TY - GEN
T1 - Towards tightly-coupled datacenter with free-space optical links
AU - Hu, Yao
AU - Matsutani, Hiroki
AU - Hara, Hiroaki
AU - Amano, Hideharu
AU - Fujiwara, Ikki
AU - Koibuchi, Michihiro
N1 - Funding Information:
This research and development work was supported by the MIC/SCOPE #162101001.
Publisher Copyright:
© 2017 Association for Computing Machinery.
PY - 2017/9/17
Y1 - 2017/9/17
N2 - 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..
AB - 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..
KW - Datacenter
KW - Free-space optics
KW - Interconnection network
KW - Job scheduling
KW - Rackscale architecture
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U2 - 10.1145/3141128.3141130
DO - 10.1145/3141128.3141130
M3 - Conference contribution
AN - SCOPUS:85045750710
T3 - ACM International Conference Proceeding Series
SP - 33
EP - 39
BT - 2017 International Conference on Cloud and Big Data Computing, ICCBDC 2017
PB - Association for Computing Machinery
T2 - 2017 International Conference on Cloud and Big Data Computing, ICCBDC 2017
Y2 - 17 September 2017 through 19 September 2017
ER -