Tagged: ANL-ALCF Toggle Comment Threads | Keyboard Shortcuts

  • 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

    Advertisements
     
  • 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, , LLNL NIF, , 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

     
  • richardmitnick 11:02 am on March 14, 2017 Permalink | Reply
    Tags: , ANL-ALCF, , , Vector boson plus jet event   

    From ALCF: “High-precision calculations help reveal the physics of the universe” 

    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

    March 9, 2017
    Joan Koka

    1
    With the theoretical framework developed at Argonne, researchers can more precisely predict particle interactions such as this simulation of a vector boson plus jet event. Credit: Taylor Childers, Argonne National Laboratory

    On their quest to uncover what the universe is made of, researchers at the U.S. Department of Energy’s (DOE) Argonne National Laboratory are harnessing the power of supercomputers to make predictions about particle interactions that are more precise than ever before.

    Argonne researchers have developed a new theoretical approach, ideally suited for high-performance computing systems, that is capable of making predictive calculations about particle interactions that conform almost exactly to experimental data. This new approach could give scientists a valuable tool for describing new physics and particles beyond those currently identified.

    The framework makes predictions based on the Standard Model, the theory that describes the physics of the universe to the best of our knowledge. Researchers are now able to compare experimental data with predictions generated through this framework, to potentially uncover discrepancies that could indicate the existence of new physics beyond the Standard Model. Such a discovery would revolutionize our understanding of nature at the smallest measurable length scales.

    “So far, the Standard Model of particle physics has been very successful in describing the particle interactions we have seen experimentally, but we know that there are things that this model doesn’t describe completely.


    The Standard Model of elementary particles (more schematic depiction), with the three generations of matter, gauge bosons in the fourth column, and the Higgs boson in the fifth.

    We don’t know the full theory,” said Argonne theorist Radja Boughezal, who developed the framework with her team.

    “The first step in discovering the full theory and new models involves looking for deviations with respect to the physics we know right now. Our hope is that there is deviation, because it would mean that there is something that we don’t understand out there,” she said.

    The theoretical method developed by the Argonne team is currently being deployed on Mira, one of the fastest supercomputers in the world, which is housed at the Argonne Leadership Computing Facility, a DOE Office of Science User Facility.

    Using Mira, researchers are applying the new framework to analyze the production of missing energy in association with a jet, a particle interaction of particular interest to researchers at the Large Hadron Collider (LHC) in Switzerland.




    LHC at CERN

    Physicists at the LHC are attempting to produce new particles that are known to exist in the universe but have yet to be seen in the laboratory, such as the dark matter that comprises a quarter of the mass and energy of the universe.


    Dark matter cosmic web and the large-scale structure it forms The Millenium Simulation, V. Springel et al

    Although scientists have no way today of observing dark matter directly — hence its name — they believe that dark matter could leave a “missing energy footprint” in the wake of a collision that could indicate the presence of new particles not included in the Standard Model. These particles would interact very weakly and therefore escape detection at the LHC. The presence of a “jet”, a spray of Standard Model particles arising from the break-up of the protons colliding at the LHC, would tag the presence of the otherwise invisible dark matter.

    In the LHC detectors, however, the production of a particular kind of interaction — called the Z-boson plus jet process — can mimic the same signature as the potential signal that would arise from as-yet-unknown dark matter particles. Boughezal and her colleagues are using their new framework to help LHC physicists distinguish between the Z-boson plus jet signature predicted in the Standard Model from other potential signals.

    Previous attempts using less precise calculations to distinguish the two processes had so much uncertainty that they were simply not useful for being able to draw the fine mathematical distinctions that could potentially identify a new dark matter signal.

    “It is only by calculating the Z-boson plus jet process very precisely that we can determine whether the signature is indeed what the Standard Model predicts, or whether the data indicates the presence of something new,” said Frank Petriello, another Argonne theorist who helped develop the framework. “This new framework opens the door to using Z-boson plus jet production as a tool to discover new particles beyond the Standard Model.”

    Applications for this method go well beyond studies of the Z-boson plus jet. The framework will impact not only research at the LHC, but also studies at future colliders which will have increasingly precise, high-quality data, Boughezal and Petriello said.

    “These experiments have gotten so precise, and experimentalists are now able to measure things so well, that it’s become necessary to have these types of high-precision tools in order to understand what’s going on in these collisions,” Boughezal said.

    “We’re also so lucky to have supercomputers like Mira because now is the moment when we need these powerful machines to achieve the level of precision we’re looking for; without them, this work would not be possible.”

    Funding and resources for this work was previously allocated through the Argonne Leadership Computing Facility’s (ALCF’s) Director’s Discretionary program; the ALCF is supported by the DOE’s Office of Science’s Advanced Scientific Computing Research program. Support for this work will continue through allocations coming from the Innovation and Novel Computational Impact on Theory and Experiment (INCITE) program.

    The INCITE program promotes transformational advances in science and technology through large allocations of time on state-of-the-art supercomputers.

    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 2:33 pm on January 23, 2017 Permalink | Reply
    Tags: ANL-ALCF, , , , , Stable versions of synthetic peptides, Tailor-made drug molecules   

    From ALCF: “A rising peptide: Supercomputing helps scientists come closer to tailoring drug molecules” 

    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

    January 23, 2017
    Robert Grant

    1
    An artificial peptide made from a mixture of natural L-amino acids (the right half of the molecule) and non-natural, mirror-image D-amino acids (the left half of the molecule), designed computationally using INCITE resources. This peptide is designed to fold into a stable structure with a topology not found in nature, featuring a canonical right-handed alpha-helix packing against a non-canonical left-handed alpha-helix. Since structure imparts function, the ability to design non-natural structures permits scientists to create exciting new functions never explored by natural proteins. This peptide was synthesized chemically, and its structure was solved by nuclear magnetic resonance spectroscopy to confirm that it does indeed adopt this fold. The peptide backbone is shown as a translucent gold ribbon, and amino acid side-chains are shown as dark sticks. The molecular surface is shown as a transparent outline. Credit: Vikram Mulligan, University of Washington

    A team of researchers led by biophysicists at the University of Washington have come one step closer to designing tailor-made drug molecules that are more precise and carry fewer side effects than most existing therapeutic compounds.

    With the help of the Mira supercomputer, located at the Argonne Leadership Computing Facility at the U.S. Department of Energy’s (DOE) Argonne National Laboratory, the scientists have successfully designed and verified stable versions of synthetic peptides, components that join together to form proteins.

    They published their work in a recent issue of Nature.

    The computational protocol, which was validated by assembling physical peptides in the chemistry lab and comparing them to the computer models, may one day enable drug developers to craft novel, therapeutic peptides that precisely target specific disease-causing molecules within the body. And the insights the researchers gleaned constitute a significant advance in the fundamental understanding of protein folding.

    “That you can design molecules from scratch that fold up into structures, some of which are quite unlike what you see in nature, demonstrates a pretty fundamental understanding of what goes on at the molecular level,” said David Baker, the University of Washington biophysicist who led the research. “That’s certainly one of the more exciting things about this work.”

    Baker Lab

    David Baker
    David Baker

    The majority of drugs that humans use to treat the variety of ailments we suffer are so-called “small molecules.” These tiny compounds easily pass through different body systems to target receptor proteins studded in the membranes of our cells.

    Most do their job well, but they come with a major drawback: “Most drugs in use right now are small molecules, which are very tiny and nonspecific. They bind to lots of different things, which produces lots of side effects,” said Vikram Mulligan, a postdoctoral researcher in Baker’s lab and coauthor on the paper.

    More complex protein drugs ameliorate this problem, but they less readily disperse throughout the body because the more bulky molecules have a harder time passing through blood vessels, the linings of the digestive tract and other barriers.

    And proteins, which are giant on the molecular scale, have several layers of structure that all overlap to make them less static and more dynamic, making predicting their binding behavior a tricky prospect.

    But between the extremes of small, but imprecise, molecules and floppy, but high-specificity proteins, there exists a middle ground – peptides. These short chains of amino acids, which normally link together to make complex proteins, can target specific receptors, diffuse easily throughout the body and also sustain a rigid structure.

    Some naturally-occurring peptides are already used as drugs, such as the immunosuppressant ciclosporin, but researchers could open up a world of pharmaceutical opportunity if they could design and synthesize peptides.

    That’s precisely what Baker and his team did, tweaking the Rosetta software package that they built for the design of protein structures to accommodate synthetic amino acids that do not exist in nature, in addition to the 20 natural amino acids.

    After designing the chemical building blocks of peptides, the researchers used the supercomputer Mira, with its 10 petaflops of processing power and more than 780,000 cores, to model scores of potential shapes, or conformations, that specific backbone sequences of amino acids might take.

    “We basically sample millions and millions of these conformations,” said Yuri Alexeev, a project specialist in computational science at the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility. “At the same time you also improve the energy functions,” which are measurements to describe the efficiency and stability of each possible folding arrangement.

    Though he was not a coauthor on the Nature paper, Alexeev helped Baker’s team scale up previous programs it had used to design proteins for modeling peptides on Mira.

    Executing so many calculations simultaneously would be virtually impossible without Mira’s computing power, according to Mulligan.

    “The big challenge with designing peptides that fold is that you have a chain of amino acids that can exist in an astronomical number of conformations,” he said.

    Baker and his colleagues had tasked Mira with modeling millions of potential peptide conformations before, but this study stands out for two reasons.

    First, the researchers arrived at a handful of peptides with specific conformations that the computations predicted would be stable.

    Second, when Baker’s lab created seven of these peptides in their physical wet lab, the reality of the peptides’ conformations and stability corresponded remarkably well with the computer models.

    “At best, what comes out of a computer is a prediction, and at worst what comes out of a computer is a fantasy. So we never really consider it a result until we’ve actually made the molecule in the wet lab and confirmed that it actually has the structure that we designed it to have,” said Mulligan.

    “That’s exactly what we did in this paper,” he said. “We made a panel of these peptides that were designed to fold into very specific shapes, diverse shapes, and we experimentally confirmed that all of them folded into the shapes that we designed.”

    While this experiment sought to create totally new peptides in stable conformations as a proof of concept, Mulligan says that the Baker lab is now moving on to design functional peptides with specific targets in mind.

    Further research may bring the team closer to a protocol that could actually be used to design peptide drugs that target a specific receptor, such as those that make viruses like Ebola or HIV susceptible to attack.

    Computer time was awarded by the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program; the project also used resources of the Environmental Molecular Sciences Laboratory, a DOE Office of Science User Facility at Pacific Northwest National Laboratory.

    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 3:29 pm on January 4, 2017 Permalink | Reply
    Tags: ANL-ALCF, , , Wind studies   

    From ALCF: “Supercomputer simulations helping to improve wind predictions” 

    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

    January 3, 2017
    Katie Jones

    1
    Station locations and lists of instruments deployed within the Columbia River Gorge, Columbia River Basin, and surrounding region. Credit:
    James Wilczak, NOAA

    A research team led by the National Oceanic and Atmospheric Administration (NOAA) is performing simulations at the Argonne Leadership Computing Facility (ALCF), a U.S. Department of Energy (DOE) Office of Science User Facility, to develop numerical weather prediction models that can provide more accurate wind forecasts in regions with complex terrain. The team, funded by DOE in support of its Wind Forecast Improvement Project II (WFIP 2), is testing and validating the computational models with data being collected from a network of environmental sensors in the Columbia River Gorge region.

    Wind turbines dotting the Columbia River Gorge in Washington and Oregon can collectively generate about 4,500 megawatts (MW) of power, or more than that of five, 800-MW nuclear power plants. However, the gorge region and its dramatic topography create highly variable wind conditions, posing a challenge for utility operators who use weather forecast models to predict when wind power will be available on the grid.

    If predictions are unreliable, operators must depend on steady power sources like coal and nuclear plants to meet demand. Because they take a long time to fuel and heat, conventional power plants operate on less flexible timetables and can generate power that is then wasted if wind energy unexpectedly floods the grid.

    To produce accurate wind predictions over complex terrain, researchers are using Mira, the ALCF’s 10-petaflops IBM Blue Gene/Q supercomputer, to increase resolution and improve physical representations to better simulate wind features in national forecast models. In a unique intersection of field observation and computer simulation, the research team has installed and is collecting data from a network of environmental instruments in the Columbia River Gorge region that is being used to test and validate model improvements.

    This research is part of the Wind Forecast Improvement Project II (WFIP 2), an effort sponsored by DOE in collaboration with NOAA, Vaisala—a manufacturer of environmental and meteorological equipment—and a number of national laboratories and universities. DOE aims to increase U.S. wind energy from five to 20 percent of total energy use by 2020, which means optimizing how wind is used on the grid.

    “Our goal is to give utility operators better forecasts, which could ultimately help make the cost of wind energy a little cheaper,” said lead model developer Joe Olson of NOAA. “For example, if the forecast calls for a windy day but operators don’t trust the forecast, they won’t be able to turn off coal plants, which are releasing carbon dioxide when maybe there was renewable wind energy available.”

    The complicated physics of wind

    For computational efficiency, existing forecast models assume the Earth’s surface is relatively flat—which works well at predicting wind on the flat terrain of the Midwestern United States where states like Texas and Iowa generate many thousands of megawatts of wind power. Yet, as the Columbia River Gorge region demonstrates, some of the ripest locations for harnessing wind energy could be along mountains and coastlines where conditions are difficult to predict.

    “There are a lot of complications predicting wind conditions for terrain with a high degree of complexity at a variety of spatial scales,” Olson said.

    Two major challenges include overcoming a model resolution that is too low for resolving wind features in sharp valleys and mountain gaps and a lack of observational data.

    At the NOAA National Center for Environmental Prediction, two atmospheric models run around the clock to provide national weather forecasts: the 13-km Rapid Refresh (RAP) and the 3-km High-Resolution Rapid Refresh (HRRR). Only a couple of years old, the HRRR model has improved storm and winter weather predictions by resolving atmospheric features at 9 km2—or about 2.5 times the size of Central Park in New York City.

    At a resolution of a few kilometers, HRRR can capture processes at the mesoscale—about the size of storms—but cannot resolve features at the microscale, which is a few hundred feet. Some phenomena important to wind prediction that cannot be modeled in RAP or HRRR include mountain wakes (the splitting of airflow obstructed by the side of a mountain); mountain waves (the oscillation of air flow on the side of the mountain that affects cloud formation and turbulence); and gap flow (small-scale winds that can blow strongly through gaps in mountains and gorge ridges).

    The 750-meter leap

    To make wind predictions that are sufficiently accurate for utility operators, Olson said they need to model physical parameters at a 750-m resolution—about one-sixth the size of Central Park, or an average wind farm. This 16-times increase in resolution will require a lot of real-world data for model testing and validation, which is why the WFIP 2 team outfitted the Columbia River Gorge region with more than 20 environmental sensor stations.

    “We haven’t been able to identify all the strengths and weaknesses for wind predictions in the model because we haven’t had a complete, detailed dataset,” Olson said. “Now we have an expansive network of wind profilers and other weather instruments. Some are sampling wind in mountain gaps and valleys, others are on ridges. It’s a multiscale network that can capture the high-resolution aspects of the flow, as well as the broader mesoscale flows.”

    Many of the sensors send data every 10 minutes. Considering data will be collected for an 18-month period that began in October 2015 and ends March 2017, this steady stream will ultimately amount to about half a petabyte. The observational data is initially sent to Pacific Northwest National Laboratory where it is stored until it is used to test model parameters on Mira at Argonne.

    The WFIP 2 research team needed Mira’s highly parallel architecture to simulate an ensemble of about 20 models with varied parameterizations. ALCF researchers Ray Loy and Ramesh Balakrishnan worked with the team to optimize the HRRR architectural configuration and craft a strategy that allowed them to run the necessary ensemble jobs.

    “We wanted to run on Mira because ALCF has experience using HRRR for climate simulations and running ensembles jobs that would allow us to compare the models’ physical parameters,” said Rao Kotamarthi, chief scientist and department head of Argonne’s Climate and Atmospheric Science Department. “The ALCF team helped to scale the model to Mira and instructed us on how to bundle jobs so they avoid interrupting workflow, which is important for a project that often has new data coming in.”

    The ensemble approach allowed the team to create case studies that are used to evaluate how each simulation compared to observational data.

    “We pick certain case studies where the model performs very poorly, and we go back and change the physics in the model until it improves, and we keep doing that for each case study so that we have significant improvement across many scenarios,” Olson said.

    At the end of the field data collection, the team will simulate an entire year of weather conditions with an emphasis on wind in the Columbia River Gorge region using the control model—the 3-km HRRR model before any modifications were made—and a modified model with the improved physical parameterizations.

    “That way, we’ll be able to get a good measure of how much has improved overall,” Olson said.

    Computing time on Mira was awarded through the ASCR Leadership Computing Challenge (ALCC). Collaborating institutions include DOE’s Wind Energy Technologies Office, NOAA, Argonne, Pacific Northwest National Laboratory, Lawrence Livermore National Laboratory, the National Renewable Energy Laboratory, the University of Colorado, Notre Dame University, Texas Tech University, and Vaisala.

    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 3:28 pm on November 23, 2016 Permalink | Reply
    Tags: ANL-ALCF, , , Computerworld, ,   

    From ALCF via Computerworld: “U.S. sets plan to build two exascale supercomputers” 

    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

    1

    COMPUTERWORLD

    Nov 21, 2016
    Patrick Thibodeau

    2
    ARM

    The U.S believes it will be ready to seek vendor proposals to build two exascale supercomputers — costing roughly $200 million to $300 million each — by 2019.

    The two systems will be built at the same time and will be ready for use by 2023, although it’s possible one of the systems could be ready a year earlier, according to U.S. Department of Energy officials.

    But the scientists and vendors developing exascale systems do not yet know whether President-Elect Donald Trump’s administration will change directions. The incoming administration is a wild card. Supercomputing wasn’t a topic during the campaign, and Trump’s dismissal of climate change as a hoax, in particular, has researchers nervous that science funding may suffer.

    At the annual supercomputing conference SC16 last week in Salt Lake City, a panel of government scientists outlined the exascale strategy developed by President Barack Obama’s administration. When the session was opened to questions, the first two were about Trump. One attendee quipped that “pointed-head geeks are not going to be well appreciated.”

    Another person in the audience, John Sopka, a high-performance computing software consultant, asked how the science community will defend itself from claims that “you are taking the money from the people and spending it on dreams,” referring to exascale systems.

    Paul Messina, a computer scientist and distinguished fellow at Argonne National Labs who heads the Exascale Computing Project, appeared sanguine. “We believe that an important goal of the exascale computing project is to help economic competitiveness and economic security,” said Messina. “I could imagine that the administration would think that those are important things.”

    Politically, there ought to be a lot in HPC’s favor. A broad array of industries rely on government supercomputers to conduct scientific research, improve products, attack disease, create new energy systems and understand climate, among many other fields. Defense and intelligence agencies also rely on large systems.

    The ongoing exascale research funding (the U.S. budget is $150 million this year) will help with advances in software, memory, processors and other technologies that ultimately filter out to the broader commercial market.

    This is very much a global race, which is something the Trump administration will have to be mindful of. China, Europe and Japan are all developing exascale systems.

    China plans to have an exascale system ready by 2020. These nations see exascale — and the computing advances required to achieve it — as a pathway to challenging America’s tech dominance.

    “I’m not losing sleep over it yet,” said Messina, of the possibility that the incoming Trump administration may have different supercomputing priorities. “Maybe I will in January.”

    The U.S. will award the exascale contracts to vendors with two different architectures. This is not a new approach and is intended to help keep competition at the highest end of the market. Recent supercomputer procurements include systems built on the IBM Power architecture, Nvidia’s Volta GPU and Cray-built systems using Intel chips.

    The timing of these exascale systems — ready for 2023 — is also designed to take advantage of the upgrade cycles at the national labs. The large systems that will be installed in the next several years will be ready for replacement by the time exascale systems arrive.

    The last big performance milestone in supercomputing occurred in 2008 with the development of a petaflop system. An exaflop is a 1,000-petaflop system and building it is challenging because of the limits of Moore’s Law, a 1960s-era observation that noted the number of transistors on a chip doubles about every two years.

    “Now we’re at the point where Moore’s Law is just about to end,” said Messina in an interview. That means the key to building something faster “is by having much more parallelism, and many more pieces. That’s how you get the extra speed.”

    An exascale system will solve a problem 50 times faster than the 20-petaflop systems in use in government labs today.

    Development work has begun on the systems and applications that can utilize hundreds of millions of simultaneous parallel events. “How do you manage it — how do you get it all to work smoothly?” said Messina.

    Another major problem is energy consumption. An exascale machine can be built today using current technology, but such a system would likely need its own power plant. The U.S. wants an exascale system that can operate on 20 megawatts and certainly no more than 30 megawatts.

    Scientists will have to come up with a way “to vastly reduce the amount of energy it takes to do a calculation,” said Messina. The applications and software development are critical because most of the energy is used to move data. And new algorithms will be needed.

    About 500 people are working at universities and national labs on the DOE’s coordinated effort to develop the software and other technologies exascale will need.

    Aside from the cost of building the systems, the U.S. will spend millions funding the preliminary work. Vendors want to maintain the intellectual property of what they develop. If it cost, for instance, $50 million to develop a certain aspect of a system, the U.S. may ask the vendor to pay 40% of that cost if they want to keep the intellectual property.

    A key goal of the U.S. research funding is to avoid creation of one-off technologies that can only be used in these particular exascale systems.

    “We have to be careful,” Terri Quinn, a deputy associate director for HPC at Lawrence Livermore National Laboratory, said at the SC16 panel session. “We don’t want them (vendors) to give us capabilities that are not sustainable in a business market.”

    The work under way will help ensure that the technology research is far enough along to enable the vendors to respond to the 2019 request for proposals.

    Supercomputers can deliver advances in modeling and simulation. Instead of building physical prototypes of something, a supercomputer can allow modeling virtually. This can speed the time it takes something to get to market, whether a new drug or car engine. Increasingly, HPC is used in big data and is helping improve cybersecurity through rapid analysis; artificial intelligence and robotics are other fields with strong HPC demand.

    China will likely beat the U.S. in developing an exascale system, but the real test will be their usefulness.

    Messina said the U.S. approach is to develop an exascale eco-system involving vendors, universities and the government. The hope is that the exascale systems will not only a have a wide range of applications ready for them, but applications that are relatively easy to program. Messina wants to see these systems quickly put to immediate and broad use.

    “Economic competitiveness does matter to a lot of people,” said Messina.

    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 12:59 pm on November 12, 2016 Permalink | Reply
    Tags: ANL-ALCF, , ,   

    From Argonne Leadership Computing Facility “Exascale Computing Project announces $48 million to establish four exascale co-design centers” 

    ANL Lab
    News from Argonne National Laboratory

    Argonne Leadership Computing Facility
    A DOE Office of Science user facility

    November 11, 2016
    Mike Bernhardt

    1
    Co-design and integration of hardware, software, applications and platforms, is essential to deploying exascale-class systems that will meet the future requirements of the scientific communities these systems will serve. Credit: Andre Schleife, UIUC

    The U.S. Department of Energy’s (DOE’s) Exascale Computing Project (ECP) today announced that it has selected four co-design centers as part of a 4-year $48 million funding award. The first year is funded at $12 million, and is to be allocated evenly among the four award recipients.

    The ECP is responsible for the planning, execution and delivery of technologies necessary for a capable exascale ecosystem to support the nation’s exascale imperative, including software, applications, hardware and early testbed platforms.

    Exascale refers to computing systems at least 50 times faster than the nation’s most powerful supercomputers in use today.

    According to Doug Kothe, ECP Director of Application Development: “Co-design lies at the heart of the Exascale Computing Project. ECP co-design, an intimate interchange of the best that hardware technologies, software technologies and applications have to offer each other, will be a catalyst for delivery of exascale-enabling science and engineering solutions for the U.S.”

    “By targeting common patterns of computation and communication, known as “application motifs,” we are confident that these ECP co-design centers will knock down key performance barriers and pave the way for applications to exploit all that capable exascale has to offer,” he said.

    The development of capable exascale systems requires an interdisciplinary engineering approach in which the developers of the software ecosystem, the hardware technology and a new generation of computational science applications are collaboratively involved in a participatory design process referred to as co-design.

    The co-design process is paramount to ensuring that future exascale applications adequately reflect the complex interactions and trade-offs associated with the many new—and sometimes conflicting—design options, enabling these applications to tackle problems they currently can’t address.

    According to ECP Director Paul Messina, “The establishment of these and future co design centers is foundational to the creation of an integrated, usable and useful exascale ecosystem. After a lengthy review, we are pleased to announce that we have initially selected four proposals for funding. The establishment of these co-design centers, following on the heels of our recent application development awards, signals the momentum and direction of ECP as we bring together the necessary ecosystem and infrastructure to drive the nation’s exascale imperative.”
    The four selected co-design proposals and their principal investigators are as follows:

    CODAR: Co-Design Center for Online Data Analysis and Reduction at the Exascale

    Principal Investigator: Ian Foster, Argonne National Laboratory Distinguished Fellow

    This co-design center will focus on overcoming the rapidly growing gap between compute speed and storage input/output rates by evaluating, deploying and integrating novel online data analysis and reduction methods for the exascale. Working closely with Exascale Computing Project applications, CODAR will undertake a focused co-design process that targets both common and domain-specific data analysis and reduction methods, with the goal of allowing application developers to choose and configure methods to output just the data needed by the application. CODAR will engage directly with providers of ECP hardware, system software, programming models, data analysis and reduction algorithms and applications in order to better understand and guide tradeoffs in the development of exascale systems, applications and software frameworks, given constraints relating to application development costs, application fidelity, performance portability, scalability and power efficiency.

    “Argonne is pleased to be leading CODAR efforts in support of the Exascale Computing Project,” said Argonne Distinguished Fellow Ian Foster. “We aim in CODAR to co-optimize applications, data services and exascale platforms to deliver the right bits in the right place at the right time.”

    Block-Structured AMR Co-Design Center

    Principal Investigator: John Bell, Lawrence Berkeley National Laboratory

    The Block-Structured Adaptive Mesh Refinement Co-Design Center will be led by Lawrence Berkeley National Laboratory with support from Argonne National Laboratory and the National Renewable Energy Laboratory. The goal is to develop a new framework, AMReX, to support the development of block-structured adaptive mesh refinement algorithms for solving systems of partial differential equations with complex boundary conditions on exascale architectures. Block-structured adaptive mesh refinement provides a natural framework in which to focus computing power on the most critical parts of the problem in the most computationally efficient way possible. Block-structured AMR is already widely used to solve many problems relevant to DOE. Specifically, at least six of the 22 exascale application projects announced last month—in the areas of accelerators, astrophysics, combustion, cosmology, multiphase flow and subsurface flow—will rely on block-structured AMR as part of the ECP.

    “This co-design center reflects the important role of adaptive mesh refinement in accurately simulating problems at scales ranging from the edges of flames to global climate to the makeup of the universe, and how AMR will be critical to tackling problems at the exascale,” said David Brown, director of Berkeley Lab’s Computational Research Division. “It’s also important to note that AMR will be a critical component in a third of the 22 exascale application projects announced in September, which will help ensure that researchers can make productive use of exascale systems when they are deployed.”

    Center for Efficient Exascale Discretizations (CEED)

    Principal Investigator: Tzanio Kolev, Lawrence Livermore National Laboratory

    Fully exploiting future exascale architectures will require a rethinking of the algorithms used in the large-scale applications that advance many science areas vital to DOE and the National Nuclear Security Administration (NNSA), such as global climate modeling, turbulent combustion in internal combustion engines, nuclear reactor modeling, additive manufacturing, subsurface flow and national security applications. The newly established Center for Efficient Exascale Discretizations aims to help these DOE and NNSA applications to take full advantage of exascale hardware by using state-of-the-art ‘high-order discretizations’ that provide an order of magnitude performance improvement over traditional methods.

    In simple mathematical terms, discretization denotes the process of dividing a geometry into finite elements, or building blocks, in preparation for analysis. This process, which can dramatically improve application performance, involves making simplifying assumptions to reduce demands on the computer, but with minimal loss of accuracy. Recent developments in supercomputing make it increasingly clear that the high-order discretizations, which CEED is focused on, have the potential to achieve optimal performance and deliver fast, efficient and accurate simulations on exascale systems.

    The CEED Co-Design Center is a research partnership of two DOE labs and five universities. Partners include Lawrence Livermore National Laboratory; Argonne National Laboratory; the University of Illinois Urbana-Champaign; Virginia Tech; University of Tennessee, Knoxville; Colorado University, Boulder; and the Rensselaer Polytechnic Institute.

    “The CEED team I have the privilege to lead is dedicated to the development of next-generation discretization software and algorithms that will enable a wide range of applications to run efficiently on future hardware,” said CEED director Tzanio Kolev of Lawrence Livermore National Laboratory. “Our co-design center is focused first and foremost on applications. We bring to this enterprise a collaborative team of application scientists, computational mathematicians and computer scientists with a strong track record of delivering performant software on leading-edge platforms. Collectively, we support hundreds of users in national labs, industry and academia, and we are committed to pushing simulation capabilities to new levels across an ever-widening range of applications.”

    Co-design center for Particle Applications (CoPA)

    Principal Investigator: Tim Germann, Los Alamos National Laboratory

    This co-design center will serve as a centralized clearinghouse for particle-based ECP applications, communicating their requirements and evaluating potential uses and benefits of ECP hardware and software technologies using proxy applications. Particle-based simulation approaches are ubiquitous in computational science and engineering, and they involve the interaction of each particle with its environment by direct particle-particle interactions at shorter ranges and/or by particle-mesh interactions with a local field that is set up by longer-range effects. Best practices in code portability, data layout and movement, and performance optimization will be developed and disseminated via sustainable, productive and interoperable co-designed numerical recipes for particle-based methods that meet the application requirements within the design space of software technologies and subject to exascale hardware constraints. The ultimate goal is the creation of scalable open exascale software platforms suitable for use by a variety of particle-based simulations.

    “Los Alamos is delighted to be leading the Co-Design Center for Particle-Based Methods: From Quantum to Classical, Molecular to Cosmological, which builds on the success of ExMatEx, the Exascale CoDesign Center for Materials in Extreme Environments,” said John Sarrao, Associate Director for Theory, Simulation, and Computation at Los Alamos. “Advancing deterministic particle-based methods is essential for simulations at the exascale, and Los Alamos has long believed that co-design is the right approach for advancing these frontiers. We look forward to partnering with our colleague laboratories in successfully executing this important element of the Exascale Computing Project.”

    About ECP

    The ECP 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.

    About the Office of Science

    DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit http://science.energy.gov/.

    About NNSA

    Established by Congress in 2000, NNSA is a semi-autonomous agency within DOE, responsible for enhancing national security through the military application of nuclear science. NNSA maintains and enhances the safety, security and effectiveness of the U.S. nuclear weapons stockpile without nuclear explosive testing; works to reduce the global danger from weapons of mass destruction; provides the U.S. Navy with safe and effective nuclear propulsion; and responds to nuclear and radiological emergencies in the United States and abroad.

    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.

    The Advanced Photon Source at Argonne National Laboratory is one of five national synchrotron radiation light sources supported by the U.S. Department of Energy’s Office of Science to carry out applied and basic research to understand, predict, and ultimately control matter and energy at the electronic, atomic, and molecular levels, provide the foundations for new energy technologies, and support DOE missions in energy, environment, and national security. To learn more about the Office of Science X-ray user facilities, visit http://science.energy.gov/user-facilities/basic-energy-sciences/.

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

    Argonne Lab Campus

     
c
Compose new post
j
Next post/Next comment
k
Previous post/Previous comment
r
Reply
e
Edit
o
Show/Hide comments
t
Go to top
l
Go to login
h
Show/Hide help
shift + esc
Cancel
%d bloggers like this: