Osaka University

PetaFlow ProjectA project towards an ultraparallel synergy
Internet system for scientific applications
Ken-ichi Baba
Cybermedia Center, Osaka University
baba@cmc.osaka-u.ac.jp
November 13, 2012

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Outline of PetaFlow Project JST in Japan and ANR in France
Strategic Japanese-French Cooperative Program on“Information and Communications Technology Including
Computer Sciences”
 Theme:Peta-scale computing with transnational high-speed
networking: application to upper airway flow Duration: Five years from 2009 to 2013
 Leader:Prof. Shinji Shimojo (Japan)
and Dr. Annemie Van Hirtum (France)

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Project Member and Role
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Shinji Shimojo: Leader and Network(Osaka University, JAPAN)
Ken-ichi Baba: Network(Osaka University, JAPAN)
Yuya Hasegawa: Network(Osaka University, JAPAN)
Kohji Koyamada: Visualization(Kyoto University, JAPAN)
Allan Lorant: Visualization(Kyoto University, JAPAN)
Takamichi Nishijima: Network(Osaka University, JAPAN)
Kazunori Nozaki: Application(Osaka University, JAPAN)
Hiroyuki Ohsaki: Network(Osaka University, JAPAN)
Naohisa Sakamoto: Visualization(Kyoto University, JAPAN)
Eisaku Sakane: Network(NII, JAPAN)

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Annemie van Hirtum: Leader andApplication (Gipsa-lab, CNRS, FRANCE)
Alexandre Ancel: Visualization(INRIA, Grenoble University, FRANCE)Yo Fujiso: Application(Gipsa-lab, CNRS, FRANCE)
Paulo Goncalves: Network(ENS Lyon, INRIA, FRANCE)
Matthieu Imbert: Network(ENS Lyon, INRIA, FRANCE)
Pierre Neyron: Visualization(CNRS, Grenoble University, FRANCE)
Anne-Cecile Orgerie: Network(Irisa, CNRS, FRANCE)
Xavier Pelorson: Application(Gipsa-lab, CNRS, FRANCE)
Bruno Raffin: Visualization(INRIA, Grenoble University, FRANCE)

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Background: Reaching Peta-Scale Data
The amount of information handled and the speed ofinformation processing/transmission are reaching petascale.
 In large-scale numerical computations and large-scale
simulations, the number of objects and the amount ofdata generated are reaching peta-scale.
 Similarly, the maximum communication speed of a single
optical fiber reaches several tens of tera-bit/s, and the
bandwidth-delay product of a wide-area optical
network exceeds several peta-bits.

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Background: Toward Synergetic Integration
To realize peta-scale computing, networking, andvisualizing technologies, individual research anddevelopment in each technological field should not suffice.
 Instead, a new ICT paradigm peta-flow computing,which enables peta-scale information processing andcommunication by synergetic integration of threetechnological fields, is desired.

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Our Goal Image A project towards an ultraparallel synergy Internet
system for scientific applications
Obtain high-density datafrom high functional devices
and observational equipments

Volume renderingof large-scale data

Large-scale
Data Transfer

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Analysis by using Super Computer

Visualization by usingcluster computers

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Our aims
 A project towards an ultraparallel synergy Internetsystem for scientific applications
Computational Speech and Oral Science
Peta-scale
analytic data

Network Measurements and Instruments
Grid tools(GridFTP)

Network Middleware
Pixel andVolume stream

Visualization Platform
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PetaFlow Application
Interactive super computing helps oral practitioners (dentists)
to demonstrate a predictive orthodontic surgery or fabrication ofdentures that enable patients to know the change of pronunciation
before his operation, such as tooth movements.
To do this, appropriate HPC
packaging is necessarily so as
to avoid strange movements
due to losing frames, becausethe package includes heavy
simulations, CFD etc. Smooth
and useful computational oral
therapies required the profluent
information flow by using theadvancing internettechnologies
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PetaFlow Visualization (1/3)
 FlowVR– Software environment to allow the user to develop and run highperformance interactive application on distributed computing
environment

J.Allard, V.Gouranton, L.Lecointre, S.Limet, E.Melin, B.Raffin and S.Robert, “FlowVR: a Middleware for Large Scale Virtual Reality Applications”, Euro-Par'04, 2004

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PetaFlow Visualization (2/3)
 Particle-based Volume Rendering– Suitable for large and complex volume datasets– Volume data is represented as particles– Visibility sorting is not required
Opacity

Particle density(Num. of particles within a unit volume)

N.Sakamoto, J.Nonaka, K.Koyamada, and S.Tanaka, Particle-based Volume Rendering, In Proc. of Asia- Pacific Symposium on Visualization 2007, pp.141-144, 20072012/11/13

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PetaFlow Visualization (3/3)
 Remote visualization
system– Large-scalevisualization with
Particle-based
Volume Rendering
technique– PC cluster / Gridapplication
development with
FlowVR

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Remote PC

NetworkLocal PC

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PetaFlow Networking (1/6)
 Network design and construction on Testbed network
 Network measurement and monitoring Traffic control in long-distance broadband network

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PetaFlow Networking (2/6)
The PetaFlow network testbed is a layer-2 virtual private network (VPN). It has
been developed from the NAREGI-Grid5000 network testbed (2006–2009) andconstructed through a collaboration among SINET, JGN-X, RENATER, GEANT, and MAN
LAN. Figure shows the topology of the PetaFlow network testbed. On the Japanese side,the network is composed of SINET and JGN-X networks, which are connected at Tokyo.
The NII and Kyoto University connect with SINET, and Osaka University connects withJGN-X. The international network operated by SINET is used to connect the Japanese
research foothold with Grid5000, and this network extends to MAN LAN (New York, USA)
via GEANT (Europe). The Grid5000 backbone network is provided by RENATER.

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PetaFlow Networking (3/6)
RESO team within PetaFlow

Aim: to guarantee the reliability of thecommunications and data file transfers→ Bandwidth provisioning tools to ensure Quality ofService for real-time applications→ Metrology platform to control the quality of thelink and in particular end-to-end:- latency- throughput- jitterOsaka University

PetaFlow Networking (4/6)
Collaboration with the University of Melbourne
Design a packet capture facility which provides:- accurate timestamps- easy deployment- low costin comparison with current solutions (DAG+GPS, NIC+NTP,…)
Evaluation of this solution on the PetaFlow test-bed tocompare its performance against the DAG cards in atranscontinental context

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PetaFlow Networking (5/6)
A Bandwidth Control Method with Fairness
 High-speed transport protocol– In long-distance broadband network

 Contention problem:– Flows with High-speed transport protocol share same link
– Sum of throughput for each flow sometimes decreases– A particular flow occupies bandwidth and another flow decreases
bandwidth

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PetaFlow Networking (6/6)
A Bandwidth Control Method with Fairness
 We control at the switch in network
 Proposed control method
1. Estimation of the window size
2. Determination of dropped packets

 We can achieve the high value of fairness index of ourproposed method

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Conclusion and Future Work We need to provide world-wide computing environment
 We need collaborative work among application,visualization and networking for such PetaScalecomputing.
 We researched and developed technologies on eachlayer: application, visualization and networking
 Establishment of fundamental technologies for peta-flow
computing such as– Networking-aware computing– Visualizing-aware computing– Networking-aware visualizing Combine these technologies, then ultimately creation ofa new communication paradigm
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Our Presentation at SC12
 Osaka University– Booth #1837– PetaFlow Project and Research on Network

 Kyoto University– Booth #3830– Visualization by PBVR NICT– Booth #4018– Testbed Network Activity

 INRIA– Booth #1209

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Thank you very much for your kind attention.

Presented by

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