HPGMG 1.0: A Benchmark for Ranking High Performance Computing Systems

Adams, Mark; Brown, Jed; Shalf, John; Straalen, Brian Van; Strohmaier, Erich; Williams, Sam

doi:10.2172/1131029

Title: HPGMG 1.0: A Benchmark for Ranking High Performance Computing Systems

Full Record
Other Related Research

Abstract

This document provides an overview of the benchmark ? HPGMG ? for ranking large scale general purpose computers for use on the Top500 list [8]. We provide a rationale for the need for a replacement for the current metric HPL, some background of the Top500 list and the challenges of developing such a metric; we discuss our design philosophy and methodology, and an overview of the specification of the benchmark. The primary documentation with maintained details on the specification can be found at hpgmg.org and the Wiki and benchmark code itself can be found in the repository https://bitbucket.org/hpgmg/hpgmg.

Authors:: Adams, Mark; Brown, Jed; Shalf, John; Straalen, Brian Van; Strohmaier, Erich; Williams, Sam

Publication Date:: 2014-05-05

Research Org.:: Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

Sponsoring Org.:: Computational Research Division

OSTI Identifier:: 1131029

Report Number(s):: LBNL-6630E

DOE Contract Number:: DE-AC02-05CH11231

Resource Type:: Technical Report

Country of Publication:: United States

Language:: English

Subject:: 97 MATHEMATICS AND COMPUTING; benchmark, full multigrid, geometric multigrid, multigrid, top500

Citation Formats


                    Adams, Mark, Brown, Jed, Shalf, John, Straalen, Brian Van, Strohmaier, Erich, and Williams, Sam. HPGMG 1.0: A Benchmark for Ranking High Performance Computing Systems.  United States: N. p., 2014. 
        Web.  doi:10.2172/1131029.

Copy to clipboard


                    Adams, Mark, Brown, Jed, Shalf, John, Straalen, Brian Van, Strohmaier, Erich, & Williams, Sam. HPGMG 1.0: A Benchmark for Ranking High Performance Computing Systems.  United States.  https://doi.org/10.2172/1131029

Copy to clipboard


                    Adams, Mark, Brown, Jed, Shalf, John, Straalen, Brian Van, Strohmaier, Erich, and Williams, Sam. 2014.  
        "HPGMG 1.0: A Benchmark for Ranking High Performance Computing Systems".  United States.  https://doi.org/10.2172/1131029.  https://www.osti.gov/servlets/purl/1131029.

Copy to clipboard


                    
@article{osti_1131029,

  title        = {HPGMG 1.0: A Benchmark for Ranking High Performance Computing Systems},

  author       = {Adams, Mark and Brown, Jed and Shalf, John and Straalen, Brian Van and Strohmaier, Erich and Williams, Sam},

  abstractNote = {This document provides an overview of the benchmark ? HPGMG ? for ranking large scale general purpose computers for use on the Top500 list [8]. We provide a rationale for the need for a replacement for the current metric HPL, some background of the Top500 list and the challenges of developing such a metric; we discuss our design philosophy and methodology, and an overview of the specification of the benchmark. The primary documentation with maintained details on the specification can be found at hpgmg.org and the Wiki and benchmark code itself can be found in the repository https://bitbucket.org/hpgmg/hpgmg.},

  doi          = {10.2172/1131029},

  url          = {https://www.osti.gov/biblio/1131029},
  journal      = {},
number       = ,

  volume       = ,

  place        = {United States},

  year         = {2014},

  month        = {5}

}

Copy to clipboard

Technical Report:

View Technical Report (0.19 MB)

https://doi.org/10.2172/1131029

Save / Share:

Export Metadata

Save to My Library

Similar records in OSTI.GOV collections:

Solving a trillion unknowns per second with HPGMG on Sunway TaihuLight

Journal Article Ma, Wenjing; Ao, Yulong; Yang, Chao; ... - Cluster Computing

Benchmarks for supercomputers are important tools, not only for evaluating and ranking modern supercomputers, but also for providing hints for future architecture design. As a new benchmark, HPGMG (high performance geometric multigrid) solves a linear equation set with a full geometric multi-grid algorithm. It involves computation on different scales, data movement with various volumes, global communication and neighbor communication with both large and small messages, etc., and is more correlated to real world applications than traditional benchmarks such as LINPACK. Therefore, it is desirable to examine how well HPGMG can perform on leadership supercomputers such as Sunway Taihulight. Sunway Taihulight,more »« less
https://doi.org/10.1007/s10586-019-02938-w

Full Text Available
Understanding the Performance and Potential of Cloud Computing for Scientific Applications

Journal Article Sadooghi, Iman; Martin, Jesus; Li, Tonglin; ... - IEEE Transactions on Cloud Computing

In this paper, commercial clouds bring a great opportunity to the scientific computing area. Scientific applications usually require significant resources, however not all scientists have access to sufficient high-end computing systems, may of which can be found in the Top500 list. Cloud Computing has gained the attention of scientists as a competitive resource to run HPC applications at a potentially lower cost. But as a different infrastructure, it is unclear whether clouds are capable of running scientific applications with a reasonable performance per money spent. This work studies the performance of public clouds and places this performance in context tomore »« less
Cited by 18
https://doi.org/10.1109/TCC.2015.2404821

Full Text Available
Hospital Energy Benchmarking Guidance - Version 1.0

Technical Report Singer, Brett

This document describes an energy benchmarking framework for hospitals. The document is organized as follows. The introduction provides a brief primer on benchmarking and its application to hospitals. The next two sections discuss special considerations including the identification of normalizing factors. The presentation of metrics is preceded by a description of the overall framework and the rationale for the grouping of metrics. Following the presentation of metrics, a high-level protocol is provided. The next section presents draft benchmarks for some metrics; benchmarks are not available for many metrics owing to a lack of data. This document ends with a listmore »« less
https://doi.org/10.2172/974318

Full Text Available
Introduction to the HPC Challenge Benchmark Suite

Conference Luszczek, Piotr; Dongarra, Jack; Koester, David; ...

The HPC Challenge benchmark suite has been released by the DARPA HPCS program to help define the performance boundaries of future Petascale computing systems. HPC Challenge is a suite of tests that examine the performance of HPC architectures using kernels with memory access patterns more challenging than those of the High Performance Linpack (HPL) benchmark used in the Top500 list. Thus, the suite is designed to augment the Top500 list, providing benchmarks that bound the performance of many real applications as a function of memory access characteristics e.g., spatial and temporal locality, and providing a framework for including additional tests.more »« less
Full Text Available
US Department of Energy, Office of Science High Performance Computing Facility Operational Assessment 2019 Oak Ridge Leadership Computing Facility

Technical Report Abston, J.; Adamson, Ryan; Atchley, Scott; ...

Oak Ridge National Laboratory's (ORNL's) Leadership Computing Facility (OLCF) continues to surpass its operational target goals: supporting users; delivering fast, reliable computational ecosystems; creating innovative solutions for high performance computing (HPC) needs; and managing risks, safety, and security associated with operating some of the most powerful computers in the world. The results can be seen in the cutting-edge science conducted by users and the praise from the research community. Calendar year (CY) 2019 was a big year as OLCF staff ran five world-class resources (the leadershipclass computers Titan and Summit, the large analysis cluster called Eos, and the massive parallelmore »« less
https://doi.org/10.2172/1649264

Full Text Available

Similar Records