Towards tightly-coupled datacenter with free-space optical links

Yao Hu, Hiroki Matsutani, Hiroaki Hara, Hideharu Amano, Ikki Fujiwara, Michihiro Koibuchi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


Clean slate design of computing system is an emerging topic for continuing growth of warehouse-scale computers. A famous custom design is rackscale (RS) computing by considering a single rack as a computer that consists of a number of processors, storages and accelerators customized to a target application. In RS, each user is expected to occupy a single or more than one rack. However, new users frequently appear and the users often change their application scales and parameters that would require different numbers of processors, storages and accelerators in a rack. The reconfiguration of interconnection networks on their components is potentially needed to support the above demand in RS. In this context, we propose the inter-rackscale (IRS) architecture that disaggregates various hardware resources into different racks according to their own areas. The heart of IRS is to use free-space optics (FSO) for tightly-coupled connections between processors, storages and GPUS distributed in different racks, by swapping endpoints of FSO links to change network topologies. Through a large IRS system simulation, we show that by utilizing FSO links for interconnection between racks, the FSO-equipped IRS architecture can provide comparable communication latency between heterogeneous resources to that of the counterpart RS architecture. A utilization of 3 FSO terminals per rack can improve at least 87.34% of inter-CPU/SSD(GPU) communication over Fat-tree and improve at least 92.18% of that over 2-D Torus. We verify the advantages of IRS over RS in job scheduling performance..

Original languageEnglish
Title of host publication2017 International Conference on Cloud and Big Data Computing, ICCBDC 2017
PublisherAssociation for Computing Machinery
Number of pages7
ISBN (Electronic)9781450353434
Publication statusPublished - 2017 Sept 17
Event2017 International Conference on Cloud and Big Data Computing, ICCBDC 2017 - London, United Kingdom
Duration: 2017 Sept 172017 Sept 19

Publication series

NameACM International Conference Proceeding Series


Other2017 International Conference on Cloud and Big Data Computing, ICCBDC 2017
Country/TerritoryUnited Kingdom


  • Datacenter
  • Free-space optics
  • Interconnection network
  • Job scheduling
  • Rackscale architecture

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications


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