Performance Analysis, Design Considerations, and Applications of Extreme-Scale In Situ Infrastructures

Ayachit, Utkarsh; Bauer, Andrew; Duque, Earl P. N.; Eisenhauer, Greg; Ferrier, Nicola; Gu, Junmin; Jansen, Kenneth E.; Loring, Burlen; Lukic, Zarija; Menon, Suresh; Morozov, Dmitriy; O'Leary, Patrick; Ranjan, Reetesh; Rasquin, Michel; Stone, Christopher P.; Vishwanath, Venkat; Weber, Gunther H.; Whitlock, Brad; Wolf, Matthew; Wu, K. John; Bethel, E. Wes

doi:10.1109/SC.2016.78

Title: Performance Analysis, Design Considerations, and Applications of Extreme-Scale In Situ Infrastructures

Abstract

A key trend facing extreme-scale computational science is the widening gap between computational and I/O rates, and the challenge that follows is how to best gain insight from simulation data when it is increasingly impractical to save it to persistent storage for subsequent visual exploration and analysis. One approach to this challenge is centered around the idea of in situ processing, where visualization and analysis processing is performed while data is still resident in memory. This paper examines several key design and performance issues related to the idea of in situ processing at extreme scale on modern platforms: scalability, overhead, performance measurement and analysis, comparison and contrast with a traditional post hoc approach, and interfacing with simulation codes. We illustrate these principles in practice with studies, conducted on large-scale HPC platforms, that include a miniapplication and multiple science application codes, one of which demonstrates in situ methods in use at greater than 1M-way concurrency.

Authors:

Ayachit, Utkarsh ^[1]; Bauer, Andrew ^[1]; Duque, Earl P. N. ^[2]; Eisenhauer, Greg ^[3]; Ferrier, Nicola ^[4]; Gu, Junmin ^[5]; Jansen, Kenneth E. ^[6]; Loring, Burlen ^[5]; Lukic, Zarija ^[5]; Menon, Suresh ^[3]; Morozov, Dmitriy ^[5]; O'Leary, Patrick ^[1]; Ranjan, Reetesh ^[3]; Rasquin, Michel ^[7]; Stone, Christopher P. ^[8]; Vishwanath, Venkat ^[4]; Weber, Gunther H. ^[5]; Whitlock, Brad ^[2]; Wolf, Matthew ^[3]; Wu, K. John ^[5] more »

Kitware, Inc., Clifton Park, NY (United States)
Intelligent Light, Rutherford, NJ (United States)
Georgia Inst. of Technology, Atlanta, GA (United States)
Argonne National Lab. (ANL), Argonne, IL (United States)
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Univ. of Colorado, Boulder, CO (United States)
Univ. of Colorado, Boulder, CO (United States); Cenaero, Charleroi (Belgium)
Computational Science and Engineering, LLC, Annapolis, MD (United States)

Publication Date:: Tue Nov 01 00:00:00 EDT 2016

Research Org.:: Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Kitware, Inc., Clifton Park, NY (United States)

Sponsoring Org.:: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR); USDOE Office of Nuclear Energy (NE)

OSTI Identifier:: 1379776

Alternate Identifier(s):: OSTI ID: 1595254

Grant/Contract Number:: AC02-05CH11231; SC0012037

Resource Type:: Accepted Manuscript

Journal Name:: International Conference for High Performance Computing, Networking, Storage and Analysis (Online)

Additional Journal Information:: Journal Name: International Conference for High Performance Computing, Networking, Storage and Analysis (Online); Journal Volume: 2017; Conference: International Conference for High Performance Computing, Networking, Storage and Analysis, Salt Lake City, UT (United States), 13-18 Nov 2016; Journal ID: ISSN 2167-4337

Publisher:: IEEE

Country of Publication:: United States

Language:: English

Subject:: 97 MATHEMATICS AND COMPUTING; concurrent computing; computational modeling; data models; data visualization; scientific computing; analytical models; libraries

Citation Formats


                    Ayachit, Utkarsh, Bauer, Andrew, Duque, Earl P. N., Eisenhauer, Greg, Ferrier, Nicola, Gu, Junmin, Jansen, Kenneth E., Loring, Burlen, Lukic, Zarija, Menon, Suresh, Morozov, Dmitriy, O'Leary, Patrick, Ranjan, Reetesh, Rasquin, Michel, Stone, Christopher P., Vishwanath, Venkat, Weber, Gunther H., Whitlock, Brad, Wolf, Matthew, Wu, K. John, and Bethel, E. Wes. Performance Analysis, Design Considerations, and Applications of Extreme-Scale In Situ Infrastructures.  United States: N. p., 2016. 
Web.  doi:10.1109/SC.2016.78.

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                    Ayachit, Utkarsh, Bauer, Andrew, Duque, Earl P. N., Eisenhauer, Greg, Ferrier, Nicola, Gu, Junmin, Jansen, Kenneth E., Loring, Burlen, Lukic, Zarija, Menon, Suresh, Morozov, Dmitriy, O'Leary, Patrick, Ranjan, Reetesh, Rasquin, Michel, Stone, Christopher P., Vishwanath, Venkat, Weber, Gunther H., Whitlock, Brad, Wolf, Matthew, Wu, K. John, & Bethel, E. Wes. Performance Analysis, Design Considerations, and Applications of Extreme-Scale In Situ Infrastructures.  United States.  https://doi.org/10.1109/SC.2016.78

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                    Ayachit, Utkarsh, Bauer, Andrew, Duque, Earl P. N., Eisenhauer, Greg, Ferrier, Nicola, Gu, Junmin, Jansen, Kenneth E., Loring, Burlen, Lukic, Zarija, Menon, Suresh, Morozov, Dmitriy, O'Leary, Patrick, Ranjan, Reetesh, Rasquin, Michel, Stone, Christopher P., Vishwanath, Venkat, Weber, Gunther H., Whitlock, Brad, Wolf, Matthew, Wu, K. John, and Bethel, E. Wes. Tue .  
"Performance Analysis, Design Considerations, and Applications of Extreme-Scale In Situ Infrastructures".  United States.  https://doi.org/10.1109/SC.2016.78.  https://www.osti.gov/servlets/purl/1379776.

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@article{osti_1379776,

  title        = {Performance Analysis, Design Considerations, and Applications of Extreme-Scale In Situ Infrastructures},

  author       = {Ayachit, Utkarsh and Bauer, Andrew and Duque, Earl P. N. and Eisenhauer, Greg and Ferrier, Nicola and Gu, Junmin and Jansen, Kenneth E. and Loring, Burlen and Lukic, Zarija and Menon, Suresh and Morozov, Dmitriy and O'Leary, Patrick and Ranjan, Reetesh and Rasquin, Michel and Stone, Christopher P. and Vishwanath, Venkat and Weber, Gunther H. and Whitlock, Brad and Wolf, Matthew and Wu, K. John and Bethel, E. Wes},

  abstractNote = {A key trend facing extreme-scale computational science is the widening gap between computational and I/O rates, and the challenge that follows is how to best gain insight from simulation data when it is increasingly impractical to save it to persistent storage for subsequent visual exploration and analysis. One approach to this challenge is centered around the idea of in situ processing, where visualization and analysis processing is performed while data is still resident in memory. This paper examines several key design and performance issues related to the idea of in situ processing at extreme scale on modern platforms: scalability, overhead, performance measurement and analysis, comparison and contrast with a traditional post hoc approach, and interfacing with simulation codes. We illustrate these principles in practice with studies, conducted on large-scale HPC platforms, that include a miniapplication and multiple science application codes, one of which demonstrates in situ methods in use at greater than 1M-way concurrency.},

  doi          = {10.1109/SC.2016.78},

  journal      = {International Conference for High Performance Computing, Networking, Storage and Analysis (Online)},

  number       = ,

  volume       = 2017,

  place        = {United States},

  year         = {Tue Nov 01 00:00:00 EDT 2016},

  month        = {Tue Nov 01 00:00:00 EDT 2016}

}

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Works referencing / citing this record:

Scalable In situ Analysis of Molecular Dynamics Simulations
conference, January 2017

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Proceedings of the In Situ Infrastructures on Enabling Extreme-Scale Analysis and Visualization - ISAV'17
DOI: 10.1145/3144769.3144772

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Citation Formats

Scalable In situ Analysis of Molecular Dynamics Simulations conference, January 2017

Scalable In situ Analysis of Molecular Dynamics Simulations
conference, January 2017