development of e-science applications in taiwan
DESCRIPTION
Development of e-Science Applications in Taiwan. Hsin-Yen Chen Hurng-Chun Lee, Wei-Long Ueng and Simon C. Lin ASGC APAN 22 July 1 8 - 22 , Singapore. Exponentail Growth World. Gorden Bell Prize “price performance”. Gordon Bell Prize outpaces Moore’s Law. The Data Deluge. - PowerPoint PPT PresentationTRANSCRIPT
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Development of e-Science Applications in Taiwan
Hsin-Yen Chen Hurng-Chun Lee, Wei-Long Ueng and Simon C. Lin
ASGCAPAN 22
July 18-22, Singapore
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Exponentail Growth World
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Gorden Bell Prize “price performance”
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Gordon Bell Prize outpaces Moore’s Law
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The Data Deluge• A large novel: 1Mbyte; The Bible:5 Mbytes• A Mozart symphony (compressed): 10Mbytes• A digital mammogram: 100Mbytes• OED on CD: 500 Mbytes• Digital movie (compressed): 10 Gbytes• Annual production of refereed journal literature ( 20k journals; 2M a
rticles) : 1Tbytes• Library of Congress: 20 Tbytes• The Internet Archive ( 10 B pages; From 1996 to 2002): 100Tbyts• Annual production of information (print, film, optical & magnetic m
edia): 1500 to 3000 Pbytes• All Worldwide Telephone communication in 2002: 19.3 ExaBytes• Moore’s Law enables instruments and detectors to generate unpr
ecedented amount of data in all scientific disciplines
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It’s about the Collaboration !
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Any Opportunity for Small Countries?
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Enabling Grids for E-ScienceE
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OSG Participation
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Taiwan’s Thinking
• International collaboration/participation with the global Grid Cyber- and e-Infrastructure is the key
• Our strategy is to use High Energy Physics to drive the Next Generation Grid Infrastructure. No national Grid organization has been established yet!
• We are setting up a new Academia Sinica Grid Computing Centre (ASGC) reorganised from ASCC
• ASGC will provide Grid-based infrastructure, service, e-Science application development, and promote Grid activities in Taiwan
• ASGC is fully supported by Academia Sinica and NSC in Taiwan
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Taiwan signed the first WLCG MoU
• Jos Engelen (CERN CSO) and President YT Lee (Academia Sinica) Signed the WLCG MoU on 9 Dec. 2005 as a Tier-1 Centre for ATLAS and CMS
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Plan for Taiwan Tier-1 Network
Backup PathBackup Pathto T0to T0
Primary Path to T0Primary Path to T0(plan to install 10GE in (plan to install 10GE in 2007)2007)
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LCG and EGEE Grid Sites in theAsia-Pacific Region
4 LCG sites in Taiwan
12 LCG sites in Asia/Pacific
Academia Sinica Grid Computing Centre
Tier-1 Centre for the LHC Computing Grid (LCG)Asian Operations Centre for LCG and EGEECoordinator of the Asia/Pacific Federation in EGEE
AP Federation now shares the e-Infrastructure with WLCG
LCG siteother site
PAEC NCPIslamabad
IHEP Beijing
KNU Daegu
Univ. Melbourne
GOG Singapore
KEK TsukubaICEPP Tokyo
Taipei - ASGC, IPAS NTU, NCU
VECC Kolkata
Tata Inst.Mumbai
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Contributions of ASGC in WLCG
• WLCG Tier1 Center – Collaborating ATLAS & CMS teams (NCU, NTU, IPAS) in Taiwan
• Regional Operation Centre and Core Infrastructure Centre• Production CA Services• LCG Technology Development
Data Management Grid Technology Certification & Testing Application Software ARDA (Distribute Analysis) 3D (Distributed Deployment of Database) Operation and Management
Dissemination and Outreach
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Education and TrainingEvent Date Attendant Venue
China Grid LCG Training 16~18 May 2004 40 Beijing, China
ISGC 2004 Tutorial 26 July 2004 50 AS, Taiwan
Grid Workshop 16-18 Aug. 2004 50 Shang-Dong, China
NTHU 22~23 Dec. 2004
110 Shin-Chu, Taiwan
NCKU 9~10 Mar. 2005 80 Tainan, TaiwanISGC 2005 Tutorial 25 Apr. 2005 80 AS, Taiwan
Tung-Hai Univ. June 2005 100 Tai-Chung, Taiwan
EGEE Workshop Aug. 2005 80 20th APAN, Taiwan
EGEE Administrator Workshop
Mar. 2006 40 AS, Taiwan
EGEE Tutorial and ISGC 1~5 May, 2006 80 AS, Taiwan
gLite and the development of EGEE were introduced in all events which are run by ASGC
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Issues of the Grid applications
• Due to the loose coupling nature, distributing application jobs on the Grid is not trivial• extra works are needed concerning the efficient job
handling and result gathering• need also efforts to handle transient network or site
problems• complexities should be hidden and the interface to
end user should be application oriented
• The significant Grid system overhead makes the Grid only benefit to the jobs with long computing time• not suitable for the pilot jobs for decision making
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e-Science Applications in Taiwan
• High Energy Physics: WLCG• Bioinformatics: mpiBLAST-g2• Biomedicine: Distributing AutoDock tasks on the
Grid using DIANE• Digital Archive: Data Grid for Digital Archive Lon
g-term preservation• Atmospheric Science• Geoscience: GeoGrid for data management and
hazards mitigation• Seismology Science• Ecology Research and Monitoring: EcoGrid• SARS Grid: Access Grid Tech.• BioPortal• e-Science Application Framework Development
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• Biomedical goal• accelerating the discovery of novel potent inhibitors thru
minimizing non-productive trial-and-error approaches• improving the efficiency of high throughput screening
• Grid goal• aspect of massive throughput: reproducing a grid-enabled in silico
process (exercised in DC I) with a shorter time of preparation• aspect of interactive feedback: evaluating an alternative light-
weight grid application framework (DIANE)• Grid Resources:
• AuverGrid, BioinfoGrid, EGEE-II, Embrace, & TWGrid
• Problem Size: around 300 K compounds from ZINC database and a chemical combinatorial library, need ~ 137 CPU years in 4 weeks
a world-wide infrastructure providing over than 5,000 CPUs
EGEE Biomed DC II – Large Scale Virtual Screening of Drug Design on the Grid
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T06 (wild type)T06 energy distribution
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-23 -22 -21 -20 -19 -18 -17 -16 -15 -14 -13 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0
kcal/mol
tota
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ber 1f8b
1f8c
2qwe
34.92%
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2.43%
binding energy
docking energy
Kcal/mol
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T01 (E119A)
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-23 -22 -21 -20 -19 -18 -17 -16 -15 -14 -13 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0
kcal/mol
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55%
11.58% binding energy
docking energy
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O
A119O
E119O
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T01 (E119A)T06 (wild type)
code compound R group ΔG_T06 ΔG_T01
1f8b DAN -OH -11.40 -10.17
1f8c 4AM* -NH2 -12.92 -10.18
2qwe GNA (Zanamivir) -NC(NH2)2 -14.76 -12.70
* Oseltamivir is with a 4-amine, too.
GNA
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Web Services-based Grid Infrastructure
• Model the world as a collection of services• Resource descriptions and aggregation• Discovery• Composition• Adaptation & Evolution• Quality of Services: security, performance,
reliability, scalability, …• Workflow (lifecycle management)• Open Source Implementation
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GAPortal Framework Architechure
GAPortal Toolkits
Job RepositoryUser/Grid Proxy
Manager
GAPortal Interface Container
Data Management System
• Layered architecture to improve the usability of Grid Applications
• Two frameworks built on the top of current Grid middleware toProvide friendly graphic user interfaceHandle Grid application logic an efficient wayReduce the efforts of application gridification
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GAPortal: Autodock service
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SRB System Monitoring
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Use LAS (Live Access Server) to access the dataset from the SRB System, and integrate with Google Earth
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TEC DataGrid-based Digital Library
TEC Community LibraryTEC Community Library
DataGrid-based Digital Library• 9 Terabytes of on-line disk• More than 100 Terabytes of tape archive
Outputs
Seismogram Retrieval
Quick Focal Mechanism Determination
Inversion of Slip Distribution on Fault Plane
Waveform Simulation
1999 Chi-Chi Taiwan Earthquake
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Data Requesting System
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SeisGrid ArchitectureSeisGrid Architecture
Web-Based Portal User InterfaceWeb-Based Portal User Interface
SRB-based Digital LibrarySRB-based Digital Library
Job repositoryJob repository User/GridProxy Manager
User/GridProxy Manager
Virtual QueuingSystem
Virtual QueuingSystem
Grid AgentGrid Agent
Grid Computing ElementGrid Computing Element
C
C
C
C
CWB
C
C
C
C
IESASSensors
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Industrial Program
• NSC-Quanta Collaboration• To help Quanta Blade System have best performance for HPC
and Grid Computing• Quanta is the largest Notebook manufacturer in the world• Participants: AS, NTU, NCTU, NTHU, NCHC• Scientific Research Disciplines: Material Science, Nano-Techn
ology, Computational Chemistry, Bioinformatics, Engineering, etc.
• Microsoft Collaboration• Enable MS CCS been the CE (gLite)
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Conclusion
• Critical mass decides which Grid technology/system to prevail; Collaboration, Data and Complexity Reduction ar the main themes
• We are about to witness Data Deluge in all disciplines of e-Sciences
• Unprecedented way to collaborate on day-to-day basis will change the sociology of academia life, eco-system of business world and eventually every one in the society
• It is about a new paradigm of collaboration , data and computing will outgrow each of us. Together, we will achieve goals not possible individually!
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Thank Your attention!