e-Science Development of Taiwan Eric Yen & Simon Lin ISGC, - - PowerPoint PPT Presentation

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e-Science Development of Taiwan Eric Yen & Simon Lin ISGC, - - PowerPoint PPT Presentation

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e-Science Development of Taiwan Eric Yen & Simon Lin ISGC, March 2011 Outline Extending Regional Production DCI Conducting e-Science Collaborations Life Science, Earth Science, Environmental Changes, Social Science and HEP

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e-Science Development of Taiwan

Eric Yen & Simon Lin

ISGC, March 2011

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Outline

  • Extending Regional Production DCI
  • Conducting e-Science Collaborations
  • Life Science, Earth Science, Environmental Changes,

Social Science and HEP

  • Technology Development
  • Building New generation DCI and Operation Technology
  • Application Technology
  • Service-Oriented Computing & Cloud
  • Dissemination, Training and International

Collaboration

2

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  • 38 sites in 15 countries
  • > 1,800 Users
  • Average availability > 90% after Nov. 2010
  • 15,000 Cores, 5 PB Disk, 4 PB Tape
  • 62K Jobs/day, 80K CPU-Hrs/day
  • EUAsia, LHC experiments, Biomed, etc.

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e-Science Infrastructure in Asia

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4

e-Science Networking in Asia Pacific Region

SINET

SG

I2 / GN2 WIDE

JP-Tokyo- LCG2 AU-ATLAS JP-KEK2 JP-KEK1 PK-NCP HK-HKU KR-KNU KR-KISTI- GCRT CN-SDU- LCG2 CN-BEIJING- LCG2

AARNET

PK-PAKGRID MY-MIMOS IN- VECC1 IN-TIFR TW-NIU

TWAREN/ TANET IP Transit

TW- NTCU TW-FTT TW- NCUHEP ASGC IN- VECC2 JP- HIROSHIMA- WLCG2 MY-UPM- BIRUNI-01 TH-HAII TH- NECTEC VN-IOIT- HN VN-IOIT- KEYLAB VN-IFI- PPS MY-UM- CRYSTAL PH-ASTI- LIKNAYAN

KREONET CSTNET

NL

2.5G 2.5G 5G 10G 622M 10G

TW HK US JP

CERNET APAN-JP

iHEP-CAS NTU ATLAS Sites CMS Sites ALICE Sites EUAsiaGrid Sites ITB-ID

! 6+ PB data in/out ASGC in 2010 ! 11 Gbps reached

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5

Resource Status

  • All resources are integrated and managed by Grid system.
  • Operated and managed by ASGC.

Resource Groups CPU Cores Disk (TB) Tape (TB) Inter-Conn User Groups E-Science, HPC, Grid and Cloud Applications 4,504 4,660 4,020

Ethernet

WLCG, TWGrid 5,640 700 0 10G Ethe + IB

(DDR/ QDR)

Earth, Env. Changes, EUAsiaGrid, Astronomy & HPC 4,416 470 Ethernet Cloud, Other e- Science

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Monitoring Tools/Alarm System at ASGC

Weathermap! MRTG! Ganglia!

6

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System Optimization

  • Performance, Cost, Energy Saving, Early Warning and

Automation

  • Storage System and Data Management
  • Deploying higher density disk array with large bandwidth
  • 24x2TB array " 96x2TB array
  • #storage servers reduced, and 10Gb Ethernet and 8Gb fibre

interface equipped

  • Castor and DPM performance tuning: from array controller to

DPM/Castor and intermediary services are explored.

  • Merging ATLAS storage class to DPM
  • Reduce data transmission between ASGC and TW-FTT
  • Castor takes care only Tape-required data services
  • Distributed file system
  • Computing System
  • Networking: from DC to international connection
  • DBMS Architecture and Services

7

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Stress Test and Performance Tuning

8

Details at “Operation & Management” Session, 1600, Mar 23

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Smart Center

  • Power Efficiency
  • Increase power efficiency by eliminating the

use of UPS

  • UPS reduces power efficiency by 30 percent.

Among them, 10 percent is in the form of heat that has to be carried away.

  • Thermal Efficiency
  • Apply space technology to heat conduction of

the data center to increase thermal capacity

  • Intelligent Monitoring & Control
  • Analyzing long term data allows us to build

models that can assist us in operating the center intelligently " early warning and automation

9

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Cloud Technology

  • VM Management Framework
  • Data and Storage Virtualization
  • Application Platform Management
  • Easy software provisioning of identified applications
  • WLCG, targeted e-Science applications, MapReduce +

Hadoop, !

  • Brokering Services
  • resource level and service level
  • Monitoring and Accounting
  • Interoperability (between cloud/grid and among

component/layers)

  • Standardization

10

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11

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Exercises and Use Cases

  • VM deployment
  • Benchmarking on cases from 1s, 10s, 100s, to 1000s VMs at a

time

  • Minimize the VM image size, either for general purpose or

customization

  • VM live migration
  • Through Global File System
  • gLite Work Node on-demand
  • VO-based resource policy implementation
  • Evaluate the impact to resource utilization and best practices
  • Employ P2P solutions for data transmission/location
  • Monitoring & Accounting –
  • leveraging current WWG services and add on those missing

components

  • Nagios-based framework

12

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SLIDE 13

www.egi.eu EGI-InSPIRE RI-261323 ( W

Enabling Grids for E-sciencE

Computational Chemistry Social Science Bioinformatics and Biomedical High Energy Physics Mitigation of natural disasters :;/<==<1+)"(&>(<..) :;/<<2<2) :;?</+,-&1.)@) 7*)(&=<)A,.)B<C)0&()+D<)?(&E</+).'//<..F)

:#7.6,G(62H):G::H):GI)A,.)J,/6=6+,-1>) 8<>6&1,=)!&==,5&(,-&1),12)K(62>61>) 7.6,)A6+D)+D<)L&(=2)

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e-Science Collaborations in Asia

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Discipline Applications Partners Going DG

HEP ATLAS, CMS, ALICE, BELLE, CDF, GEANT4 TH, TW, CESNET, INFN X BioMedical Virtual Screening for Drug Discovery – Avian Flu, Dengue Fever MY, TW, VN, CESNET, INFN X Pandemic disease analysis VN, FR Bioinformatics Grid enabling phylogenetic inference SG, TW, VN, CESNET, INFN SVM Parameter optimization for prediction of Caspases Genome search to identify T3SS effect X Autodock ligand-receptor docking X Complex diseases studies Earth Science Disaster Mitigation on Earthquake ID, MY, PH, TH, VN, TW, CESNET, INFN X Comp Chemistry Chemical compound property analysis TH, TW, CESNET X Climate Change Weather simulation, sea level rising ID, PH, TH, VN, TW Social Sci. Social Simulation TW, UK X

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Application Repository

Application Status: S1 (in consideration), S2 (running but not ported to gLite yet), S3 (ported to gLite, unavailable in EUAsia VO), S4 (available in EUAsia VO), S5 (ready for production)

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  • Convenient access to grid infrastructures for individual users
  • Provides, through the portal interface, support to:
  • Submission of jobs
  • Specific forms for individual applications
  • Helping to prepare the job description and input data
  • Data management
  • Allow sharing with other users
  • Job Monitoring

EUAsiaGrid Portal

  • Life Sciences

– Autodock 4, Beast, Blast, Gromacs, MrBayes, Muscle, Prodist – GVSS*

  • Earth Science: Earthquake*
  • Weather Simulation: WRF*
  • Statistics: R
  • Other User Defined Applications
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Exemplar Applications

17

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Grid Virtual Screening Service by AutoDock

  • View the best conformation of a

simulation!

  • One-click job submission!

Submit the docking job to the Grid with just one click !

  • Generate the histogram with a given energy

threshold!

  • Visualize your job status!

SG + DG

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GVSS

  • 19

"2006! • GAP release! 2007!

  • Avian flu (DC2) / DCR drug screening (2.4M docking,

137+ CPU-years) " CNU/KR for wet lab test!

2008!

  • Dengue fever (NS3) / CDI drug screening (300K

docking, 4167 CPU-days)!

2009! • GVSS release! 2010!

  • Dengue fever / ZINC, ChemBridge drug screening!
  • Antibiotics / GRC drug screening!
  • Compound Profiling!
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Seismic Sensor Networks

Global/Regional Sensor Data

  • Ref. Historical Events

Data

Earthquake Data Center (SeisGrid)

Archive Archive

Risk Analysis & Reduction High Resolution Source & Rupture Process Analysis

Forward Simulation & Event Construction on Grid

Local Sensor & Observation Data

Fast Reporting System

Collaborators: PH, VN, TW, ID, MY, TH

e-Science for Earthquake Disaster Mitigation

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Seismogram Simulation Services

  • 1. Location and Tomography

Model Selction

  • 2. Epicenter Data Preparation
  • 3. Choose Position for Seismogram
  • 4. Seismogram Access & Visualization
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Future Works – Hazard Maps

  • Achieving full process of quantitative seismic

hazard assessment

  • Collecting and analyzing event data
  • Understanding fault characteristics in

details

  • Facilitating accurate simulation on

seismic waves

  • Assessing anticipated earthquake and

potential damages by the correct seismic and engineering models

  • Maps of disaster coverage, risk and also

evacuation are pragmatic to better preparedness

  • 7168 grid points for Taiwan SGT DB takes 45

days on 80x 8-core nodes, and 100TB

  • utput

Near-surface velocity

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Shake Movie

CWB Strong Motion Observation

Click to show movie

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:1M6(&1N<1+,=)!D,1><.)

  • 9644>2<"2/D/+2;X/D">,"6,Y/2D<+,YE,8">Z"<X/";X+,8E,8"

/+2<X"

– C2>0E,8"<X/"U+2[E,8"U>27Y" – K,?/D\8+</"E[4+;<D">Z"/]<2/[/"U/+<X/2"

  • QP.">?/2"8GE</"ED"+?+E7+07/"DE,;/"1+2;X"#!(!"

#%"

  • .>;6D">,"1/</>2>7>8E;+7"

P/D/+2;X/D"E,"F+EU+,"+,Y"9>6<X" J+D<"3DE+"

– N/+?5"2+E,Z+77"D5D</["Y62E,8"1/E-S6" D/+D>," – F54X>>,"2>6</"+,Y"42/;E4E<+\>," – J+D<"3DE+,"H7E[+</" – H7E[+</";X+,8/"E,"1/^>,8"PE?/2"I+DE," – G+,YD7EY/"[>Y/7E,8"

Collaborators: ! HAII, TH! EUAsiaGrid! RCEC, AS, Taiwan!

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25

Highest winds: 140 km/h (10-min sustained) Fatalities : 789 total Rainfall : 2777 mm (total) Damage : $6.2 billion (2009 USD)

Typhoon Morakot (2-11 August, 2009)

Xiaolin village (小林村), Taiwan

96 hrs observation rainfall (mm)!

119E 120E 121E 122E 123E! 25N! 24N! 23N! 22N! WRF (3km) 96hr simulation rainfall (mm)! 25N! 24N! 23N! 22N! 119E 120E 121E 122E 123E!

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Wind Map (Megi, 2010)

26

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27.

Research topics and approach

Regional Climate Changes Urban heat Island effects Ozone, Biomass burning

(local, regional)

Application

1.Health impact (NCKU)

  • 2. Scenario study (NCDR)

Biomass burning Dust +air pollutants dry!warm moist!" cool moist! cool

Inversion

Aerosols

(local, regional)

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Fukushima radioactive plume dispersion!

"#!

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Numerical Simulation for Tsunami Hazards (Liu et al., 2007)

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Social Simulation

  • Project on population migration simulation from 2010
  • TW-UK Collaboration
  • Porting the UK-based Migration Model to gLite/EUAsiaGrid
  • Customization of the model for/of Taiwan
  • Taking into account the birthrate, fertility, and mortality
  • Deploy the local model based on regional researches
  • Feedback cycle for model verification:
  • Based on the real Census data of Taiwan
  • Deployment of agent-based modeling/simulation methods
  • Further extension
  • Financial model
  • Social changes
  • Collaborators: U. Manchester; U. St. Andrews; Survey

Research Center, AS; EUAsiaGrid

Social Resilience in the future!

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e-Science : Vision for new Science

  • Manage and mine large scale data set efficiently
  • Better understanding on natural phenomena
  • Improve our computation/data model based on the

validation of simulation and real data (observation)

  • Sharing of resources and dynamic provisioning, eg,

computing, storage and data, etc.

  • Realize the values of cross disciplinary cooperation
  • Encourage scientists to deal with larger and more

complicated problems collaboratively

  • Enhance capability of hazard mitigation and

support early warning

  • !

31

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32

  • Exploring earth deep interior (sensor networking,

source rupture analysis)

  • Disaster mitigation
  • Seismic wave propagation analysis
  • Early warning
  • Event data preservation

Earthquake

  • Tsunami propagation and flood simulation
  • Breaking-wave simulation
  • Early warning
  • Event data preservation

Tsunami

  • Air pollutant propagation and quality analysis
  • Weather simulation

Air Pollution

  • Agent modeling and risk assessment
  • Adaptation or recovery process modeling

Social Resilience

e-Science for Combined Disasters

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<$*/6<1/<)0&()+D<)O,..<.)

  • Not only porting scientific applications to e-Science collaboration,

but also establishing research oriented production services and long term scientific collaboration among partners

  • Unique scientific values of e-Science Application Data, e.g.

– LHC data, unprecedented energy frontier, new fundamental understanding of the Universe – Earthquake data, first-principle simulation, archival and re-use – Drug Discovery data, neglected diseases information, open access and generating more knowledge – Regional collaborative data often related to Disaster Mitigation

  • Common concerns such as Disaster Mitigation address the challenge of

regional cooperation

  • Take advantage of sharing and collaboration to bridge the gap between

Asia and the world, an opportunity to leapfrog

  • However, one must reduce the entry barriers for e-Science in Asia
  • In Asia, e-Science for the masses is more strategic than the big science!