Graph500

From Wikipedia, the free encyclopedia
Jump to navigation Jump to search

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).

Richard Murphy from Sandia, 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[edit]

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 two 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). 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]

  • serial high-level in GNU Octave
  • serial low-level in C
  • parallel C version with usage of OpenMP
  • two versions for Cray-XMT
  • basic MPI version (with MPI-1 functions)
  • optimized MPI version (with MPI-2 one-sided communications)

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

Top 10 ranking[edit]

2016[edit]

According to June 2016 release of the list:[7]

Rank Site Machine (architecture) Number of nodes Number of cores Problem scale GTEPS
1 Riken Advanced Institute for Computational Science K computer (Fujitsu custom) 82944 663552 40 38621.4
2 National Supercomputing Center in Wuxi Sunway TaihuLight (NRCPC - Sunway MPP) 40768 10599680 40 23755.7
3 Lawrence Livermore National Laboratory IBM Sequoia (Blue Gene/Q) 98304 1572864 41 23751
4 Argonne National Laboratory IBM Mira (Blue Gene/Q) 49152 786432 40 14982
5 Forschungszentrum Jülich JUQUEEN (Blue Gene/Q) 16384 262144 38 5848
6 CINECA Fermi (Blue Gene/Q) 8192 131072 37 2567
7 Changsha, China Tianhe-2 (NUDT custom) 8192 196608 36 2061.48
8 CNRS/IDRIS-GENCI Turing (Blue Gene/Q) 4096 65536 36 1427
8 Science and Technology Facilities Council – Daresbury Laboratory Blue Joule (Blue Gene/Q) 4096 65536 36 1427
8 University of Edinburgh DIRAC (Blue Gene/Q) 4096 65536 36 1427
8 EDF R&D Zumbrota (Blue Gene/Q) 4096 65536 36 1427
8 Victorian Life Sciences Computation Initiative Avoca (Blue Gene/Q) 4096 65536 36 1427

2014[edit]

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

Rank Site Machine (Architecture) Number of nodes Number of cores Problem scale GTEPS
1 RIKEN Advanced Institute for Computational Science K computer (Fujitsu custom) 65536 524288 40 17977.1
2 Lawrence Livermore National Laboratory IBM Sequoia (Blue Gene/Q) 65536 1048576 40 16599
3 Argonne National Laboratory IBM Mira (Blue Gene/Q) 49152 786432 40 14328
4 Forschungszentrum Jülich JUQUEEN (Blue Gene/Q) 16384 262144 38 5848
5 CINECA Fermi (Blue Gene/Q) 8192 131072 37 2567
6 Changsha, China Tianhe-2 (NUDT custom) 8192 196608 36 2061.48
7 CNRS/IDRIS-GENCI Turing (Blue Gene/Q) 4096 65536 36 1427
7 Science and Technology Facilities Council - Daresbury Laboratory Blue Joule (Blue Gene/Q) 4096 65536 36 1427
7 University of Edinburgh DIRAC (Blue Gene/Q) 4096 65536 36 1427
7 EDF R&D Zumbrota (Blue Gene/Q) 4096 65536 36 1427
7 Victorian Life Sciences Computation Initiative Avoca (Blue Gene/Q) 4096 65536 36 1427

2013[edit]

According to June 2013 release of the list:[8]

Rank Site Machine (Architecture) Number of nodes Number of cores Problem scale GTEPS
1 Lawrence Livermore National Laboratory IBM Sequoia (Blue Gene/Q) 65536 1048576 40 15363
2 Argonne National Laboratory IBM Mira (Blue Gene/Q) 49152 786432 40 14328
3 Forschungszentrum Jülich JUQUEEN (Blue Gene/Q) 16384 262144 38 5848
4 RIKEN Advanced Institute for Computational Science K computer (Fujitsu custom) 65536 524288 40 5524.12
5 CINECA Fermi (Blue Gene/Q) 8192 131072 37 2567
6 Changsha, China Tianhe-2 (NUDT custom) 8192 196608 36 2061.48
7 CNRS/IDRIS-GENCI Turing (Blue Gene/Q) 4096 65536 36 1427
7 Science and Technology Facilities Council - Daresbury Laboratory Blue Joule (Blue Gene/Q) 4096 65536 36 1427
7 University of Edinburgh DIRAC (Blue Gene/Q) 4096 65536 36 1427
7 EDF R&D Zumbrota (Blue Gene/Q) 4096 65536 36 1427
7 Victorian Life Sciences Computation Initiative Avoca (Blue Gene/Q) 4096 65536 36 1427

See also[edit]

References[edit]

  1. ^ a b The Exascale Report (2012-03-15). "The Case for the Graph 500 – Really Fast or Really Productive? Pick One". Inside HPC. 
  2. ^ a b "Archived copy". Archived from the original on 2014-06-28. Retrieved 2014-06-26. 
  3. ^ http://ieeexplore.ieee.org/abstract/document/7840705/
  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. (2016-12-01). "Extreme scale breadth-first search on supercomputers". 2016 IEEE International Conference on Big Data (Big Data): 1040–1047. doi:10.1109/BigData.2016.7840705. 
  7. ^ http://www.graph500.org/results_jun_2016
  8. ^ "Archived copy". Archived from the original on 2013-06-21. Retrieved 2013-06-19. 

External links[edit]