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Title: Basic Energy Sciences Exascale Requirements Review. An Office of Science review sponsored jointly by Advanced Scientific Computing Research and Basic Energy Sciences, November 3-5, 2015, Rockville, Maryland

Abstract

Computers have revolutionized every aspect of our lives. Yet in science, the most tantalizing applications of computing lie just beyond our reach. The current quest to build an exascale computer with one thousand times the capability of today’s fastest machines (and more than a million times that of a laptop) will take researchers over the next horizon. The field of materials, chemical reactions, and compounds is inherently complex. Imagine millions of new materials with new functionalities waiting to be discovered — while researchers also seek to extend those materials that are known to a dizzying number of new forms. We could translate massive amounts of data from high precision experiments into new understanding through data mining and analysis. We could have at our disposal the ability to predict the properties of these materials, to follow their transformations during reactions on an atom-by-atom basis, and to discover completely new chemical pathways or physical states of matter. Extending these predictions from the nanoscale to the mesoscale, from the ultrafast world of reactions to long-time simulations to predict the lifetime performance of materials, and to the discovery of new materials and processes will have a profound impact on energy technology. In addition, discoverymore » of new materials is vital to move computing beyond Moore’s law. To realize this vision, more than hardware is needed. New algorithms to take advantage of the increase in computing power, new programming paradigms, and new ways of mining massive data sets are needed as well. This report summarizes the opportunities and the requisite computing ecosystem needed to realize the potential before us. In addition to pursuing new and more complete physical models and theoretical frameworks, this review found that the following broadly grouped areas relevant to the U.S. Department of Energy (DOE) Office of Advanced Scientific Computing Research (ASCR) would directly affect the Basic Energy Sciences (BES) mission need. Simulation, visualization, and data analysis are crucial for advances in energy science and technology. Revolutionary mathematical, software, and algorithm developments are required in all areas of BES science to take advantage of exascale computing architectures and to meet data analysis, management, and workflow needs. In partnership with ASCR, BES has an emerging and pressing need to develop new and disruptive capabilities in data science. More capable and larger high-performance computing (HPC) and data ecosystems are required to support priority research in BES. Continued success in BES research requires developing the next-generation workforce through education and training and by providing sustained career opportunities.« less

Authors:
 [1];  [2];  [3];  [4];  [2];  [5];  [6];  [2];  [2];  [4];  [6];  [5];  [5];  [6];  [4];  [4];  [7];  [5];  [5];  [2] more »;  [8];  [9];  [5];  [10];  [11];  [12];  [13];  [5];  [2];  [14];  [15];  [2];  [16];  [17];  [18];  [19];  [20];  [16];  [16];  [21];  [16];  [5];  [22];  [23];  [2];  [24];  [25];  [26];  [4];  [5];  [16];  [27];  [2];  [10];  [28];  [4];  [29];  [5];  [30];  [16];  [26];  [31];  [8];  [2];  [2];  [32];  [3];  [28];  [16];  [5];  [16];  [8];  [33];  [19];  [34];  [5];  [11];  [4];  [4];  [16];  [3];  [5];  [2];  [35];  [26];  [2];  [2];  [31];  [2] « less
  1. Ames Lab., Ames, IA (United States)
  2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  3. SLAC National Accelerator Lab., Menlo Park, CA (United States)
  4. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  5. Argonne National Lab. (ANL), Argonne, IL (United States)
  6. Energy Sciences Network (ESNet), Berkeley, CA (United States)
  7. Univ. of Texas, El Paso, TX (United States)
  8. Princeton Univ., NJ (United States)
  9. Univ. of Illinois, Urbana-Champaign, IL (United States)
  10. Univ. of Texas, Austin, TX (United States)
  11. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  12. Univ. of Florida, Gainesville, FL (United States)
  13. Washington State Univ., Pullman, WA (United States)
  14. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)
  15. Univ. of Alabama, Tuscaloosa, AL (United States)
  16. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  17. Stony Brook Univ., NY (United States)
  18. Georgetown Univ., Washington, DC (United States)
  19. Univ. of Minnesota, Minneapolis, MN (United States)
  20. Univ. of Chicago, IL (United States)
  21. Iowa State Univ., Ames, IA (United States)
  22. Univ. of Michigan, Ann Arbor, MI (United States)
  23. Univ. of California, Davis, CA (United States)
  24. Univ. of California, Merced, CA (United States)
  25. Louisiana State Univ., Baton Rouge, LA (United States)
  26. Univ. of Southern California, Los Angeles, CA (United States)
  27. Indian Inst. of Science, Bangalore (India)
  28. Univ. of Washington, Seattle, WA (United States)
  29. Stanford Univ., CA (United States)
  30. Columbia Univ., New York, NY (United States)
  31. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  32. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  33. Univ. of California, Berkeley, CA (United States)
  34. Purdue Univ., West Lafayette, IN (United States)
  35. Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States)
Publication Date:
Research Org.:
US Department of Energy, Washington, DC (United States). Advanced Scientific Computing Research and Basic Energy Sciences
Sponsoring Org.:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21); USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)
OSTI Identifier:
1341721
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Windus, Theresa, Banda, Michael, Devereaux, Thomas, White, Julia C., Antypas, Katie, Coffey, Richard, Dart, Eli, Dosanjh, Sudip, Gerber, Richard, Hack, James, Monga, Inder, Papka, Michael E., Riley, Katherine, Rotman, Lauren, Straatsma, Tjerk, Wells, Jack, Baruah, Tunna, Benali, Anouar, Borland, Michael, Brabec, Jiri, Carter, Emily, Ceperley, David, Chan, Maria, Chelikowsky, James, Chen, Jackie, Cheng, Hai-Ping, Clark, Aurora, Darancet, Pierre, DeJong, Wibe, Deslippe, Jack, Dixon, David, Donatelli, Jeffrey, Dunning, Thomas, Fernandez-Serra, Marivi, Freericks, James, Gagliardi, Laura, Galli, Giulia, Garrett, Bruce, Glezakou, Vassiliki-Alexandra, Gordon, Mark, Govind, Niri, Gray, Stephen, Gull, Emanuel, Gygi, Francois, Hexemer, Alexander, Isborn, Christine, Jarrell, Mark, Kalia, Rajiv K., Kent, Paul, Klippenstein, Stephen, Kowalski, Karol, Krishnamurthy, Hulikal, Kumar, Dinesh, Lena, Charles, Li, Xiaosong, Maier, Thomas, Markland, Thomas, McNulty, Ian, Millis, Andrew, Mundy, Chris, Nakano, Aiichiro, Niklasson, A.M.N., Panagiotopoulos, Thanos, Pandolfi, Ron, Parkinson, Dula, Pask, John, Perazzo, Amedeo, Rehr, John, Rousseau, Roger, Sankaranarayanan, Subramanian, Schenter, Greg, Selloni, Annabella, Sethian, Jamie, Siepmann, Ilja, Slipchenko, Lyudmila, Sternberg, Michael, Stevens, Mark, Summers, Michael, Sumpter, Bobby, Sushko, Peter, Thayer, Jana, Toby, Brian, Tull, Craig, Valeev, Edward, Vashishta, Priya, Venkatakrishnan, V., Yang, C., Yang, Ping, and Zwart, Peter H. Basic Energy Sciences Exascale Requirements Review. An Office of Science review sponsored jointly by Advanced Scientific Computing Research and Basic Energy Sciences, November 3-5, 2015, Rockville, Maryland. United States: N. p., 2017. Web. doi:10.2172/1341721.
Windus, Theresa, Banda, Michael, Devereaux, Thomas, White, Julia C., Antypas, Katie, Coffey, Richard, Dart, Eli, Dosanjh, Sudip, Gerber, Richard, Hack, James, Monga, Inder, Papka, Michael E., Riley, Katherine, Rotman, Lauren, Straatsma, Tjerk, Wells, Jack, Baruah, Tunna, Benali, Anouar, Borland, Michael, Brabec, Jiri, Carter, Emily, Ceperley, David, Chan, Maria, Chelikowsky, James, Chen, Jackie, Cheng, Hai-Ping, Clark, Aurora, Darancet, Pierre, DeJong, Wibe, Deslippe, Jack, Dixon, David, Donatelli, Jeffrey, Dunning, Thomas, Fernandez-Serra, Marivi, Freericks, James, Gagliardi, Laura, Galli, Giulia, Garrett, Bruce, Glezakou, Vassiliki-Alexandra, Gordon, Mark, Govind, Niri, Gray, Stephen, Gull, Emanuel, Gygi, Francois, Hexemer, Alexander, Isborn, Christine, Jarrell, Mark, Kalia, Rajiv K., Kent, Paul, Klippenstein, Stephen, Kowalski, Karol, Krishnamurthy, Hulikal, Kumar, Dinesh, Lena, Charles, Li, Xiaosong, Maier, Thomas, Markland, Thomas, McNulty, Ian, Millis, Andrew, Mundy, Chris, Nakano, Aiichiro, Niklasson, A.M.N., Panagiotopoulos, Thanos, Pandolfi, Ron, Parkinson, Dula, Pask, John, Perazzo, Amedeo, Rehr, John, Rousseau, Roger, Sankaranarayanan, Subramanian, Schenter, Greg, Selloni, Annabella, Sethian, Jamie, Siepmann, Ilja, Slipchenko, Lyudmila, Sternberg, Michael, Stevens, Mark, Summers, Michael, Sumpter, Bobby, Sushko, Peter, Thayer, Jana, Toby, Brian, Tull, Craig, Valeev, Edward, Vashishta, Priya, Venkatakrishnan, V., Yang, C., Yang, Ping, & Zwart, Peter H. Basic Energy Sciences Exascale Requirements Review. An Office of Science review sponsored jointly by Advanced Scientific Computing Research and Basic Energy Sciences, November 3-5, 2015, Rockville, Maryland. United States. doi:10.2172/1341721.
Windus, Theresa, Banda, Michael, Devereaux, Thomas, White, Julia C., Antypas, Katie, Coffey, Richard, Dart, Eli, Dosanjh, Sudip, Gerber, Richard, Hack, James, Monga, Inder, Papka, Michael E., Riley, Katherine, Rotman, Lauren, Straatsma, Tjerk, Wells, Jack, Baruah, Tunna, Benali, Anouar, Borland, Michael, Brabec, Jiri, Carter, Emily, Ceperley, David, Chan, Maria, Chelikowsky, James, Chen, Jackie, Cheng, Hai-Ping, Clark, Aurora, Darancet, Pierre, DeJong, Wibe, Deslippe, Jack, Dixon, David, Donatelli, Jeffrey, Dunning, Thomas, Fernandez-Serra, Marivi, Freericks, James, Gagliardi, Laura, Galli, Giulia, Garrett, Bruce, Glezakou, Vassiliki-Alexandra, Gordon, Mark, Govind, Niri, Gray, Stephen, Gull, Emanuel, Gygi, Francois, Hexemer, Alexander, Isborn, Christine, Jarrell, Mark, Kalia, Rajiv K., Kent, Paul, Klippenstein, Stephen, Kowalski, Karol, Krishnamurthy, Hulikal, Kumar, Dinesh, Lena, Charles, Li, Xiaosong, Maier, Thomas, Markland, Thomas, McNulty, Ian, Millis, Andrew, Mundy, Chris, Nakano, Aiichiro, Niklasson, A.M.N., Panagiotopoulos, Thanos, Pandolfi, Ron, Parkinson, Dula, Pask, John, Perazzo, Amedeo, Rehr, John, Rousseau, Roger, Sankaranarayanan, Subramanian, Schenter, Greg, Selloni, Annabella, Sethian, Jamie, Siepmann, Ilja, Slipchenko, Lyudmila, Sternberg, Michael, Stevens, Mark, Summers, Michael, Sumpter, Bobby, Sushko, Peter, Thayer, Jana, Toby, Brian, Tull, Craig, Valeev, Edward, Vashishta, Priya, Venkatakrishnan, V., Yang, C., Yang, Ping, and Zwart, Peter H. Fri . "Basic Energy Sciences Exascale Requirements Review. An Office of Science review sponsored jointly by Advanced Scientific Computing Research and Basic Energy Sciences, November 3-5, 2015, Rockville, Maryland". United States. doi:10.2172/1341721. https://www.osti.gov/servlets/purl/1341721.
@article{osti_1341721,
title = {Basic Energy Sciences Exascale Requirements Review. An Office of Science review sponsored jointly by Advanced Scientific Computing Research and Basic Energy Sciences, November 3-5, 2015, Rockville, Maryland},
author = {Windus, Theresa and Banda, Michael and Devereaux, Thomas and White, Julia C. and Antypas, Katie and Coffey, Richard and Dart, Eli and Dosanjh, Sudip and Gerber, Richard and Hack, James and Monga, Inder and Papka, Michael E. and Riley, Katherine and Rotman, Lauren and Straatsma, Tjerk and Wells, Jack and Baruah, Tunna and Benali, Anouar and Borland, Michael and Brabec, Jiri and Carter, Emily and Ceperley, David and Chan, Maria and Chelikowsky, James and Chen, Jackie and Cheng, Hai-Ping and Clark, Aurora and Darancet, Pierre and DeJong, Wibe and Deslippe, Jack and Dixon, David and Donatelli, Jeffrey and Dunning, Thomas and Fernandez-Serra, Marivi and Freericks, James and Gagliardi, Laura and Galli, Giulia and Garrett, Bruce and Glezakou, Vassiliki-Alexandra and Gordon, Mark and Govind, Niri and Gray, Stephen and Gull, Emanuel and Gygi, Francois and Hexemer, Alexander and Isborn, Christine and Jarrell, Mark and Kalia, Rajiv K. and Kent, Paul and Klippenstein, Stephen and Kowalski, Karol and Krishnamurthy, Hulikal and Kumar, Dinesh and Lena, Charles and Li, Xiaosong and Maier, Thomas and Markland, Thomas and McNulty, Ian and Millis, Andrew and Mundy, Chris and Nakano, Aiichiro and Niklasson, A.M.N. and Panagiotopoulos, Thanos and Pandolfi, Ron and Parkinson, Dula and Pask, John and Perazzo, Amedeo and Rehr, John and Rousseau, Roger and Sankaranarayanan, Subramanian and Schenter, Greg and Selloni, Annabella and Sethian, Jamie and Siepmann, Ilja and Slipchenko, Lyudmila and Sternberg, Michael and Stevens, Mark and Summers, Michael and Sumpter, Bobby and Sushko, Peter and Thayer, Jana and Toby, Brian and Tull, Craig and Valeev, Edward and Vashishta, Priya and Venkatakrishnan, V. and Yang, C. and Yang, Ping and Zwart, Peter H.},
abstractNote = {Computers have revolutionized every aspect of our lives. Yet in science, the most tantalizing applications of computing lie just beyond our reach. The current quest to build an exascale computer with one thousand times the capability of today’s fastest machines (and more than a million times that of a laptop) will take researchers over the next horizon. The field of materials, chemical reactions, and compounds is inherently complex. Imagine millions of new materials with new functionalities waiting to be discovered — while researchers also seek to extend those materials that are known to a dizzying number of new forms. We could translate massive amounts of data from high precision experiments into new understanding through data mining and analysis. We could have at our disposal the ability to predict the properties of these materials, to follow their transformations during reactions on an atom-by-atom basis, and to discover completely new chemical pathways or physical states of matter. Extending these predictions from the nanoscale to the mesoscale, from the ultrafast world of reactions to long-time simulations to predict the lifetime performance of materials, and to the discovery of new materials and processes will have a profound impact on energy technology. In addition, discovery of new materials is vital to move computing beyond Moore’s law. To realize this vision, more than hardware is needed. New algorithms to take advantage of the increase in computing power, new programming paradigms, and new ways of mining massive data sets are needed as well. This report summarizes the opportunities and the requisite computing ecosystem needed to realize the potential before us. In addition to pursuing new and more complete physical models and theoretical frameworks, this review found that the following broadly grouped areas relevant to the U.S. Department of Energy (DOE) Office of Advanced Scientific Computing Research (ASCR) would directly affect the Basic Energy Sciences (BES) mission need. Simulation, visualization, and data analysis are crucial for advances in energy science and technology. Revolutionary mathematical, software, and algorithm developments are required in all areas of BES science to take advantage of exascale computing architectures and to meet data analysis, management, and workflow needs. In partnership with ASCR, BES has an emerging and pressing need to develop new and disruptive capabilities in data science. More capable and larger high-performance computing (HPC) and data ecosystems are required to support priority research in BES. Continued success in BES research requires developing the next-generation workforce through education and training and by providing sustained career opportunities.},
doi = {10.2172/1341721},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Fri Feb 03 00:00:00 EST 2017},
month = {Fri Feb 03 00:00:00 EST 2017}
}

Technical Report:

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  • Understanding the fundamentals of genomic systems or the processes governing impactful weather patterns are examples of the types of simulation and modeling performed on the most advanced computing resources in America. High-performance computing and computational science together provide a necessary platform for the mission science conducted by the Biological and Environmental Research (BER) office at the U.S. Department of Energy (DOE). This report reviews BER’s computing needs and their importance for solving some of the toughest problems in BER’s portfolio. BER’s impact on science has been transformative. Mapping the human genome, including the U.S.-supported international Human Genome Project that DOEmore » began in 1987, initiated the era of modern biotechnology and genomics-based systems biology. And since the 1950s, BER has been a core contributor to atmospheric, environmental, and climate science research, beginning with atmospheric circulation studies that were the forerunners of modern Earth system models (ESMs) and by pioneering the implementation of climate codes onto high-performance computers. See http://exascaleage.org/ber/ for more information.« less
  • The additional computing power offered by the planned exascale facilities could be transformational across the spectrum of plasma and fusion research — provided that the new architectures can be efficiently applied to our problem space. The collaboration that will be required to succeed should be viewed as an opportunity to identify and exploit cross-disciplinary synergies. To assess the opportunities and requirements as part of the development of an overall strategy for computing in the exascale era, the Exascale Requirements Review meeting of the Fusion Energy Sciences (FES) community was convened January 27–29, 2016, with participation from a broad range ofmore » fusion and plasma scientists, specialists in applied mathematics and computer science, and representatives from the U.S. Department of Energy (DOE) and its major computing facilities. This report is a summary of that meeting and the preparatory activities for it and includes a wealth of detail to support the findings. Technical opportunities, requirements, and challenges are detailed in this report (and in the recent report on the Workshop on Integrated Simulation). Science applications are described, along with mathematical and computational enabling technologies. Also see http://exascaleage.org/fes/ for more information.« less
  • The U.S. Department of Energy (DOE) Office of Science (SC) Offices of High Energy Physics (HEP) and Advanced Scientific Computing Research (ASCR) convened a programmatic Exascale Requirements Review on June 10–12, 2015, in Bethesda, Maryland. This report summarizes the findings, results, and recommendations derived from that meeting. The high-level findings and observations are as follows. Larger, more capable computing and data facilities are needed to support HEP science goals in all three frontiers: Energy, Intensity, and Cosmic. The expected scale of the demand at the 2025 timescale is at least two orders of magnitude — and in some cases greatermore » — than that available currently. The growth rate of data produced by simulations is overwhelming the current ability of both facilities and researchers to store and analyze it. Additional resources and new techniques for data analysis are urgently needed. Data rates and volumes from experimental facilities are also straining the current HEP infrastructure in its ability to store and analyze large and complex data volumes. Appropriately configured leadership-class facilities can play a transformational role in enabling scientific discovery from these datasets. A close integration of high-performance computing (HPC) simulation and data analysis will greatly aid in interpreting the results of HEP experiments. Such an integration will minimize data movement and facilitate interdependent workflows. Long-range planning between HEP and ASCR will be required to meet HEP’s research needs. To best use ASCR HPC resources, the experimental HEP program needs (1) an established, long-term plan for access to ASCR computational and data resources, (2) the ability to map workflows to HPC resources, (3) the ability for ASCR facilities to accommodate workflows run by collaborations potentially comprising thousands of individual members, (4) to transition codes to the next-generation HPC platforms that will be available at ASCR facilities, (5) to build up and train a workforce capable of developing and using simulations and analysis to support HEP scientific research on next-generation systems.« less
  • The widespread use of computing in the American economy would not be possible without a thoughtful, exploratory research and development (R&D) community pushing the performance edge of operating systems, computer languages, and software libraries. These are the tools and building blocks — the hammers, chisels, bricks, and mortar — of the smartphone, the cloud, and the computing services on which we rely. Engineers and scientists need ever-more specialized computing tools to discover new material properties for manufacturing, make energy generation safer and more efficient, and provide insight into the fundamentals of the universe, for example. The research division of themore » U.S. Department of Energy’s (DOE’s) Office of Advanced Scientific Computing and Research (ASCR Research) ensures that these tools and building blocks are being developed and honed to meet the extreme needs of modern science. See also http://exascaleage.org/ascr/ for additional information.« less
  • The mission of the U.S. Department of Energy Office of Science (DOE SC) is the delivery of scientific discoveries and major scientific tools to transform our understanding of nature and to advance the energy, economic, and national security missions of the United States. To achieve these goals in today’s world requires investments in not only the traditional scientific endeavors of theory and experiment, but also in computational science and the facilities that support large-scale simulation and data analysis. The Advanced Scientific Computing Research (ASCR) program addresses these challenges in the Office of Science. ASCR’s mission is to discover, develop, andmore » deploy computational and networking capabilities to analyze, model, simulate, and predict complex phenomena important to DOE. ASCR supports research in computational science, three high-performance computing (HPC) facilities — the National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory and Leadership Computing Facilities at Argonne (ALCF) and Oak Ridge (OLCF) National Laboratories — and the Energy Sciences Network (ESnet) at Berkeley Lab. ASCR is guided by science needs as it develops research programs, computers, and networks at the leading edge of technologies. As we approach the era of exascale computing, technology changes are creating challenges for science programs in SC for those who need to use high performance computing and data systems effectively. Numerous significant modifications to today’s tools and techniques will be needed to realize the full potential of emerging computing systems and other novel computing architectures. To assess these needs and challenges, ASCR held a series of Exascale Requirements Reviews in 2015–2017, one with each of the six SC program offices,1 and a subsequent Crosscut Review that sought to integrate the findings from each. Participants at the reviews were drawn from the communities of leading domain scientists, experts in computer science and applied mathematics, ASCR facility staff, and DOE program managers in ASCR and the respective program offices. The purpose of these reviews was to identify mission-critical scientific problems within the DOE Office of Science (including experimental facilities) and determine the requirements for the exascale ecosystem that would be needed to address those challenges. The exascale ecosystem includes exascale computing systems, high-end data capabilities, efficient software at scale, libraries, tools, and other capabilities. This effort will contribute to the development of a strategic roadmap for ASCR compute and data facility investments and will help the ASCR Facility Division establish partnerships with Office of Science stakeholders. It will also inform the Office of Science research needs and agenda. The results of the six reviews have been published in reports available on the web at http://exascaleage.org/. This report presents a summary of the individual reports and of common and crosscutting findings, and it identifies opportunities for productive collaborations among the DOE SC program offices.« less