PETFLOW
a project towards an ultra parallel synergy internet system
in scientific applications
Cybermedia Center, Osaka University, JapanPETAFLOW CLOUD

It is no falsehood to state that‘current society and scienceattempt to deal with increasing
amounts of data’ . Today,
peta-scale data are commonly
gathered as well as generated
thanks to the continuous
development of measurement
technologies and computational
Fig.1 (Top) :r e sour c es i n d i v er se f iel ds o f
The oral flow-sound simulation inpronunciation of “/s/”science and society. Efficient
processing or generation of peta-scale data requires highperformance computational (HPC) resources which should bemade remotely accessible through long-distance high performance
networking and might be represented thanks to thepetaflow-project, interactive scientific visualization. Consequently,
generation or processing of peta-scale data benefits from theemergence of adequate ‘Information and communication
technologies (ICT)’ with respect to high performance‘computing-networking-visualization’ and their mutual‘awareness’ . It is aimed to develop and validate such ICT
solutions using a transnational high speed research network
between Japan and France connecting ‘GRID5000’ (France) to the‘Naregi’ (Japan) testbed. Data-transfer protocols are aimed to bevalidated on data obtained for a real scientific problem involving
peta-scale data. Due to the medical relevance as well as basic
scientific interest, peta-scale data are obtained from HPC
Computational Fluid Dynamics (CFD) simulations on a vector
supercomputer (NEC SX9 Japan) aiming to predict the airflow
through the upper airways. In addition, CFD simulation outcome isused as an input for aero-acoustic computations (CAA) for
prediction of noise production. Besides the international transfer ofthe generated peta-scale data, scientific visualization of peta-scaledata is aimed on a single PC as well as on a tiled display wall for
3D interactive reconstruction of the flow and noise data. Insummary, the petaflow project aims to contribute to thestate-of-theart of HPC, networking, scientific visualization and theirmutual interactions for peta-scale data, while at the same time it isaimed to contribute to basic research in the fields of CFD and CAA
applied to flow through the upper airways.

There are many kinds of applications which perform numericalsimulations, for example, Virtual Physiological Human (VPH), Realtime Space Weather Simulater, Numerical Whether Simulation,
Nuclear Fusion Simulations, Aerodynamic Research for the Next
Generation Supersonic Transport and Numerical Simulation toTsunami Disaster Prevention. It is necessary to increase the total
amount of computational resources to perform those applications.
It has not been sufficient, however, to do them at all.
This problem arise from such a structure that each researchers orgroups own their own computational resources. This structure ofscientific society is notefficient in terms of several
aspects. We hereby propose“PetaFlow cloud”. PetaFlow
cloud enables researchers orgroups to obtain the solutions
for their concrete objects thatcan be required by several
numerical simulation codes.
PetaFlow cloud has threemain components, first“ P e t a - s c a l e
Networking-Storage”, second
Fig.6(c) : Vision of PetaFlow:“Peta-scale Computing” and・Peta-scale Networking – Storage
・Peta-scale Computing“Peta-scale Visualization”.

PETAFLOW NETWORK・Peta-scale Visualization

PETASCALE VISUALIZATION
Oral flow-sound simulation results in higher-level complexities of3D phenomena and huge volume datasets. Visualizing huge data
often requires use of high-resolution display such that importantfine structures are not missed. It is because the number ofelements forming the huge volume data exceeds resolutions of thenormal LCD displays.
The particle-based volume rendering (PBVR) is one of the effective
rendering techniques applicable to huge volume data. It is basedon the Sabella’ s density emitter model, in which the scalar field ischaracterized as a cloud of opaque and self-emitting particles withthe single-level scattering. PBVR does not require sorting ofelements, being different from the ray-casting method, and soenables us to treat over giga-byte huge data easily.

PetaFlow network testbed is a Layer-2 Virtual Private Network. It
has been developed from NAREGI-Grid5000 network testbed(2006--2009) and constructed with the collaboration of SINET,
JGN2plus, RENATER, GEANT, and MAN LAN. Figure XX shows thetopology of the PetaFlow network testbed. Japanese-side network
is composed of SINET and JGN2plus networks connected at
Tokyo. NII and Kyoto University connect with SINET, and Osaka
University connects with JGN2plus. In order to connect Japanese
research foothold with Grid5000, the international network
operated by SINET is used and extends to MAN LAN. On the otherhand, Grid5000 backbone network is provided by RENATER. The
network from Grid5000 extends to MAN LAN via GEANT.
Paulo Goncalves : INRIA, ENS Lyon, Universit´e de Lyon
Xavier Grandchamp : Gipsa-lab, UMR CNRS 5216, Grenoble Universities
Xavier Pelorson : Gipsa-lab, UMR CNRS 5216, Grenoble Universities
Bruno Raffin : INRIA Grenoble, France
Annemie Van Hirtum : Gipsa-lab, UMR CNRS 5216, Grenoble Universities
Pascale Vicat-Blanc : INRIA, ENS Lyon, Universit´e de Lyon
Ken-ichi Baba : Vizlab, Kyoto University
Julien Cisonni : The Center for Advanced Medical Engineering and Informatics
Yasuo Ebara : Cybermedia Center, Osaka University
Kazunori Nozaki : The Center for Advanced Medical Engineering and Informatics
Hiroyuki Ohsaki : Graduate School of Information Science and Technology
Shigeo Wada : The Center for Advanced Medical Engineering and Informatics
Takuma Kawamura : Vizlab, Kyoto University
Kohji Koyamada : Vizlab, Kyoto University
Eisaku Sakane : National Information and Communication Technology, Japan
Naohisa Sakamoto : Vizlab, Kyoto University
Shinji Shimojo : National Institute of Informatics, Japan

Contact: Petaflow
E-mail: petaflow@ispj.jp

PETFLOW a project towards an ultra parallel synergy internet system in scientific applications

BACKGROUND