Hierarchical Roofline analysis for GPUs: Accelerating performance optimization for the NERSC‐9 Perlmutter system

doi:10.1002/cpe.5547

This content will become publicly available on November 11, 2020

Title: Hierarchical Roofline analysis for GPUs: Accelerating performance optimization for the NERSC‐9 Perlmutter system

Authors:

^[1];

^[1]; Williams, Samuel ^[2]

National Energy Research Scientific Computing Center (NERSC)Lawrence Berkeley National Laboratory Berkeley California
Computational Research Division (CRD)Lawrence Berkeley National Laboratory Berkeley California

Publication Date:: 2019-11-12

Sponsoring Org.:: USDOE

OSTI Identifier:: 1574050

Grant/Contract Number:: AC02-05CH11231

Resource Type:: Publisher's Accepted Manuscript

Journal Name:: Concurrency and Computation. Practice and Experience

Additional Journal Information:: Journal Name: Concurrency and Computation. Practice and Experience; Journal ID: ISSN 1532-0626

Publisher:: Wiley Blackwell (John Wiley & Sons)

Country of Publication:: United Kingdom

Language:: English

Citation Formats


                    Yang, Charlene, Kurth, Thorsten, and Williams, Samuel. Hierarchical Roofline analysis for GPUs: Accelerating performance optimization for the NERSC‐9 Perlmutter system.  United Kingdom: N. p., 2019. 
        Web.  doi:10.1002/cpe.5547.

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                    Yang, Charlene, Kurth, Thorsten, & Williams, Samuel. Hierarchical Roofline analysis for GPUs: Accelerating performance optimization for the NERSC‐9 Perlmutter system.  United Kingdom.  doi:10.1002/cpe.5547.

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                    Yang, Charlene, Kurth, Thorsten, and Williams, Samuel. Tue .  
        "Hierarchical Roofline analysis for GPUs: Accelerating performance optimization for the NERSC‐9 Perlmutter system".  United Kingdom.  doi:10.1002/cpe.5547.

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@article{osti_1574050,

  title        = {Hierarchical Roofline analysis for GPUs: Accelerating performance optimization for the NERSC‐9 Perlmutter system},

  author       = {Yang, Charlene and Kurth, Thorsten and Williams, Samuel},

  abstractNote = {},

  doi          = {10.1002/cpe.5547},

  journal      = {Concurrency and Computation. Practice and Experience},

  number       = ,

  volume       = ,

  place        = {United Kingdom},

  year         = {2019},

  month        = {11}

}

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DOI: 10.1002/cpe.5547

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Works referenced in this record:

Roofline: an insightful visual performance model for multicore architectures
journal, April 2009

Williams, Samuel; Waterman, Andrew; Patterson, David
Communications of the ACM, Vol. 52, Issue 4
DOI: 10.1145/1498765.1498785

Electron self-energy calculation using a general multi-pole approximation
journal, April 2003

Soininen, J. A.; Rehr, J. J.; Shirley, Eric L.
Journal of Physics: Condensed Matter, Vol. 15, Issue 17
DOI: 10.1088/0953-8984/15/17/312

Demystifying Parallel and Distributed Deep Learning: An In-depth Concurrency Analysis
journal, August 2019

Ben-Nun, Tal; Hoefler, Torsten
ACM Computing Surveys, Vol. 52, Issue 4
DOI: 10.1145/3320060

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This content will become publicly available on November 11, 2020

Title: Hierarchical Roofline analysis for GPUs: Accelerating performance optimization for the NERSC‐9 Perlmutter system

Citation Formats

Roofline: an insightful visual performance model for multicore architectures journal, April 2009

Electron self-energy calculation using a general multi-pole approximation journal, April 2003

Demystifying Parallel and Distributed Deep Learning: An In-depth Concurrency Analysis journal, August 2019

Roofline: an insightful visual performance model for multicore architectures
journal, April 2009

Electron self-energy calculation using a general multi-pole approximation
journal, April 2003

Demystifying Parallel and Distributed Deep Learning: An In-depth Concurrency Analysis
journal, August 2019