ABSTRACT
We propose a multi-plane isomorphic network that increases network throughput and reduces network latency by effectively configuring multi-plane networks. In the proposed network, each plane adopts the same graph topology but different switch-to-switch connections. We evaluate the dual-plane isomorphic hypercube network by graph analysis and cycle level simulation. Results of the graph analysis show that the dual-plane isomorphic 8-hypercube reduces the average shortest path length by 22% and improves throughput by 28% compared with the dual-plane hypercube. Similar improvements are confirmed from the results of the cycle level simulation. We also examine the dual-plane isomorphic folded-hypercube network. Finally, we discuss the effect of longer cable length caused by the isomorphic network on the network cost and latency.
- N. R. Adiga, G. Almasi, G. S. Almasi, Y. Aridor, R. Barik, D. Beece, R. Bellofatto, G. Bhanot, R. Bickford, M. Blumrich, A. A. Bright, J. Brunheroto, C. Cascaval, J. Castanos, W. Chan, L. Ceze, P. Coteus, S. Chatterjee, D. Chen, G. Chiu, T. M. Cipolla, P. Crumley, K. M. Desai, A. Deutsch, T. Domany, M. B. Dombrowa, W. Donath, M. Eleftheriou, C. Erway, J. Esch, B. Fitch, J. Gagliano, A. Gara, R. Garg, R. Germain, M. E. Giampapa, B. Gopalsamy, J. Gunnels, M. Gupta, F. Gustavson, S. Hall, R. A. Haring, D. Heidel, P. Heidelberger, L. M. Herger, D. Hoenicke, R. D. Jackson, T. Jamal-Eddine, G. V. Kopcsay, E. Krevat, M. P. Kurhekar, A. P. Lanzetta, D. Lieber, L. K. Liu, M. Lu, M. Mendell, A. Misra, Y. Moatti, L. Mok, J. E. Moreira, B. J. Nathanson, M. Newton, M. Ohmacht, A. Oliner, V. Pandit, R. B. Pudota, R. Rand, R. Regan, B. Rubin, A. Ruehli, S. Rus, R. K. Sahoo, A. Sanomiya, E. Schenfeld, M. Sharma, E. Shmueli, S. Singh, P. Song, V. Srinivasan, B. D. Steinmacher-Burow, K. Strauss, C. Surovic, R. Swetz, T. Takken, R. B. Tremaine, M. Tsao, A. R. Umamaheshwaran, P. Verma, P. Vranas, T. J. C. Ward, M. Wazlowski, W. Barrett, C. Engel, B. Drehmel, B. Hilgart, D. Hill, F. Kasemkhani, D. Krolak, C. T. Li, T. Liebsch, J. Marcella, A. Muff, A. Okomo, M. Rouse, A. Schram, M. Tubbs, G. Ulsh, C. Wait, J. Wittrup, M. Bae, K. Dockser, L. Kissel, M. K. Seager, J. S. Vetter, and K. Yates. 2002. An Overview of the BlueGene/L Supercomputer. In SC '02: Proceedings of the 2002 ACM/IEEE Conference on Supercomputing. 60--60. https://doi.org/10.1109/SC.2002.10017Google ScholarCross Ref
- Kevin J. Barker, Alan Benner, Ray Hoare, Adolfy Hoisie, Alex K. Jones, Darren K. Kerbyson, Dan Li, Rami Melhem, Ram Rajamony, Eugen Schenfeld, Shuyi Shao, Craig Stunkel, and Peter Walker. 2005. On the Feasibility of Optical Circuit Switching for High Performance Computing Systems. In Proceedings of the 2005 ACM/IEEE Conference on Supercomputing (SC '05). IEEE Computer Society, Washington, DC, USA, 16--. https://doi.org/10.1109/SC.2005.48Google ScholarDigital Library
- Maciej Besta and Torsten Hoefler. 2014. Slim Fly: A Cost Effective Low-diameter Network Topology. In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC '14). IEEE Press, Piscataway, NJ, USA, 348--359. https://doi.org/10.1109/SC.2014.34Google ScholarDigital Library
- Salvador Coll, Eitan Frachtenberg, Fabrizio Petrini, Adolfy Hoisie, and Leonid Gurvits. 2001. Using multi-rail networks in high-performance clusters. In Proceedings 2001 IEEE International Conference on Cluster Computing. 15--24. https://doi.org/10.1109/CLUSTR.2001.959946Google ScholarCross Ref
- A. R. Curtis, T. Carpenter, M. Elsheikh, A. LÃşpez-Ortiz, and S. Keshav. 2012. REWIRE: An optimization-based framework for unstructured data center network design. In 2012 Proceedings IEEE INFOCOM. 1116--1124. https://doi.org/10.1109/INFCOM.2012.6195470Google ScholarCross Ref
- COLFAX DIRECT. 2019.. Retrieved July 31, 2019 from https://colfaxdirect.com/store/pc/home.aspGoogle Scholar
- Hewlett Packard Enterprise. 2019. HPE SGI 8600 System. Retrieved July 31, 2019 from https://www.hpe.com/jp/ja/product-catalog/detail/pip.hpe-sgi-8600-system.1010032504.htmlGoogle Scholar
- Nikhil Jain, Abhinav Bhatele, Louis H. Howell, David Böhme, Ian Karlin, Edgar A. León, Misbah Mubarak, Noah Wolfe, Todd Gamblin, and Matthew L. Leininger. 2017. Predicting the Performance Impact of Different Fat-tree Configurations. In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC '17). ACM, New York, NY, USA, Article 50, 13 pages. https://doi.org/10.1145/3126908.3126967Google ScholarDigital Library
- John Kim, William J. Dally, and Dennis Abts. 2007. Flattened Butterfly: A Cost-efficient Topology for High-radix Networks. In Proceedings of the 34th Annual International Symposium on Computer Architecture (ISCA '07). ACM, New York, NY, USA, 126--137. https://doi.org/10.1145/1250662.1250679Google ScholarDigital Library
- John Kim, Wiliam J. Dally, Steve Scott, and Dennis Abts. 2008. Technology-Driven, Highly-Scalable Dragonfly Topology. In Proceedings of the 35th Annual International Symposium on Computer Architecture (ISCA '08). IEEE Computer Society, Washington, DC, USA, 77--88. https://doi.org/10.1109/ISCA.2008.19Google ScholarDigital Library
- Michihiro Koibuchi, Hiroki Matsutani, Hideharu Amano, D. Frank Hsu, and Henri Casanova. 2012. A Case for Random Shortcut Topologies for HPC Interconnects. In Proceedings of the 39th Annual International Symposium on Computer Architecture (ISCA '12). IEEE Computer Society, Washington, DC, USA, 177--188. http://dl.acm.org/citation.cfm?id=2337159.2337179Google ScholarDigital Library
- Charles E. Leiserson. 1985. Fat-trees: Universal Networks for Hardware-efficient Supercomputing. IEEE Trans. Comput. 34, 10 (Oct. 1985), 892--901. http://dl.acm.org/citation.cfm?id=4492.4495Google ScholarDigital Library
- Jiuxing Liu, Abhinav Vishnu, and Dhabaleswar K. Panda. 2004. Building Multirail InfiniBand Clusters: MPI-Level Design and Performance Evaluation. In Proceedings of the 2004 ACM/IEEE Conference on Supercomputing (SC '04). IEEE Computer Society, Washington, DC, USA, 33--. https://doi.org/10.1109/SC.2004.15Google ScholarDigital Library
- Satoshi Matsuoka. 2017. TSUBAME3 and ABCI: Supercomputer Architectures for HPC and AI/BD Convergence. Retrieved July 31, 2019 from http://on-demand. gputechconf.com/gtc/2017/presentation/S7813-Matsuoka-scalable.pdf.pdfGoogle Scholar
- Jayaram Mudigonda, Praveen Yalagandula, and Jeffrey C. Mogul. 2011. Taming the Flying Cable Monster: A Topology Design and Optimization Framework for Data-center Networks. In Proceedings of the 2011 USENIX Conference on USENIX Annual Technical Conference (USENIXATC'11). USENIX Association, Berkeley, CA, USA, 8--8. http://dl.acm.org/citation.cfm?id=2002181.2002189Google Scholar
- NASA. 2019. Pleiades Supercomputer. Retrieved July 31, 2019 from https://www.nas.nasa.gov/hecc/resources/pleiades.htmlGoogle Scholar
- Tom Papatheodore. 2018. Summit System Overview. Retrieved July 31, 2019 from https://www.olcf.ornl.gov/wp-content/uploads/2018/05/Intro_Summit_System_Overview.pdfGoogle Scholar
- Mellanox Technologies. 2017. Deploying HPC Cluster with Mellanox InfiniBand Interconnect Solutions. Retrieved July 31, 2019 from http://www.mellanox.com/related-docs/solutions/deploying-hpc-cluster-with-mellanox-infiniband-interconnect-solutions-archive.pdfGoogle Scholar
- Mellanox Technologies. 2018. SB7700 InfiniBand EDR 100Gb/s Switch System. Retrieved July 31, 2019 from http://www.mellanox.com/related-docs/prod_ib_switch_systems/pb_sb7700.pdfGoogle Scholar
- Noah Wolfe, Misbah Mubarak, Nikhil Jain, Jens Domke, Abhinav Bhatele, Christopher D. Carothers, and Robert B. Ross. 2017. Preliminary Performance Analysis of Multi-rail Fat-tree Networks. In Proceedings of the 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid '17). IEEE Press, Piscataway, NJ, USA, 258--261. https://doi.org/10.1109/CCGRID.2017.102Google ScholarDigital Library
Index Terms
- Dual-Plane Isomorphic Hypercube Network
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