Graph500

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The Graph500 is a rating of supercomputer systems, focused on data-intensive loads. The project was announced on International Supercomputing Conference in June 2010. The first list was published at the ACM/IEEE Supercomputing Conference in November 2010. New versions of the list are published twice a year. The main performance metric used to rank the supercomputers is GTEPS (giga- traversed edges per second).

Contents

Richard Murphy from Sandia National Laboratories, says that "The Graph500's goal is to promote awareness of complex data problems", instead of focusing on computer benchmarks like HPL (High Performance Linpack), which TOP500 is based on. [1]

Despite its name, there were several hundreds of systems in the rating, growing up to 174 in June 2014. [2]

The algorithm and implementation that won the championship is published in the paper titled "Extreme scale breadth-first search on supercomputers". [3]

There is also list Green Graph 500, which uses same performance metric, but sorts list according to performance per Watt, like Green 500 works with TOP500 (HPL).

Benchmark

The benchmark used in Graph500 stresses the communication subsystem of the system, instead of counting double precision floating-point. [1] It is based on a breadth-first search in a large undirected graph (a model of Kronecker graph with average degree of 16). There are three computation kernels in the benchmark: the first kernel is to generate the graph and compress it into sparse structures CSR or CSC (Compressed Sparse Row/Column); the second kernel does a parallel BFS search of some random vertices (64 search iterations per run); the third kernel runs a single-source shortest paths (SSSP) computation. Six possible sizes (Scales) of graph are defined: toy (226 vertices; 17 GB of RAM), mini (229; 137 GB), small (232; 1.1 TB), medium (236; 17.6 TB), large (239; 140 TB), and huge (242; 1.1 PB of RAM). [4]

The reference implementation of the benchmark contains several versions: [5]

The implementation strategy that have won the championship on the Japanese K computer is described in. [6]

Top 10 ranking

According to June 2023 release of the list the new Wuhan supercomputer is highest ranked for the SSSP results with 19039.1 GTEPS (and Fugaku is 4th) while for the BFS results its 2nd there with a different lower measurement for GTEPS: [7]

RankCountrySiteMachine (architecture)Number of nodesNumber of coresProblem scale GTEPS
1Flag of Japan.svg  Japan RIKEN Advanced Institute for Computational Science Supercomputer Fugaku (Fujitsu A64FX)152064729907242137096
2Flag of the People's Republic of China.svg  China Wuhan Kunpeng 920+Tesla A100252699955240121804.3
3Flag of the United States.svg  USA FrontierHPE Cray EX235a924887301124029654.6
4Flag of the People's Republic of China.svg  China Pengcheng LabPengcheng Cloudbrain-II (Kunpeng 920+Ascend 910)488936964025242.9
5Flag of the People's Republic of China.svg  China National Supercomputing Center in Wuxi Sunway TaihuLight (Sunway MPP)40768105996804023755.7

Japan also has a new computer ranked 8th.

2022

According to November 2022 release of the list: [8]

RankCountrySiteMachine (architecture)Number of nodesNumber of coresProblem scale GTEPS
1Flag of Japan.svg  Japan RIKEN Advanced Institute for Computational Science Supercomputer Fugaku (Fujitsu A64FX)158976763084841102955
2Flag of the People's Republic of China.svg  China Pengcheng LabPengcheng Cloudbrain-II (Kunpeng 920+Ascend 910)488936964025242.9
3Flag of the People's Republic of China.svg  China National Supercomputing Center in Wuxi Sunway TaihuLight (Sunway MPP)40768105996804023755.7
4Flag of Japan.svg  Japan Information Technology Center, University of Tokyo Wisteria/BDEC-01 (PRIMEHPC FX1000)76803686403716118
5Flag of Japan.svg  Japan Japan Aerospace Exploration Agency TOKI-SORA (PRIMEHPC FX1000)57602764803610813
6Flag of Europe.svg  EU EuroHPC/CSC LUMI-C (HPE Cray EX)1492190976388467.71
7Flag of the United States.svg  US Oak Ridge National Laboratory OLCF Summit (IBM POWER9)204886016407665.7
8Flag of Germany.svg  Germany Leibniz Rechenzentrum SuperMUC-NG (ThinkSystem SD530 Xeon Platinum 8174 24C 3.1GHz Intel Omni-Path)4096196608396279.47
9Flag of Germany.svg  Germany Zuse Institute Berlin Lise (Intel Omni-Path)1270121920385423.94
10Flag of the People's Republic of China.svg  China National Engineering Research Center for Big Data Technology and SystemDepGraph Supernode (DepGraph (+GPU Tesla A100))1128334623.379

2020

Arm-based Fugaku took the top spot of the list. [9]

2016

According to June 2016 release of the list: [10]

RankSiteMachine (architecture)Number of nodesNumber of coresProblem scale GTEPS
1 Riken Advanced Institute for Computational Science K computer (Fujitsu custom)829446635524038621.4
2 National Supercomputing Center in Wuxi Sunway TaihuLight (NRCPC - Sunway MPP)40768105996804023755.7
3 Lawrence Livermore National Laboratory IBM Sequoia (Blue Gene/Q)9830415728644123751
4 Argonne National Laboratory IBM Mira (Blue Gene/Q)491527864324014982
5 Forschungszentrum Jülich JUQUEEN (Blue Gene/Q)16384262144385848
6 CINECA Fermi (Blue Gene/Q)8192131072372567
7 Changsha, China Tianhe-2 (NUDT custom)8192196608362061.48
8CNRS/IDRIS-GENCITuring (Blue Gene/Q)409665536361427
8Science and Technology Facilities Council – Daresbury LaboratoryBlue Joule (Blue Gene/Q)409665536361427
8 University of Edinburgh DIRAC (Blue Gene/Q)409665536361427
8EDF R&DZumbrota (Blue Gene/Q)409665536361427
8 Victorian Life Sciences Computation Initiative Avoca (Blue Gene/Q)409665536361427

2014

According to June 2014 release of the list: [2]

RankSiteMachine (architecture)Number of nodesNumber of coresProblem scale GTEPS
1 RIKEN Advanced Institute for Computational Science K computer (Fujitsu custom)655365242884017977.1
2 Lawrence Livermore National Laboratory IBM Sequoia (Blue Gene/Q)6553610485764016599
3 Argonne National Laboratory IBM Mira (Blue Gene/Q)491527864324014328
4 Forschungszentrum Jülich JUQUEEN (Blue Gene/Q)16384262144385848
5 CINECA Fermi (Blue Gene/Q)8192131072372567
6 Changsha, China Tianhe-2 (NUDT custom)8192196608362061.48
7CNRS/IDRIS-GENCITuring (Blue Gene/Q)409665536361427
7Science and Technology Facilities Council - Daresbury LaboratoryBlue Joule (Blue Gene/Q)409665536361427
7 University of Edinburgh DIRAC (Blue Gene/Q)409665536361427
7EDF R&DZumbrota (Blue Gene/Q)409665536361427
7 Victorian Life Sciences Computation Initiative Avoca (Blue Gene/Q)409665536361427

2013

According to June 2013 release of the list: [11]

RankSiteMachine (architecture)Number of nodesNumber of coresProblem scale GTEPS
1Lawrence Livermore National LaboratoryIBM Sequoia (Blue Gene/Q)6553610485764015363
2Argonne National LaboratoryIBM Mira (Blue Gene/Q)491527864324014328
3Forschungszentrum JülichJUQUEEN (Blue Gene/Q)16384262144385848
4RIKEN Advanced Institute for Computational ScienceK computer (Fujitsu custom)65536524288405524.12
5CINECAFermi (Blue Gene/Q)8192131072372567
6Changsha, ChinaTianhe-2 (NUDT custom)8192196608362061.48
7CNRS/IDRIS-GENCITuring (Blue Gene/Q)409665536361427
7Science and Technology Facilities Council - Daresbury LaboratoryBlue Joule (Blue Gene/Q)409665536361427
7University of EdinburghDIRAC (Blue Gene/Q)409665536361427
7EDF R&DZumbrota (Blue Gene/Q)409665536361427
7Victorian Life Sciences Computation InitiativeAvoca (Blue Gene/Q)409665536361427

See also

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References

  1. 1 2 The Exascale Report (March 15, 2012). "The Case for the Graph 500 – Really Fast or Really Productive? Pick One". Inside HPC.
  2. 1 2 "June 2014 | Graph 500". Archived from the original on June 28, 2014. Retrieved June 26, 2014.
  3. ↑ Ueno, Koji; Suzumura, Toyotaro; Maruyama, Naoya; Fujisawa, Katsuki; Matsuoka, Satoshi (2016). "Extreme scale breadth-first search on supercomputers". 2016 IEEE International Conference on Big Data (Big Data). pp. 1040–1047. doi:10.1109/BigData.2016.7840705. ISBN   978-1-4673-9005-7. S2CID   8680200.
  4. ↑ Performance Evaluation of Graph500 on Large-Scale Distributed Environment // IEEE IISWC 2011, Austin, TX; presentation
  5. ↑ "Graph500: адекватный рейтинг" (in Russian). Open Systems #1 2011.
  6. ↑ Ueno, K.; Suzumura, T.; Maruyama, N.; Fujisawa, K.; Matsuoka, S. (December 1, 2016). "Extreme scale breadth-first search on supercomputers". 2016 IEEE International Conference on Big Data (Big Data). pp. 1040–1047. doi:10.1109/BigData.2016.7840705. ISBN   978-1-4673-9005-7. S2CID   8680200.
  7. ↑ "Complete Results - Graph 500". June 14, 2017. Retrieved July 21, 2023.
  8. ↑ "November 2022; Graph 500". June 14, 2017. Retrieved November 18, 2022.
  9. ↑ "Fujitsu and RIKEN Take First Place in Graph500 Ranking with Supercomputer Fugaku". HPCwire. June 23, 2020. Retrieved August 8, 2020.
  10. ↑ "June 2016 | Graph 500". Archived from the original on June 24, 2016. Retrieved July 6, 2016.
  11. ↑ "June 2013 | Graph 500". Archived from the original on June 21, 2013. Retrieved June 19, 2013.
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