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State-of-the-art parallel systems employ a huge number of computing nodes that are connected by an interconnection network. An interconnection network (ICN) plays an important role in a parallel system, since it is responsible to communication capability. In general, an ICN shows non-linear phenomena in its communication performance, most of them are caused by congestion. Thus, designing a large-scale parallel system requires sufficient discussions through repetitive simulation runs. This causes another problem in simulating large-scale systems within a reasonable cost. This paper shows a promising solution by introducing the cellular automata concept, which is originated in our prior work. Assuming 2D-torus topologies for simplification of discussion, this paper discusses fundamental design of router functions in terms of cellular automata, data structure of packets, alternative modeling of a router function, and miscellaneous optimization. The proposed models have a good affinity to GPGPU technology and, as representative speed-up results, the GPU-based simulator accelerates simulation upto about 1264 times from sequential execution on a single CPU. Furthermore, since the proposed models are applicable in the shared memory model, multithread implementation of the proposed methods achieve about 162 times speed-ups at the maximum.

- Publication
- IEICE TRANSACTIONS on Information Vol.E102-D No.1 pp.52-74

- Publication Date
- 2019/01/01

- Publicized
- 2018/10/05

- Online ISSN
- 1745-1361

- DOI
- 10.1587/transinf.2018EDP7131

- Type of Manuscript
- PAPER

- Category
- Computer System

Takashi YOKOTA

Utsunomiya University

Kanemitsu OOTSU

Utsunomiya University

Takeshi OHKAWA

Utsunomiya University

The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.

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Takashi YOKOTA, Kanemitsu OOTSU, Takeshi OHKAWA, "Accelerating Large-Scale Interconnection Network Simulation by Cellular Automata Concept" in IEICE TRANSACTIONS on Information,
vol. E102-D, no. 1, pp. 52-74, January 2019, doi: 10.1587/transinf.2018EDP7131.

Abstract: State-of-the-art parallel systems employ a huge number of computing nodes that are connected by an interconnection network. An interconnection network (ICN) plays an important role in a parallel system, since it is responsible to communication capability. In general, an ICN shows non-linear phenomena in its communication performance, most of them are caused by congestion. Thus, designing a large-scale parallel system requires sufficient discussions through repetitive simulation runs. This causes another problem in simulating large-scale systems within a reasonable cost. This paper shows a promising solution by introducing the cellular automata concept, which is originated in our prior work. Assuming 2D-torus topologies for simplification of discussion, this paper discusses fundamental design of router functions in terms of cellular automata, data structure of packets, alternative modeling of a router function, and miscellaneous optimization. The proposed models have a good affinity to GPGPU technology and, as representative speed-up results, the GPU-based simulator accelerates simulation upto about 1264 times from sequential execution on a single CPU. Furthermore, since the proposed models are applicable in the shared memory model, multithread implementation of the proposed methods achieve about 162 times speed-ups at the maximum.

URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2018EDP7131/_p

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@ARTICLE{e102-d_1_52,

author={Takashi YOKOTA, Kanemitsu OOTSU, Takeshi OHKAWA, },

journal={IEICE TRANSACTIONS on Information},

title={Accelerating Large-Scale Interconnection Network Simulation by Cellular Automata Concept},

year={2019},

volume={E102-D},

number={1},

pages={52-74},

abstract={State-of-the-art parallel systems employ a huge number of computing nodes that are connected by an interconnection network. An interconnection network (ICN) plays an important role in a parallel system, since it is responsible to communication capability. In general, an ICN shows non-linear phenomena in its communication performance, most of them are caused by congestion. Thus, designing a large-scale parallel system requires sufficient discussions through repetitive simulation runs. This causes another problem in simulating large-scale systems within a reasonable cost. This paper shows a promising solution by introducing the cellular automata concept, which is originated in our prior work. Assuming 2D-torus topologies for simplification of discussion, this paper discusses fundamental design of router functions in terms of cellular automata, data structure of packets, alternative modeling of a router function, and miscellaneous optimization. The proposed models have a good affinity to GPGPU technology and, as representative speed-up results, the GPU-based simulator accelerates simulation upto about 1264 times from sequential execution on a single CPU. Furthermore, since the proposed models are applicable in the shared memory model, multithread implementation of the proposed methods achieve about 162 times speed-ups at the maximum.},

keywords={},

doi={10.1587/transinf.2018EDP7131},

ISSN={1745-1361},

month={January},}

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TY - JOUR

TI - Accelerating Large-Scale Interconnection Network Simulation by Cellular Automata Concept

T2 - IEICE TRANSACTIONS on Information

SP - 52

EP - 74

AU - Takashi YOKOTA

AU - Kanemitsu OOTSU

AU - Takeshi OHKAWA

PY - 2019

DO - 10.1587/transinf.2018EDP7131

JO - IEICE TRANSACTIONS on Information

SN - 1745-1361

VL - E102-D

IS - 1

JA - IEICE TRANSACTIONS on Information

Y1 - January 2019

AB - State-of-the-art parallel systems employ a huge number of computing nodes that are connected by an interconnection network. An interconnection network (ICN) plays an important role in a parallel system, since it is responsible to communication capability. In general, an ICN shows non-linear phenomena in its communication performance, most of them are caused by congestion. Thus, designing a large-scale parallel system requires sufficient discussions through repetitive simulation runs. This causes another problem in simulating large-scale systems within a reasonable cost. This paper shows a promising solution by introducing the cellular automata concept, which is originated in our prior work. Assuming 2D-torus topologies for simplification of discussion, this paper discusses fundamental design of router functions in terms of cellular automata, data structure of packets, alternative modeling of a router function, and miscellaneous optimization. The proposed models have a good affinity to GPGPU technology and, as representative speed-up results, the GPU-based simulator accelerates simulation upto about 1264 times from sequential execution on a single CPU. Furthermore, since the proposed models are applicable in the shared memory model, multithread implementation of the proposed methods achieve about 162 times speed-ups at the maximum.

ER -