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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}
}

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