Grid-enabled Research Activities in CAS Kai Nan Computer Network Information Center (CNIC) Chinese Academy of Sciences (CAS) Shanghai, 21 Feb 2006.

Grid-enabled Research Activities in CAS

Kai NanComputer Network Information Center (CNIC)

Chinese Academy of Sciences (CAS)Shanghai, 21 Feb 2006

Outline

• I. Background– CAS Informatization Program 2001-2005– CAS e-Science Initiative 2006-2010

• II. Grid-enabled Research Activities– Middleware– Applications

• III. Collaborations with EU

Vision of CAS Informatization

• e-Science + ARP →Digital CAS

• e-Science represents Informatization of Research Activities

• ARP (Academia Resource Planning) represents Informatization of Administrative Activities for Research

CAS Informatization Program(2001-2005)

• Major Projects– emphasis on Upgrade of Infrastructure

Progress

Infrastructure Item By 2000 2005

Networking

core 1Gbps 2.5Gbps

backbone 2Mbps N*155M+2.5G

Oversea link 55Mbps 620M+12G

HPC

Peak TFLOPS 0.13 5.5

Linpack TFLOPS 0.05 4.3

Storage 2.1TB 182TB

Scientific Database

Member institutes 21 >45

Databases 180 400+

Data volume 725GB 15TB+

Resources

• Lenovo 6800Superserver

• Storage

• VizWall

• Scientific Data (SDB)

• Science DigitalLib (CSDL)

CAS e-Science Initiative2006-2010

• e-Science would be applications-driven

• focus on implementation of e-Science Virtual Labs, the way for scientists to use

• infrastructure may need refactoring

e-Science Virtual Labs

• “Virtual Labs”• special meanings in

the e-Science context• the key position in our

e-Science framework• the core component

to make e-Science a reality

vLabs Requirements

• Infrastructure may be (almost) ready, but e-Science is not yet.– so many existing resources in place, but just a few could be

brought into full play even now, with an advanced infrastructure ready.

• bottleneck may be the gap between products by computer experts and end users of domain scientists

• much more effort than expected to bridge this gap• Virtual Lab is proposed to be

– a basic unit of research activity in the e-Science environment – the right user interface between scientists and their e-Science

environment

vLabs Goals

• With Virtual Labs, – all kinds of resources could be integrated into

a single access point; – customized and flexible services would be

provided according to the specific requirements of different domains in an easier way than ever before;

– multidisciplinary, multi-site and multi-organization collaboration could be carried out on a routine basis.

Grid Middleware

Scientific Database (SDB)& Scientific Data Grid (SDG)

45 institutes participated503 databases

16.6 TB

236-CPU Superserver (1TF)20TB Disk Array

50TB Tape LibraryVizWall & Access Grid

Requirements and SDG

• How to FIND the data I want from hundreds or thousands of databases

• How to ACCESS large-scale, distributed and heterogeneous scientific data uniformly and conveniently

• How to make sure all this goes always in a SECURE and proper way

SDG Software Architecture

Data Access Service (DAS)

• Uniform Access Interface (read-only)

• Rich metadata

• Easy publish on web

• flexible configuration and extensibility

DAS modules

Data Access InterfaceData Access Interface

Virtual Database

Physical Database

MappingBuilder

DataView

检索词：日食 天象

中国古代天象记录（日食）数据库 DataView 服务

年号年代：康熙

SDG Services

grid-enabled Applications

e-Science applications

• High Energy Physics

• Astronomy

• Biology

• Natural Resources

• Disaster Reduction

• …

YBJ-ARGO/AS• Italy,Japan-China

cosmic ray observatories in Tibet.

• 200TB raw data per year.

• Data transferred to IHEP and processed with 400 CPUs.

• Rec. data accessible by collaborators.

YBJ-ARGO

• Established a 8Mb/s link from Tibet to Beijing, by CNIC of CAS. To be upgraded to 155Mb/s soon. Stopped bringing tapes half year agao.

• Building a computing system based on LCG,collaboration of IHEP of CAS, CNIC of CAS, INFN of Italia , EU-China Grid application under EU FP6 project

LCG Tier-1/2

• to build a LCG Tier-1/2 node in China

• Institute of High Energy Physics of CAS

• CNIC providing support and working together with IHEP

LCG2 production site @CNIC

http://goc.grid.sinica.edu.tw/gstat/BEIJING-CNIC-LCG2-IA64/

Monitoring Info on BEIJING-CNIC-LCG2-IA64

Chandra

Hubble

MMT

Smm array

VLA

Antartica submm Magellan 6.5m

Whipple -ray

SIRTF

Oak Ridge

1.2m CO

VO ＝ World Wide Telescope

Data Services Application Tools Grid Services Catalog

China Virtual Observatory at SDG Portal

Avian Bird Flu Alarming & Predicating System

By: Institute of Microbiology, CAS Institute of Zoology, CAS Institute of Virology, CAS CNIC, CAS

Avian Bird Flu in Gangcha, Qinghai Province, May 2005

上千支鱼鸥、棕鸥、斑头雁死亡

Tasks

• Integrate bird-flu basic databases from multiple institutes

• Field survey on bird-flu• Establish bioinformatics comprehensive analysis

system for bird-flu• Establish bird-flu alarming and predicting system• Establish international cooperative work

environment• Establish information publishing system (web)

Bird-flu basic databases

• Standards– Bird-flu basic database’s model and data standard– Metadata specification and description language of bird-flu

information

• Data resources– Bird-flu virus resource database– Bird-flu virus inherent resource database– Bird-flu history database– Bird-flu dynamic monitoring database– Bird-flu host database– Bird-flu information database– Bird-flu international DNA database– Bird-flu international research progress database

Technical architecture

Distribute Model

Survey on source

SDB

Winter Survey Data

Predicting

Host data

Survey data

Virus data

avian trade routes

Model E

valu

atio

n

Syste

m

Model Database

Model Storage

Model verificati

on

IAPIAP Program “Program “Global NaturalGlobal NaturalHazards Hazards and Disaster and Disaster ReductionReduction””

East Asia Resource Environment Collaborative Research Network• a network connecting

a dozen of institutes and stations from China, Russia and Mongolia

• a series of data products which integrate many relevant databases in this area and support application research

• a platform for int’l collaborative research

Global NaturalHazards and Disaster Reduction• issues in disaster reduction

– Development of mechanism of major natural disaster– Prediction of major natural disaster;– Assessment of major natural disaster;– Pre-warning and emergency response of major natura

l disaster– Regional integrated research on major natural disaste

r

• Database Construction & Application on “Natural Disaster Mitigation”

• Disaster simulation

Collaborations with EU

• Ongoing– EUChinaGrid: Interconnection and Interopera

bility of Grids between Europe & China– Infrastructure is being better

• Look forward to– further more on MIDDLEWARE & APPLICATI

ONS

Thank you!