnou and his collaborators are not just looking at Jupiter. Their three-year ALCF project also is using Mira to develop models to study magnetic field generation on the Earth and the Sun at an unprecedented level of detail.

    Dynamic dynamos

    Magnetic fields are generated deep in the cores of planets and stars by a process known as dynamo action. This phenomenon occurs when the rotating, convective motion of electrically conducting fluids (e.g., liquid metal in planets and plasma in stars) converts kinetic energy into magnetic energy. A better understanding of the dynamo process will provide new insights into the birth and evolution of the solar system, and shed light on planetary systems being discovered around other stars.

    Modeling the internal dynamics of Jupiter, the Earth, and the Sun all bring unique challenges, but the three vastly different astrophysical bodies do share one thing in common—simulating their extremely complex dynamo processes requires a massive amount of computing power.

    To date, dynamo models have been unable to accurately simulate turbulence in fluids similar to those found in planets and stars. Conventional models also are unable to resolve the broad range of spatial scales present in turbulent dynamo action. However, the continued advances in computing hardware and software are now allowing researchers to overcome such limitations.

    With their project at the ALCF, the CIG team set out to develop and demonstrate high-resolution 3D dynamo models at the largest scale possible. Using Rayleigh, an open-source code designed to study magnetohydrodynamic convection in spherical geometries, they have been able to resolve a range of spatial scales previously inaccessible to numerical simulation.

    While the code transitioned to Mira’s massively parallel architecture smoothly, Rayleigh’s developer, Nick Featherstone, worked with ALCF computational scientist Wei Jiang to achieve optimal performance on the system. Their work included redesigning Rayleigh’s initialization phase to make it run up to 10 times faster, and rewriting parts of the code to make use of a hybrid MPI/OpenMP programming model that performs about 20 percent better than the original MPI version.

    “We did the coding and porting, but running it properly on a supercomputer is a whole different thing,” said Featherstone, a researcher from the University of Colorado Boulder. “The ALCF has done a lot of performance analysis for us. They just really made sure we’re running as well as we can run.”

    Stellar research

    When the project began in 2015, the team’s primary focus was the Sun. An understanding of the solar dynamo is key to predicting solar flares, coronal mass ejections, and other drivers of space weather, which can impact the performance and reliability of space-borne and ground-based technological systems, such as satellite-based communications.

    “We’re really trying to get at the linchpin that is stopping progress on understanding how the Sun generates its magnetic field,” said Featherstone, who is leading the project’s solar dynamo research. “And that is determining the typical flow speed of plasmas in the region of convection.”

    The team began by performing 3D stellar convection simulations of a non-rotating star to fine-tune parameters so that their calculations were on a trajectory similar to observations of flow structures on the Sun’s surface. Next, they incorporated rotation into the simulations, which allowed them to begin making meaningful comparisons against observations. This led to a paper in The Astrophysical Journal Letters last year, in which the researchers were able to place upper bounds on the typical flow speed in the solar convection zone.

    The team’s research also shed light on a mysterious observation that has puzzled scientists for decades. The Sun’s visible surface is covered with patches of convective bubbles, known as granules, which cluster into groups that are about 30,000 kilometers across, known as supergranules. Many scientists have theorized that the clustering should exist on even larger scales, but Featherstone’s simulations suggest that rotation may be the reason the clusters are smaller than expected.

    “These patches of convection are the surface signature of dynamics taking place deep in the Sun’s interior,” he said. “With Mira, we’re starting to show that this pattern we see on the surface results naturally from flows that are slower than we expected, and their interaction with rotation.”

    According to Featherstone, these new insights were enabled by their model’s ability to simulate rotation and the Sun’s spherical shape, which were too computationally demanding to incorporate in previous modeling efforts.

    “To study the deep convection zone, you need the sphere,” he said. “And to get it right, it needs to be rotating.

    Getting to the core of planets

    Magnetic field generation in terrestrial planets like Earth is driven by the physical properties of their liquid metal cores. However, due to limited computing power, previous Earth dynamo models have been forced to simulate fluids with electrical conductivities that far exceed that of actual liquid metals.

    To overcome this issue, the CIG team is building a high-resolution model that is capable of simulating the metallic properties of Earth’s molten iron core. Their ongoing geodynamo simulations are already showing that flows and coupled magnetic structures develop on both small and large scales, revealing new magnetohydrodynamic processes that do not appear in lower resolution computations.

    “If you can’t simulate a realistic metal, you’re going to have trouble simulating turbulence accurately,” Aurnou said. “Nobody could afford to do this computationally, until now. So, a big driver for us is to open the door to the community and provide a concrete example of what is possible with today’s fastest supercomputers.”

    In Jupiter’s case, the team’s ultimate goal is to create a coupled model that accounts for both its dynamo region and its powerful atmospheric winds, known as jets. This involves developing a “deep atmosphere” model in which Jupiter’s jet region extends all the way through the planet and connects to the dynamo region.

    Thus far, the researchers have made significant progress with the atmospheric model, enabling the highest-resolution giant-planet simulations yet achieved. The Jupiter simulations will be used to make detailed predictions of surface vortices, zonal jet flows, and thermal emissions that will be compared to observational data from the Juno mission.

    Ultimately, the team plans to make their results publicly available to the broader research community.

    “You can almost think of our computational efforts like a space mission,” Aurnou said. “Just like the Juno spacecraft, Mira is a unique and special device. When we get datasets from these amazing scientific tools, we want to make them openly available and put them out to the whole community to look at in different ways.”

    This project was awarded computing time and resources at the ALCF through the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program supported by DOE’s Office of Science. The development of the Rayleigh code was funded by CIG, which is supported by the National Science Foundation.

    ANL ALCF Cetus IBM supercomputer

    ANL ALCF Theta Cray supercomputer

    ANL ALCF Cray Aurora supercomputer

    ANL ALCF MIRA IBM Blue Gene Q supercomputer at the Argonne Leadership Computing Facility

    See the full article here .

    Please help promote STEM in your local schools.
    STEM Icon
    Stem Education Coalition

    Argonne National Laboratory seeks solutions to pressing national problems in science and technology. The nation’s first national laboratory, Argonne conducts leading-edge basic and applied scientific research in virtually every scientific discipline. Argonne researchers work closely with researchers from hundreds of companies, universities, and federal, state and municipal agencies to help them solve their specific problems, advance America’s scientific leadership and prepare the nation for a better future. With employees from more than 60 nations, Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science. For more visit http://www.anl.gov.

    About ALCF

    The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing facilities in partnership with the computational science community.

    We help researchers solve some of the world’s largest and most complex problems with our unique combination of supercomputing resources and expertise.

    ALCF projects cover many scientific disciplines, ranging from chemistry and biology to physics and materials science. Examples include modeling and simulation efforts to:

    Discover new materials for batteries
    Predict the impacts of global climate change
    Unravel the origins of the universe
    Develop renewable energy technologies

    Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science

    Argonne Lab Campus

     
  • richardmitnick 11:23 am on October 9, 2017 Permalink | Reply
    Tags: ANL-ALCF, , , , , , ,   

    From Science Node: “US Coalesces Plans for First Exascale Supercomputer: Aurora in 2021” 

    Science Node bloc
    Science Node

    September 27, 2017
    Tiffany Trader

    ANL ALCF Cray Aurora supercomputer

    At the Advanced Scientific Computing Advisory Committee (ASCAC) meeting, in Arlington, Va., yesterday (Sept. 26), it was revealed that the “Aurora” supercomputer is on track to be the United States’ first exascale system. Aurora, originally named as the third pillar of the CORAL “pre-exascale” project, will still be built by Intel and Cray for Argonne National Laboratory, but the delivery date has shifted from 2018 to 2021 and target capability has been expanded from 180 petaflops to 1,000 petaflops (1 exaflop).

    2

    The fate of the Argonne Aurora “CORAL” supercomputer has been in limbo since the system failed to make it into the U.S. DOE budget request, while the same budget proposal called for an exascale machine “of novel architecture” to be deployed at Argonne in 2021.

    Until now, the only official word from the U.S. Exascale Computing Project was that Aurora was being “reviewed for changes and would go forward under a different timeline.”

    Officially, the contract has been “extended,” and not cancelled, but the fact remains that the goal of the Collaboration of Oak Ridge, Argonne, and Lawrence Livermore (CORAL) initiative to stand up two distinct pre-exascale architectures was not met.

    According to sources we spoke with, a number of people at the DOE are not pleased with the Intel/Cray (Intel is the prime contractor, Cray is the subcontractor) partnership. It’s understood that the two companies could not deliver on the 180-200 petaflops system by next year, as the original contract called for. Now Intel/Cray will push forward with an exascale system that is some 50x larger than any they have stood up.

    It’s our understanding that the cancellation of Aurora is not a DOE budgetary measure as has been speculated, and that the DOE and Argonne wanted Aurora. Although it was referred to as an “interim,” or “pre-exascale” machine, the scientific and research community was counting on that system, was eager to begin using it, and they regarded it as a valuable system in its own right. The non-delivery is regarded as disruptive to the scientific/research communities.

    Another question we have is that since Intel/Cray failed to deliver Aurora, and have moved on to a larger exascale system contract, why hasn’t their original CORAL contract been cancelled and put out again to bid?

    With increased global competitiveness, it seems that the DOE stakeholders did not want to further delay the non-IBM/Nvidia side of the exascale track. Conceivably, they could have done a rebid for the Aurora system, but that would leave them with an even bigger gap if they had to spin up a new vendor/system supplier to replace Intel and Cray.

    Starting the bidding process over again would delay progress toward exascale – and it might even have been the death knell for exascale by 2021, but Intel and Cray now have a giant performance leap to make and three years to do it. There is an open question on the processor front as the retooled Aurora will not be powered by Phi/Knights Hill as originally proposed.

    These events beg the question regarding the IBM-led effort and whether IBM/Nvidia/Mellanox are looking very good by comparison. The other CORAL thrusts — Summit at Oak Ridge and Sierra at Lawrence Livermore — are on track, with Summit several weeks ahead of Sierra, although it is looking like neither will make the cut-off for entry onto the November Top500 list as many had speculated.

    ORNL IBM Summit supercomputer depiction

    LLNL IBM Sierra supercomputer

    We reached out to representatives from Cray, Intel and the Exascale Computing Project (ECP) seeking official comment on the revised Aurora contract. Cray and Intel declined to comment and we did not hear back from ECP by press time. We will update the story as we learn more.

    See the full article here .

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    Stem Education Coalition

    Science Node is an international weekly online publication that covers distributed computing and the research it enables.

    “We report on all aspects of distributed computing technology, such as grids and clouds. We also regularly feature articles on distributed computing-enabled research in a large variety of disciplines, including physics, biology, sociology, earth sciences, archaeology, medicine, disaster management, crime, and art. (Note that we do not cover stories that are purely about commercial technology.)

    In its current incarnation, Science Node is also an online destination where you can host a profile and blog, and find and disseminate announcements and information about events, deadlines, and jobs. In the near future it will also be a place where you can network with colleagues.

    You can read Science Node via our homepage, RSS, or email. For the complete iSGTW experience, sign up for an account or log in with OpenID and manage your email subscription from your account preferences. If you do not wish to access the website’s features, you can just subscribe to the weekly email.”

     
  • richardmitnick 8:17 am on October 7, 2017 Permalink | Reply
    Tags: ANL-ALCF, , , Leaning into the supercomputing learning curve,   

    From ALCF: “Leaning into the supercomputing learning curve” 

    Argonne Lab
    News from Argonne National Laboratory

    ALCF

    ANL ALCF Cetus IBM supercomputer

    ANL ALCF Theta Cray supercomputer

    ANL ALCF Cray Aurora supercomputer

    ANL ALCF MIRA IBM Blue Gene Q supercomputer at the Argonne Leadership Computing Facility

    1
    Recently, 70 scientists — graduate students, computational scientists, and postdoctoral and early-career researchers — attended the fifth annual Argonne Training Program on Extreme-Scale Computing (ATPESC) in St. Charles, Illinois. Over two weeks, they learned how to seize opportunities offered by the world’s fastest supercomputers. Credit: Image by Argonne National Laboratory

    October 6, 2017
    Andrea Manning

    What would you do with a supercomputer that is at least 50 times faster than today’s fastest machines? For scientists and engineers, the emerging age of exascale computing opens a universe of possibilities to simulate experiments and analyze reams of data — potentially enabling, for example, models of atomic structures that lead to cures for disease.

    But first, scientists need to learn how to seize this opportunity, which is the mission of the Argonne Training Program on Extreme-Scale Computing (ATPESC). The training is part of the Exascale Computing Project, a collaborative effort of the U.S. Department of Energy’s (DOE) Office of Science and its National Nuclear Security Administration.

    Starting in late July, 70 participants — graduate students, computational scientists, and postdoctoral and early-career researchers — gathered at the Q Center in St. Charles, Illinois, for the program’s fifth annual training session. This two-week course is designed to teach scientists key skills and tools and the most effective ways to use leading-edge supercomputers to further their research aims.

    This year’s ATPESC agenda once again was packed with technical lectures, hands-on exercises and dinner talks.

    “Supercomputers are extremely powerful research tools for a wide range of science domains,” said ATPESC program director Marta García, a computational scientist at the Argonne Leadership Computing Facility (ALCF), a DOE Office of Science User Facility at the department’s Argonne National Laboratory.

    “But using them efficiently requires a unique skill set. With ATPESC, we aim to touch on all of the key skills and approaches a researcher needs to take advantage of the world’s most powerful computing systems.”

    To address all angles of high-performance computing, the training focuses on programming methodologies that are effective across a variety of supercomputers — and that are expected to apply to exascale systems. Renowned scientists, high-performance computing experts and other leaders in the field served as lecturers and guided the hands-on sessions.

    This year, experts covered:

    Hardware architectures
    Programming models and languages
    Data-intensive computing, input/output (I/O) and machine learning
    Numerical algorithms and software for extreme-scale science
    Performance tools and debuggers
    Software productivity
    Visualization and data analysis

    In addition, attendees tapped hundreds of thousands of cores of computing power on some of today’s most powerful supercomputing resources, including the ALCF’s Mira, Cetus, Vesta, Cooley and Theta systems; the Oak Ridge Leadership Computing Facility’s Titan system; and the National Energy Research Scientific Computing Center’s Cori and Edison systems – all DOE Office of Science User Facilities.

    “I was looking at how best to optimize what I’m currently using on these new architectures and also figure out where things are going,” said Justin Walker, a Ph.D. student in the University of Wisconsin-Madison’s Physics Department. “ATPESC delivers on instructing us on a lot of things.”

    Shikhar Kumar, Ph.D. candidate in nuclear science and engineering at the Massachusetts Institute of Technology, elaborates: “On the issue of I/O, data processing, data visualization and performance tools, there isn’t a single option that is regarded as the ‘industry standard.’ Instead, we learned about many of the alternatives, which encourages learning high-performance computing from the ground up.”

    “You can’t get this material out of a textbook,” said Eric Nielsen, a research scientist at NASA’s Langley Research Center. Added Johann Dahm of IBM Research, “I haven’t had this material presented to me in this sort of way ever.”

    Jonathan Hoy, a Ph.D. student at the University of Southern California, pointed to the larger, “ripple effect” role of this type of gathering: “It is good to have all these people sit down together. In a way, we’re setting standards here.”

    Lisa Goodenough, a postdoctoral researcher in high energy physics at Argonne, said: “The theme has been about barriers coming down.” Goodenough referred to both barriers to entry and training barriers hindering scientists from realizing scientific objectives.

    “The program was of huge benefit for my postdoctoral researcher,” said Roseanna Zia, assistant professor of chemical engineering at Stanford University. “Without the financial assistance, it would have been out of my reach,” she said, highlighting the covered tuition fees, domestic airfare, meals and lodging.

    Now, anyone can learn from the program’s broad curriculum, including the slides and videos of the lectures from some of the world’s foremost experts in extreme-scale computing, online — underscoring program organizers’ efforts to extend its reach beyond the classroom. The slides and the videos of the lectures captured at ATPESC 2017 are now available online at: http://extremecomputingtraining.anl.gov/2017-slides and http://extremecomputingtraining.anl.gov/2017-videos, respectively.

    For more information on ATPESC, including on applying for selection to attend next year’s program, visit http://extremecomputingtraining.anl.gov.

    The Exascale Computing Project is a collaborative effort of two DOE organizations — the Office of Science and the National Nuclear Security Administration. As part of President Obama’s National Strategic Computing initiative, ECP was established to develop a capable exascale ecosystem, encompassing applications, system software, hardware technologies and architectures and workforce development to meet the scientific and national security mission needs of DOE in the mid-2020s timeframe.

    See the full article here .

    Please help promote STEM in your local schools.
    STEM Icon
    Stem Education Coalition

    Argonne National Laboratory seeks solutions to pressing national problems in science and technology. The nation’s first national laboratory, Argonne conducts leading-edge basic and applied scientific research in virtually every scientific discipline. Argonne researchers work closely with researchers from hundreds of companies, universities, and federal, state and municipal agencies to help them solve their specific problems, advance America’s scientific leadership and prepare the nation for a better future. With employees from more than 60 nations, Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science. For more visit http://www.anl.gov.

    About ALCF

    The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing facilities in partnership with the computational science community.

    We help researchers solve some of the world’s largest and most complex problems with our unique combination of supercomputing resources and expertise.

    ALCF projects cover many scientific disciplines, ranging from chemistry and biology to physics and materials science. Examples include modeling and simulation efforts to:

    Discover new materials for batteries
    Predict the impacts of global climate change
    Unravel the origins of the universe
    Develop renewable energy technologies

    Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science

    Argonne Lab Campus

     
  • richardmitnick 2:39 pm on July 3, 2017 Permalink | Reply
    Tags: ANL-ALCF, , Argonne's Theta supercomputer goes online, ,   

    From ALCF: “Argonne’s Theta supercomputer goes online” 

    Argonne Lab
    News from Argonne National Laboratory

    ALCF

    ANL ALCF Cetus IBM supercomputer

    ANL ALCF Theta Cray supercomputer

    ANL ALCF Cray Aurora supercomputer

    ANL ALCF MIRA IBM Blue Gene Q supercomputer at the Argonne Leadership Computing Facility

    July 3, 2017
    Laura Wolf

    Theta, a new production supercomputer located at the U.S. Department of Energy’s Argonnne National Laboratory is officially open to the research community. The new machine’s massively parallel, many-core architecture continues Argonne’s leadership computing program towards its future Aurora system.

    Theta was built onsite at the Argonne Leadership Computing Facility (ALCF), a DOE Office of Science User Facility, where it will operate alongside Mira, an IBM Blue Gene/Q supercomputer. Both machines are fully dedicated to supporting a wide range of scientific and engineering research campaigns. Theta, an Intel-Cray system, entered production on July 1.

    The new supercomputer will immediately begin supporting several 2017-2018 DOE Advanced Scientific Computing Research (ASCR) Leadership Computing Challenge (ALCC) projects. The ALCC is a major allocation program that supports scientists from industry, academia, and national laboratories working on advancements in targeted DOE mission areas. Theta will also support projects from the ALCF Data Science Program, ALCF’s discretionary award program, and, eventually, the DOE’s Innovative and Novel Computing Computational Impact on Theory and Experiment (INCITE) program—the major means by which the scientific community gains access to the DOE’s fastest supercomputers dedicated to open science.

    Designed in collaboration with Intel and Cray, Theta is a 9.65-petaflops system based on the second-generation Intel Xeon Phi processor and Cray’s high-performance computing software stack. Capable of nearly 10 quadrillion calculations per second, Theta will enable researchers to break new ground in scientific investigations that range from modeling the inner workings of the brain to developing new materials for renewable energy applications.

    “Theta’s unique architectural features represent a new and exciting era in simulation science capabilities,” said ALCF Director of Science Katherine Riley. “These same capabilities will also support data-driven and machine-learning problems, which are increasingly becoming significant drivers of large-scale scientific computing.”

    Now that Theta is available as a production resource, researchers can apply for computing time through the facility’s various allocation programs. Although the INCITE and ALCC calls for proposals recently closed, researchers can apply for Director’s Discretionary awards at any time.

    See the full article here .

    Please help promote STEM in your local schools.
    STEM Icon
    Stem Education Coalition

    Argonne National Laboratory seeks solutions to pressing national problems in science and technology. The nation’s first national laboratory, Argonne conducts leading-edge basic and applied scientific research in virtually every scientific discipline. Argonne researchers work closely with researchers from hundreds of companies, universities, and federal, state and municipal agencies to help them solve their specific problems, advance America’s scientific leadership and prepare the nation for a better future. With employees from more than 60 nations, Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science. For more visit http://www.anl.gov.

    About ALCF

    The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing facilities in partnership with the computational science community.

    We help researchers solve some of the world’s largest and most complex problems with our unique combination of supercomputing resources and expertise.

    ALCF projects cover many scientific disciplines, ranging from chemistry and biology to physics and materials science. Examples include modeling and simulation efforts to:

    Discover new materials for batteries
    Predict the impacts of global climate change
    Unravel the origins of the universe
    Develop renewable energy technologies

    Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science

    Argonne Lab Campus

     
  • richardmitnick 12:37 pm on July 1, 2017 Permalink | Reply
    Tags: Advanced Scientific Computing Research (ASCR), ALCC program awards ALCF computing time to 24 projects, ANL-ALCF, Theta Early Science Program   

    From ALCF: “ALCC program awards ALCF computing time to 24 projects” 

    Argonne Lab
    News from Argonne National Laboratory

    ANL ALCF Cray Aurora supercomputer

    ANL ALCF Theta Cray supercomputer

    ANL ALCF MIRA IBM Blue Gene Q supercomputer at the Argonne Leadership Computing Facility

    ALCF

    ALCC program awards ALCF computing time to 24 projects

    June 26, 2017
    No writer credit found

    1
    For one of the 2017-2018 ALCC projects, Argonne physicist Katrin Heitmann will use ALCF computing resources to continue work to build a suite of multi-wavelength, multi-cosmology synthetic sky maps. The left image (red) shows the baryonic density in a large cluster of galaxies, while the right image (blue) shows the dark matter content in the same cluster.

    The U.S. Department of Energy’s (DOE’s) ASCR Leadership Computing Challenge (ALCC) has awarded 24 projects a total of 2.1 billion core-hours at the Argonne Leadership Computing Facility (ALCF). The one-year awards are set to begin July 1.

    Several of the 2017-2018 ALCC projects will be the first to run on the ALCF’s new 9.65 petaflops Intel-Cray supercomputer, Theta, when it opens to the full user community July 1.

    Projects in the Theta Early Science Program performed science simulations on the system, but those runs served a dual purpose of helping to stress-test and evaluate Theta’s capabilities.

    Each year, the ALCC program selects projects with an emphasis on high-risk, high-payoff simulations in areas directly related to the DOE mission and for broadening the community of researchers capable of using leadership computing resources.

    Managed by the Advanced Scientific Computing Research (ASCR) program within DOE’s Office of Science, the ALCC program provides awards of computing time that range from a few million to several-hundred-million core-hours to researchers from industry, academia, and government agencies. These allocations support work at the ALCF, the Oak Ridge Leadership Computing Facility (OLCF),

    and the National Energy Research Scientific Computing Center (NERSC),

    all DOE Office of Science User Facilities.

    In 2017, the ALCC program awarded 40 projects totaling 4.1 billion core-hours across the three ASCR facilities. Additional projects may be announced at a later date as ALCC proposals can be submitted throughout the year.

    The 24 projects awarded time at the ALCF are noted below. Some projects received additional computing time at OLCF and/or NERSC.

    Thomas Blum from University of Connecticut received 220 million core-hours for “Hadronic Light-by-Light Scattering and Vacuum Polarization Contributions to the Muon Anomalous Magnetic Moment from Lattice QCD with Chiral Fermions.”
    Choong-Seock Chang from Princeton Plasma Physics Laboratory [PPPL] received 80 million core-hours for “High-Fidelity Gyrokinetic Study of Divertor Heat-Flux Width and Pedestal Structure.”
    John T. Childers from Argonne National Laboratory received 58 million core-hours for “Simulating Particle Interactions and the Resulting Detector Response at the LHC and Fermilab.”
    Frederico Fiuza from SLAC National Accelerator Laboratory [SLAC][ received 50 million core-hours for “Studying Astrophysical Particle Acceleration in HED Plasmas.”
    Marco Govoni from Argonne National Laboratory received 60 million core- hours for “Computational Engineering of Electron-Vibration Coupling Mechanisms.”
    William Gustafson from Pacific Northwest National Laboratory [PNNL] received 74 million core-hours for “Large-Eddy Simulation Component of the Mesoscale Convective System Climate Model Development and Validation (CMDV-MCS) Project.”
    Olle Heinonen from Argonne National Laboratory received 5 million core-hours for “Quantum Monte Carlo Computations of Chemical Systems.”
    Katrin Heitmann from Argonne National Laboratory received 40 million core-hours for “Extreme-Scale Simulations for Multi-Wavelength Cosmology Investigations.”
    Phay Ho from Argonne National Laboratory received 68 million core-hours for “Imaging Transient Structures in Heterogeneous Nanoclusters in Intense X-ray Pulses.”
    George Karniadakis from Brown University received 20 million core-hours for “Multiscale Simulations of Hematological Disorders.”
    Daniel Livescu from Los Alamos National Laboratory [LANL] received 60 million core-hours for “Non-Boussinesq Effects on Buoyancy-Driven Variable Density Turbulence.”
    Alessandro Lovato from Argonne National Laboratory received 35 million core-hours for “Nuclear Spectra with Chiral Forces.”
    Elia Merzari from Argonne National Laboratory received 85 million core-hours for “High-Fidelity Numerical Simulation of Wire-Wrapped Fuel Assemblies.”
    Paul Messina from Argonne National Laboratory received 530 million core-hours for “ECP Consortium for Exascale Computing.”
    Aleksandr Obabko from Argonne National Laboratory received 50 million core-hours for “Numerical Simulation of Turbulent Flows in Advanced Steam Generators – Year 3.”
    Mark Petersen from Los Alamos National Laboratory received 25 million core-hours for “Understanding the Role of Ice Shelf-Ocean Interactions in a Changing Global Climate.”
    Benoit Roux from the University of Chicago received 80 million core-hours for “Protein-Protein Recognition and HPC Infrastructure.”
    Emily Shemon from Argonne National Laboratory received 44 million core-hours for “Elimination of Modeling Uncertainties through High-Fidelity Multiphysics Simulation to Improve Nuclear Reactor Safety and Economics.”
    J. Ilja Siepmann from University of Minnesota received 130 million core-hours for “Predictive Modeling of Functional Nanoporous Materials, Nanoparticle Assembly, and Reactive Systems.”
    Tjerk Straatsma from Oak Ridge National Laboratory [ORNL] received 20 million core-hours for “Portable Application Development for Next-Generation Supercomputer Architectures.”
    Sergey Syritsyn from RIKEN BNL Research Center received 135 million core-hours for “Nucleon Structure and Electric Dipole Moments with Physical Chirally-Symmetric Quarks.”
    Sergey Varganov from University of Nevada, Reno received 42 million core-hours for “Spin-Forbidden Catalysis on Metal-Sulfur Proteins.”
    Robert Voigt from Leidos received 110 million core-hours for “Demonstration of the Scalability of Programming Environments By Simulating Multi-Scale Applications.”
    Brian Wirth from Oak Ridge National Laboratory received 98 million core-hours for “Modeling Helium-Hydrogen Plasma Mediated Tungsten Surface Response to Predict Fusion Plasma Facing Component Performance.”

    See the full article here .

    Please help promote STEM in your local schools.
    STEM Icon
    Stem Education Coalition

    Argonne National Laboratory seeks solutions to pressing national problems in science and technology. The nation’s first national laboratory, Argonne conducts leading-edge basic and applied scientific research in virtually every scientific discipline. Argonne researchers work closely with researchers from hundreds of companies, universities, and federal, state and municipal agencies to help them solve their specific problems, advance America’s scientific leadership and prepare the nation for a better future. With employees from more than 60 nations, Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science. For more visit http://www.anl.gov.

    About ALCF

    The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing facilities in partnership with the computational science community.

    We help researchers solve some of the world’s largest and most complex problems with our unique combination of supercomputing resources and expertise.

    ALCF projects cover many scientific disciplines, ranging from chemistry and biology to physics and materials science. Examples include modeling and simulation efforts to:

    Discover new materials for batteries
    Predict the impacts of global climate change
    Unravel the origins of the universe
    Develop renewable energy technologies

    Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science

    Argonne Lab Campus

     
  • richardmitnick 8:33 pm on June 2, 2017 Permalink | Reply
    Tags: ANL-ALCF, , ,   

    From ALCF: “ALCF workshop prepares researchers for Theta, Mira” 

    Argonne Lab
    News from Argonne National Laboratory

    ANL Cray Aurora supercomputer
    Cray Aurora supercomputer at the Argonne Leadership Computing Facility

    MIRA IBM Blue Gene Q supercomputer at the Argonne Leadership Computing Facility
    MIRA IBM Blue Gene Q supercomputer at the Argonne Leadership Computing Facility

    ALCF

    June 1, 2017
    Jim Collins

    1
    More than 60 researchers attended the 2017 ALCF Computational Performance Workshop to work directly with ALCF staff and invited experts to test, debug, and optimize their applications on the facility’s supercomputers.

    For most supercomputer users, running science simulations on a leading-edge system for the first time requires more than just a how-to guide.

    “There are special tools and techniques you need to know to take full advantage of these massive supercomputers,” said Sean Dettrick, lead computational scientist at Tri Alpha Energy, a California-based company pursuing the development of clean fusion energy technology.

    Dettrick was one of the more than 60 researchers who attended the Argonne Leadership Computing Facility’s (ALCF) Computational Performance Workshop from May 2-5, 2017, for guidance on preparing and improving their codes for ALCF supercomputers, including Theta, the facility’s new 9.65 petaflops Intel-Cray system.

    1
    ANL ALCF Theta 9.65 petaflop Intel-Cray supercomputer

    Every year, the ALCF hosts an intensive, hands-on workshop to connect both current and prospective users with the experts who know the systems inside out—ALCF computational scientists, performance engineers, data scientists, and visualization experts, as well as invited guests from Intel, Cray, Allinea (now part of ARM), ParaTools (TAU), and Rice University (HPCToolkit). With dedicated access to ALCF computing resources, the workshop provides an opportunity for attendees to work directly with these experts to test, debug, and optimize their applications on leadership-class supercomputers.

    “The workshop is designed to help participants take their code performance to a higher level and get them computationally ready to pursue large-scale science projects on our systems,” said Ray Loy, the ALCF’s lead for training, debuggers, and math libraries. “This year, we had the added attraction of Theta, which previously had only been available to users in the Early Science Program.”

    Theta will be opened up to the broader user community when it enters production mode on July 1, 2017. The new system will be available to researchers awarded projects through the 2017-2018 ASCR Leadership Computing Challenge (ALCC) and the 2018 Innovative and Novel Computational Impact on Theory and Experiment (INCITE) programs. One of the ALCF workshop’s goals is to help researchers demonstrate code scalability for INCITE and ALCC project proposals, which are required to convey both scientific merit and computational readiness.

    For Dettrick and his colleagues, the workshop presented an opportunity to begin preparing for Theta. The team currently has a small Director’s Discretionary project at the ALCF, but they have their sights set on applying for a larger allocation through the INCITE program in the future.

    “Our company has an in-house computing cluster that is like training wheels for the large supercomputers available here,” said Dettrick. “By moving some of our modeling work to ALCF systems, our goal is to inform and expedite our experimental research efforts by carrying out larger simulations more quickly.”

    Working with ALCF staff members, the Tri Alpha Energy researchers were able to compile and run two plasma simulation codes on Theta. In the process, they worked with an Intel representative to use the Intel VTune performance profiler to identify and address some performance and scalability issues. The ALCF team suggested a number of strategies to improve threading of the codes and reduce I/O time on Theta.

    “This experience definitely planted some seeds in my mind about how we can improve productivity moving forward,” Dettrick said.

    Mark Kostuk, a mathematical modeler and optimizer from General Atomics’ Magnetic Fusion Energy Division, also brought a plasma code to the workshop to prepare for a future INCITE award. Initially, Kostuk encountered several intermittent run failures on Theta.

    He was able to overcome the issue by working with several of the on-site experts. Using the Allinea DDT Debugger, they identified one of the issues—memory errors that were appearing in calls to a math library. The collaborative effort continued into the following week, allowing Kostuk to pinpoint and fix the bug causing the run failures.

    “It really worked out great. I received a lot of hands-on help with the code,” Kostuk said. “Once we resolved the issues, I was able to run a significant set of benchmarks and scaling tests as part of our preparations for INCITE.”

    In addition to the hands-on sessions, the ALCF workshop featured talks on the facility’s system architectures, performance tools, optimization techniques, and data science capabilities (view the full agenda and presentation slides here).

    For Juan Pedro Mendez Granado, a postdoc at Caltech, the workshop provided a crash course in how to take advantage of leadership computing resources to advance his research into lithium-based batteries. Granado, a graduate of the 2016 Argonne Training Program for Extreme-Scale Computing, has been modeling the process of lithiation and delithiation for silicon anodes using a computing cluster that allows him to simulate hundreds of thousands of atoms at a time.

    “With the ALCF’s supercomputers, I could simulate millions of atoms over much larger time scales,” he said. “Simulations at this scale would give us a much better understanding of the process at an atomistic level.”

    Granado came to the workshop to explore his options for accessing ALCF computing systems. He left with intentions to apply for a Director’s Discretionary award to begin preparing for a more substantial award in the future.

    “Not only does the workshop help participants improve their code performance, it also allows us to bring new researchers into the leadership computing pipeline,” said Loy of the ALCF. “Ultimately, we’re looking to grow the community of researchers who can use our systems for science.”

    See the full article here .

    Please help promote STEM in your local schools.
    STEM Icon
    Stem Education Coalition

    Argonne National Laboratory seeks solutions to pressing national problems in science and technology. The nation’s first national laboratory, Argonne conducts leading-edge basic and applied scientific research in virtually every scientific discipline. Argonne researchers work closely with researchers from hundreds of companies, universities, and federal, state and municipal agencies to help them solve their specific problems, advance America’s scientific leadership and prepare the nation for a better future. With employees from more than 60 nations, Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science. For more visit http://www.anl.gov.

    About ALCF

    The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing facilities in partnership with the computational science community.

    We help researchers solve some of the world’s largest and most complex problems with our unique combination of supercomputing resources and expertise.

    ALCF projects cover many scientific disciplines, ranging from chemistry and biology to physics and materials science. Examples include modeling and simulation efforts to:

    Discover new materials for batteries
    Predict the impacts of global climate change
    Unravel the origins of the universe
    Develop renewable energy technologies

    Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science

    Argonne Lab Campus

     
  • richardmitnick 9:51 pm on May 26, 2017 Permalink | Reply
    Tags: ANL-ALCF, Laser-driven magnetic reconnection, , ,   

    From ALCF: “Fields and flows fire up cosmic accelerators” 

    Argonne Lab
    News from Argonne National Laboratory

    ANL Cray Aurora supercomputer
    Cray Aurora supercomputer at the Argonne Leadership Computing Facility

    MIRA IBM Blue Gene Q supercomputer at the Argonne Leadership Computing Facility
    MIRA IBM Blue Gene Q supercomputer at the Argonne Leadership Computing Facility

    ALCF

    May 15, 2017
    John Spizzirri

    1
    A visualization from a 3D OSIRIS simulation of particle acceleration in laser-driven magnetic reconnection. The trajectories of the most energetic electrons (colored by energy) are shown as the two magnetized plasmas (grey isosurfaces) interact. Electrons are accelerated by the reconnection electric field at the interaction region and escape in a fan-like profile. Credit: Frederico Fiuza, SLAC National Accelerator Laboratory/OSIRIS

    Every day, with little notice, the Earth is bombarded by energetic particles that shower its inhabitants in an invisible dusting of radiation, observed only by the random detector, or astronomer, or physicist duly noting their passing. These particles constitute, perhaps, the galactic residue of some far distant supernova, or the tangible echo of a pulsar. These are cosmic rays.

    But how are these particles produced? And where do they find the energy to travel unchecked by immense distances and interstellar obstacles?

    These are the questions Frederico Fiuza has pursued over the last three years, through ongoing projects at the Argonne Leadership Computing Facility (ALCF), a U.S. Department of Energy (DOE) Office of Science User Facility.

    High-power lasers, such as those available at the University of Rochester’s Laboratory for Laser Energetics or at the National Ignition Facility in the Lawrence Livermore National Laboratory, can produce peak powers in excess of 1,000 trillion watts. At these high-powers, lasers can instantly ionize matter and create energetic plasma flows for the desired studies of particle acceleration.

    U Rochester Omega Laser

    LLNL/NIF

    A physicist at the SLAC National Accelerator Laboratory in California, Fiuza and his team are conducting thorough investigations of plasma physics to discern the fundamental processes that accelerate particles. The answers could provide an understanding of how cosmic rays gain their energy and how similar acceleration mechanisms could be probed in the laboratory and used for practical applications.

    Because the range in scales is so dramatic, they turned to the petascale power of Mira, the ALCF’s Blue Gene/Q supercomputer, to run the first-ever 3D simulations of these laboratory scenarios.

    To drive the simulation, they used OSIRIS, a state-of-the-art, particle-in-cell code for modeling plasmas, developed by UCLA and the Instituto Superior Técnico, in Portugal, where Fiuza earned his PhD.

    In the first phase of this project, Fiuza’s team showed that a plasma instability, the Weibel instability, is able to convert a large fraction of the energy in plasma flows to magnetic fields. They have shown a strong agreement in a one-to-one comparison of the experimental data with the 3D simulation data, which was published in Nature Physics, in 2015. This helped them understand how the strong fields required for particle acceleration can be generated in astrophysical environments.

    The team’s results, which were published in Physical Review Letters, in 2016, show that laser-driven reconnection leads to strong particle acceleration. As two expanding plasma plumes interact with each other, they form a thin current sheet, or reconnection layer, which becomes unstable, breaking into smaller sheets. During this process, the magnetic field is annihilated and a strong electric field is excited in the reconnection region, efficiently accelerating electrons as they enter the region.

    This research is supported by the DOE Office of Science. Computing time at the ALCF was allocated through the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program.

    See the full article here .

    Please help promote STEM in your local schools.
    STEM Icon
    Stem Education Coalition

    Argonne National Laboratory seeks solutions to pressing national problems in science and technology. The nation’s first national laboratory, Argonne conducts leading-edge basic and applied scientific research in virtually every scientific discipline. Argonne researchers work closely with researchers from hundreds of companies, universities, and federal, state and municipal agencies to help them solve their specific problems, advance America’s scientific leadership and prepare the nation for a better future. With employees from more than 60 nations, Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science. For more visit http://www.anl.gov.

    About ALCF

    The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing facilities in partnership with the computational science community.

    We help researchers solve some of the world’s largest and most complex problems with our unique combination of supercomputing resources and expertise.

    ALCF projects cover many scientific disciplines, ranging from chemistry and biology to physics and materials science. Examples include modeling and simulation efforts to:

    Discover new materials for batteries
    Predict the impacts of global climate change
    Unravel the origins of the universe
    Develop renewable energy technologies

    Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science

    Argonne Lab Campus

     
  • richardmitnick 5:21 am on May 16, 2017 Permalink | Reply
    Tags: ANL-ALCF, , , , Particle acceleration, , Rochester’s Laboratory for Laser Energetics,   

    From ALCF: “Fields and flows fire up cosmic accelerators” 

    Argonne Lab
    News from Argonne National Laboratory

    ANL Cray Aurora supercomputer
    Cray Aurora supercomputer at the Argonne Leadership Computing Facility

    MIRA IBM Blue Gene Q supercomputer at the Argonne Leadership Computing Facility
    MIRA IBM Blue Gene Q supercomputer at the Argonne Leadership Computing Facility

    ALCF

    May 15, 2017
    John Spizzirri

    1
    A visualization from a 3D OSIRIS simulation of particle acceleration in laser-driven magnetic reconnection. The trajectories of the most energetic electrons (colored by energy) are shown as the two magnetized plasmas (grey isosurfaces) interact. Electrons are accelerated by the reconnection electric field at the interaction region and escape in a fan-like profile. Credit: Frederico Fiuza, SLAC National Accelerator Laboratory/OSIRIS

    Every day, with little notice, the Earth is bombarded by energetic particles that shower its inhabitants in an invisible dusting of radiation, observed only by the random detector, or astronomer, or physicist duly noting their passing. These particles constitute, perhaps, the galactic residue of some far distant supernova, or the tangible echo of a pulsar. These are cosmic rays.

    But how are these particles produced? And where do they find the energy to travel unchecked by immense distances and interstellar obstacles?

    These are the questions Frederico Fiuza has pursued over the last three years, through ongoing projects at the Argonne Leadership Computing Facility (ALCF), a U.S. Department of Energy (DOE) Office of Science User Facility.

    A physicist at the SLAC National Accelerator Laboratory in California, Fiuza and his team are conducting thorough investigations of plasma physics to discern the fundamental processes that accelerate particles.

    The answers could provide an understanding of how cosmic rays gain their energy and how similar acceleration mechanisms could be probed in the laboratory and used for practical applications.

    While the “how” of particle acceleration remains a mystery, the “where” is slightly better understood. “The radiation emitted by electrons tells us that these particles are accelerated by plasma processes associated with energetic astrophysical objects,” says Fiuza.

    The visible universe is filled with plasma, ionized matter formed when gas is super-heated, separating electrons from ions. More than 99 percent of the observable universe is made of plasmas, and the radiation emitted from them creates the beautiful, eerie colors that accentuate nebulae and other astronomical wonders.

    The motivation for these projects came from asking whether it was possible to reproduce similar plasma conditions in the laboratory and study how particles are accelerated.

    High-power lasers, such as those available at the University of Rochester’s Laboratory for Laser Energetics or at the National Ignition Facility in the Lawrence Livermore National Laboratory, can produce peak powers in excess of 1,000 trillion watts.

    2
    Rochester’s Laboratory for Laser Energetics


    At these high-powers, lasers can instantly ionize matter and create energetic plasma flows for the desired studies of particle acceleration.

    Intimate Physics

    To determine what processes can be probed and how to conduct experiments efficiently, Fiuza’s team recreates the conditions of these laser-driven plasmas using large-scale simulations. Computationally, he says, it becomes very challenging to simultaneously solve for the large scale of the experiment and the very small-scale physics at the level of individual particles, where these flows produce fields that in turn accelerate particles.

    Because the range in scales is so dramatic, they turned to the petascale power of Mira, the ALCF’s Blue Gene/Q supercomputer, to run the first-ever 3D simulations of these laboratory scenarios. To drive the simulation, they used OSIRIS, a state-of-the-art, particle-in-cell code for modeling plasmas, developed by UCLA and the Instituto Superior Técnico, in Portugal, where Fiuza earned his PhD.

    Part of the complexity involved in modeling plasmas is derived from the intimate coupling between particles and electromagnetic radiation — particles emit radiation and the radiation affects the motion of the particles.

    In the first phase of this project, Fiuza’s team showed that a plasma instability, the Weibel instability, is able to convert a large fraction of the energy in plasma flows to magnetic fields. They have shown a strong agreement in a one-to-one comparison of the experimental data with the 3D simulation data, which was published in Nature Physics, in 2015. This helped them understand how the strong fields required for particle acceleration can be generated in astrophysical environments.

    Fiuza uses tennis as an analogy to explain the role these magnetic fields play in accelerating particles within shock waves. The net represents the shockwave and the racquets of the two players are akin to magnetic fields. If the players move towards the net as they bounce the ball between each other, the ball, or particles, rapidly accelerate.

    “The bottom line is, we now understand how magnetic fields are formed that are strong enough to bounce these particles back and forth to be energized. It’s a multi-step process: you need to start by generating strong fields — and we found an instability that can generate strong fields from nothing or from very small fluctuations — and then these fields need to efficiently scatter the particles,” says Fiuza.

    Reconnecting

    NASA Magnetic reconnection, Credit: M. Aschwanden et al. (LMSAL), TRACE, NASA

    But particles can be energized in another way if the system provides the strong magnetic fields from the start.

    “In some scenarios, like pulsars, you have extraordinary magnetic field amplitudes,” notes Fiuza. “There, you want to understand how the enormous amount of energy stored in these fields can be directly transferred to particles. In this case, we don’t tend to think of flows or shocks as the dominant process, but rather magnetic reconnection.”

    Magnetic reconnection, a fundamental process in astrophysical and fusion plasmas, is believed to be the cause of solar flares, coronal mass ejections, and other volatile cosmic events. When magnetic fields of opposite polarity are brought together, their topologies are changed. The magnetic field lines rearrange in such a way as to convert magnetic energy into heat and kinetic energy, causing an explosive reaction that drives the acceleration of particles. This was the focus of Fiuza’s most recent project at the ALCF.

    Again, Fiuza’s team modeled the possibility of studying this process in the laboratory with laser-driven plasmas. To conduct 3D, first-principles simulations (simulations derived from fundamental theoretical assumptions/predictions), Fiuza needed to model tens of billions of particles to represent the laser-driven magnetized plasma system. They modeled the motion of every particle and then selected the thousand most energetic ones. The motion of those particles was individually tracked to determine how they were accelerated by the magnetic reconnection process.

    “What is quite amazing about these cosmic accelerators is that a very, very small number of particles carry a large fraction of the energy in the system, let’s say 20 percent. So you have this enormous energy in this astrophysical system, and from some miraculous process, it all goes to a few lucky particles,” he says. “That means that the individual motion of particles and the trajectory of particles are very important.”

    The team’s results, which were published in Physical Review Letters, in 2016, show that laser-driven reconnection leads to strong particle acceleration. As two expanding plasma plumes interact with each other, they form a thin current sheet, or reconnection layer, which becomes unstable, breaking into smaller sheets. During this process, the magnetic field is annihilated and a strong electric field is excited in the reconnection region, efficiently accelerating electrons as they enter the region.

    Fiuza expects that, like his previous project, these simulation results can be confirmed experimentally and open a window into these mysterious cosmic accelerators.

    This research is supported by the DOE Office of Science. Computing time at the ALCF was allocated through the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program.

    See the full article here .

    Please help promote STEM in your local schools.
    STEM Icon
    Stem Education Coalition

    Argonne National Laboratory seeks solutions to pressing national problems in science and technology. The nation’s first national laboratory, Argonne conducts leading-edge basic and applied scientific research in virtually every scientific discipline. Argonne researchers work closely with researchers from hundreds of companies, universities, and federal, state and municipal agencies to help them solve their specific problems, advance America’s scientific leadership and prepare the nation for a better future. With employees from more than 60 nations, Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science. For more visit http://www.anl.gov.

    About ALCF

    The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing facilities in partnership with the computational science community.

    We help researchers solve some of the world’s largest and most complex problems with our unique combination of supercomputing resources and expertise.

    ALCF projects cover many scientific disciplines, ranging from chemistry and biology to physics and materials science. Examples include modeling and simulation efforts to:

    Discover new materials for batteries
    Predict the impacts of global climate change
    Unravel the origins of the universe
    Develop renewable energy technologies

    Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science

    Argonne Lab Campus

     
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