Overview of Korea eScience Project including Aerospace R

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Overview of Korea e-Science Project including
Aerospace RD Activities
Dr. Kum Won Cho e-Science Division KISTI
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Overview of KISTI
a Government supported Research Institute to
serve Korea Scientists and Engineers with
Scientific/Industrial Data Bases, Research
Networks Supercomputing Infrastructure

• Organization8 divisions, 3 centers,
• 3 branch offices
• Personnel about 340 regular staffs,
• 100 part timers, and 100 related workers

• Annual revenue about USD100M,
• mostly funded by the central government

1967
1969
1998
1988
2001
ETRI (Electronics and Telecommunications
Research Institute)
SERI (Systems Engineering Research Institute)
KISTI (Korea Institute of Science and Technology
Information)
KIST(Korea Institute of Science Technology)
KISTI Supercomputing Center is responsible for
national e-infrastructure of Korea
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History of KISTI Supercomputers
2 GFlops
115 GFlops
2.85 TFlops
240 GFlops
Cray-2S 1st SC System in Korea until 1993
CAVE SGI Onyx3400
Cray T3E until 2002
NEC SX-5
SC 45
NEC SX-6
TeraCluster
1988
1993
2000
1997
2001
2002
2003
2007
2008
5.2 TF
8.6TF
2GF
16GF
242GF
131GF
35TF
280TF
786GF
PC Cluster 128node
Cray C90 2nd SC System in Korea until 2001
IBM p690
IBM p690 3.7TF
HP GS320 HPC160/320
4.36 TFlops
435 GFlops
111 GFlops
16 GFlops
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KISTIs 4th Supercomputer

• MPP System (1st phase)
• SUN C48 188 Nodes
• Target Performance 24 Tflops
• Internal Disk 8 GB Flash or Micro Drive
• Infiniband 4x DDR 20Gbps
• External Storage 200TBytes
• 2nd phase
• 250 TFlops Target performance
• About 21,000 cores
• 1.3 PBytes external storage

• SMP System
• IBM p595 p6
• 10 (1st), 24 nodes(2nd)
• Target Performance36TFlops
• Internal Disk 1,17 GB
• External Storage 63TB(1st), 273 TB(2nd)
• HPS(1st) interconnect network Infiniband 4x DDR
  (2nd)

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New Visualization System (plan)

• ? All KISTIs visualization systems have direct
  connection to GLORIAD(glo-kr), whose bandwidth is
  10 Gbps

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National Research Network

• KREONET is the national science research
  network of Korea, funded by MOST since 1988
• 20Gbps backbone, 1 10Gbps access networks

• GLORIAD (GLObal RIng Network for Advanced
  Applications Development) with 10/40Gbps Optical
  lambda networking
• Global Ring topology for advanced science
  applications
• GLORIAD Consortia Korea, USA, China, Russia,
  Canada, the Netherlands and 5 Nordic Countries
  (11 nations)
• Essential to support advanced application
  developments
• HEP, ITER, Astronomy, Earth System,
  Bio-Medical, HDTV etc.
• National GLORIAD project (funded by MOST of KOREA)

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KREONET Hybrid Networks (Packet Switched and
Optical Switched)
US
10G
Seoul
5G
5G
10G
20G
ChoongBook
Inchean
5G
5G
Pohang
5G
Suwan
5G
KyungBook
DaeJeon
Cheanahn
Busan
10G
5G
Changwan
Junju
10G
HK
1G
GwnagJu
KIX, DACOM IX, KT IX, BIX,6NGIX
2.5G
KREONet2 Members 300 Backbone 14
GigaPOPs(20G5G) Over 1G access links 50
JEJU
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GLIF Playground GOLEs Lambdas GOLEs GLORIAD
Lightpath Exchange
GOLE
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Korea e-Science Program (Global Science Gateway
through KISTI)
CE
(KISTI Top Brand Project, MOST)
Middleware
(MOST)
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Ref KGrid National Grid infrastructure
Middleware (Funded by MIC)

• GRASP (Grid Resource Allocation Services
  Package)
• GAIS (Grid Advanced Information System)
• MPICH-GX (MPICH-Grid eXtensible)

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Development of Cyber Environment SW

• Develop core common software technology required
  for building the e-Science environment

• S/W that can be used in common for development of
  various e-Science environments like BT and NT
• - Use selectively for building individual
  e-Science environments
• - Workflow, service framework, portal framework
  and visualization technology

• Service Framework

• Workbench

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Visualization tools

• Data Compression and the Volume
• rendering for e-Science application
• - high resolution (512X512X512) Medical
• image data rendering ( 2Frames/sec)
• US NSF funded OptIPuter project partner
• 3D Volume data (w/ wavelet compression)
• was demonstrated at iGrid2005

Develop high efficiency data compression method
using wavelet - Random access, real time
restoration support visualization application
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Application 1 e-AIRS(e-Science Aerospace
Integrated Research System)

• Next-generation RD Paradigm Combination of
  ICT and Space Tech.
• Construction of Space Tech. CI/CE for
  Large-scale Research Activities
• Co-use of Research Facilities and Data, Cyber
  Education

e-AIRSViz
e-AIRSMesh

• Multi-disciplinary Research
• Integration of Computation and
• Experiment
• Large-scale Computation and Huge Data
• Korea Aerospace-Net Community

e-AIRSSolver
e-AIRSW/T
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Aerospace Gateway Working Group

• Sharing information, tool and etc on e-Science
  Environment
• - Development of Cyber Environment
• - Grid Computing, Visualization and etc
• - Collaboration Research(CFD, CSD and etc)
• Collaboration partner
• - Korea KISTI
•  - USA NCSA, TACC, AHPCSC, Texas Tech Univ,
  LSU CCT
•    - Germany DLR, HLRS(Plan)
•   - Japan JAXA(Plan)
• - Taiwan NCHC
• - Thailand NECTEC
• Write a white paper till this year
• Submit funding proposal to government agency
• Planning to host International Workshop in 2009

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2007
2008
Seoul
??
??
?? (KISTI)
(KISTI)
?? TIGRE
PRAGMA
??
??
PRAGMA
??
?? AIST
?? AIST
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Application 2 MGrid Glyco-MGrid

• Development of Research CI/CE to Share and Reuse
  of Computing
• Resources/Resulting Data/information on the
  Molecular Simulations
• Construction of Database for the Simulations of
  Glycoconjugates

• Development Constructuin of e-Science
• Research Infra to Share, Search, and Re-
• simulate the Data between Researchers
• Constructed Glycoconjugates Database in
• WWW

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Application 3 Tele-Science (High Voltage
Electron Microscope)

• Establishment of the worlds best tele-HVEM
  system enabled data
• survey, store, management, on-line data
  analysis remotely.
• Realization of the virtual laboratory

• To increase the efficiency of the costly
• national equipment by a leading-edge
• technology
• To develop the e-Science service system
• as a standard for the integration of the
• other high-end instrumentation.

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Application 4 Biology/Bio-informatics

• Computational prediction from the entire human
  genome for
• drug discovery
• Complete public sharing of all the calculated
  data from genes,
• proteins and chemicals

• Development and operation of Grid computing
• system for effective processing of life
  science
• data and/or medicinal/chemical information
• Practical application through open web
  service and open standard DB

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Application 5 Weather Information System

• Efficient and Standardized Data Access through
  Web Services
• Agent based Data Management of SAM file
• Dynamic Indexing Cataloging

• The activating prototype of WIS requires
• efficiency test and confirmation of stability.
• We need the generalized infrastructure to
• operate the atmospheric model for every
• researcher.

Manager Center Mypage
Meta Data Search
Data Search
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Application 6 HEP
H/W 64 CPU / 5TB 08 50nodes/50TB
- ALICE(CERN) Tier2 Data Center KISTI-CNRS MoU
(April 07) - CDF(Fermi Lab) Pacific Region Data
Center KISTI-Fermi MoU(March 07)
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Global Partnership
About 30 institutions from 20 countries
GLORIAD(10G)
Collaboration
China, Japan, US, Taiwan, India etc.
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PRAGMA Grid Testbed
JLU China
AIST OsakaU UTsukuba TITech Japan
NCSA USA
CNIC GUCAS China
AIST
CNIC
UZurich Switzerland
KISTI Korea
BU USA
UUtah USA
SDSC USA
SDSC
LZU China
ASGC NCHC Taiwan
UMC USA
ASGC
CICESE Mexico
UoHyd India
CUHK HongKong
UNAM Mexico
NECTEC ThaiGrid Thailand
NECTEC ThaiGrid
IOIT-HCM Vietnam
ASURC Costa Rica
APAC QUT Australia
MIMOS USM Malaysia
BII IHPC NGO Singapore
UCN Chile
BESTGrid New Zealand
NGO
UChile Chile
MU Australia
32 Clusters from 29 institutions in 14
countries/regions ( 7 in preparation)
7 gfarm sites
Source Cindy Zheng
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Performance Analysis and Optimization of AMGA for
the WISDOM environment

• Sunil Ahn
• KISTI e-Science Department

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I. Introduction

• What is WISDOM ?
• Grid-enabled virtual screening initiative
• Search for new drug using grid infrastructure
• WISDOM environment
• Producing a large amount of data in a limited
  time with a minimal human cost during the data
  challenge.

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I. Introduction

• What is AMGA (ARDA Metadata Grid Application) ?
• AMGA is the Metadata Catalogue for gLite
• AMGA is included in gLite release 3.1
• AMGA in preproduction within several projects
• LHCb and ATLAS GANGA
• EGEE BioMed applications
• medical images metadata
• Master/Slave replication model is supported

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II. AMGA Performance Analysis

• Optimization (DB Connection Pool)
• Throughput limitation in WAN
• Load balanced AMGA Throughput is limited by the
  number of DB connections in WAN
• DB connection pool integrated into AMGA
• Results
• linear scale-up almost up to the limit of direct
  DB access in WAN too, improving AMGA throughput
  2.6 3 times with 3 AMGAs

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II. AMGA Performance Analysis

• Optimization (Load balancing)
• linear scale-up almost up to the limit of direct
  DB access in LAN
• 2.6 3 times with 3 AMGA servers
• 1.8 times in WAN

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• JSDL-PS APDL

Young-Kyoon Suh, Byungsang Kim
KISTI e-Science Division
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Why JSDL ? - Grid Heterogeneity

• Different middleware adopt different formats for
  the description of applications and their
  associated resources (JDL, RSL), and for their
  subsequent execution to a Grid.
• A Number of different data storage resources are
  also relevant for management and transfer of
  data. e.g. GsiFTP, SRB, SRM, WebDav, (S)FTP.

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JSDL-PS, draft-ogf-jsdl-ext-paramsweep

• Last Edited on 06 June 2007
• Last Edited By Michel Drescher, Fujitsu

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Parameters in an application
endowed.inp
AMACH 0.6d0 RE 5.0d6 AOA -6.0d0 TOL
1.0d-4 TINF 290.0d0 CFL 0.5d0 IERRWRT
1 TOTPES 6 NSEULER -1 KWKEBL 0 INTWRT2
50 ITMAX2 10000 STEADINESS 0

• Parameters in an application
• Parametric value itself
• String or numerical value
• Data file indicator
• Need to stage-in/out from source to destination
• Parameter file indicator
• Need to identify parameters in that file
• Example Fluid Dynamic software
• 2D_Comp
• Argument o 0 -mesh NACA0012.msh parm
  endowed.inp
• Example Bioinformatics
• AutoDock
• Argument -p ind.dpf l ind.dlg
• Optimized-folding
• Argument ltdata file namegt ltrandom seed gt

seed random types CNOH atom type names fld
4phv.nbc_maps.fld grid data file map
4phv.nbc_C.map C-atomic affinity map map
4phv.nbc_N.map N-atomic affinity map map
4phv.nbc_O.map O-atomic affinity map map
4phv.nbc_H.map H-atomic affinity map map
4phv.nbc_e.map electrostatics map move
xk263pm3.pdbq small molecule about -5.452
-8.626 -0.082 small molecule center tran0
-5.452 -8.626 -0.082 initial coordinates/A . .
ind.dpf
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Use Case Application

• Application 2D_Comp
• two-dimensional, compressible flowfield around an
  airfoil
• Geometries (mesh) NACA0012, NACA11412,
  NACA2412, NACA3412, NACA4412
• AOA -6, -2, 2, 6, 10, 14, 18, 20(increment 4)
• Steadiness -1, 0, 1(Static list)
• RE(renold) 5.0e6, 10.0e6(Static list)
• Sweep Method NESTED
• Total 210 jobs at a time

Cl-Lift coefficient Cd-Drag coefficient AOA
Angle of Attack
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APDL

• APDL Version-1.0
• http//schemas.kisti.org/pss/2007/11/apdl
• Dec 2007
• Simplify parameter and sweep element from
  pss-design
• Contain only parameter sweep element
• Sweep both values and parameters in arbitrary
  input files
• they are regarded as arguments of an application
• Contain source/destination URL for transferring
  files or data
• Collaborate with NGS(UK e-Science)

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Thank you for your attention!