Presentation Outline Existing Condition Indonesia Grid (InGrid) - - PowerPoint PPT Presentation

Presentation Outline

• Existing Condition

– Indonesia Grid (InGrid) – Cluster Computing in ITB

• ITB Grid Site
• Local Application

– Weather Forecast – Disaster Mitigation

• Grid Training
• Obstacle/Constraints

Indonesia Grid Research

• Research on Grid in Indonesia started around 2006,

together with the development of INHERENT (Indonesia Higher Education Network)

– INHERENT is Indonesian national Research and Education Network which is currenly connecting about 500 universities in Indonesia.

• Objective:

Utilize computational resources available in universities or research institutes in Indonesia to develop grid computing infrastructure.

inGrid

• inGrid or Indonesian Grid infrastructure developed

by University of Indonesia using UCLA Grid Portal consisting Globus Toolkit 4 grid middleware and Gridsphere grid portlet framework.

• In 2008, there are two clusters connected to inGrid:

– One production cluster from Faculty of Computer Science, University of Indonesia – One research cluster

• Applications available in the research cluster:

– Povray (3.1g) – gcc – mpiBLAST – g77 – GNU Octave – GROMACS

http://grid.ui.ac.id/

Source: http://grid.ui.ac.id/

Map of INHERENT

Cluster Computing in ITB

Some departments in ITB has been using cluster computing to support their Research and Education activity, they are:

• Earth Sciences

– Using Cluster Computing for running Weather Prediction Application – http://weather.geoph.itb.ac.id

• Engineering Physics

– Using cluster computing to support data processing, design, and testing. – http://computational.engineering.or.id

• etc

ITB Grid Site

• Developed in collaboration with EUAsiaGrid Project
• Uses gLite middleware
• Consists of

– User Interface combined with MON-Box – DPM/Storage Element – Computing Element – Workload Management System

• Future Development

– Integrating existing Cluster to Grid Infrastructure (current experiment is by Computational Engineering Lab. in Engineering Physics Dept.)

ID-ITB Site

ID-ITB Site Development Plan

Weather Prediction

• This Experimental application is using MODIS data

from satellite image1 to generate weather forecast information and displayed in a web page.

• Parameters used for this application like Infrared and

Water vapor are plotted to TBB (Temperature Black Body) over Maritime Continent.

1downloaded from Kochi University, Japan

Weather Prediction and Grid

• GRID utilization to support Numerical Weather

Prediction (NWP) research activity which is concerned with the development of a common regional platform for NWP application in Southeast Asia.

• NWP experiment will be performed by implementing

WRF4G (WRF for Grid) developed by University of Cantabria under EELA2 to find the most suitable downscaling strategy for NWP in South East Asia.

NWP Model Output

• 1. NCEP AVN/GFS Global Model
• 2. Regional Model
• 3. Sub-regional and Local Models
• 4. Weather Forecast on Google Map

NWP Model Output (1/4)

• 1. NCEP AVN/GFS Global Model

– using original data provided by NOAA – Can only download at 6-hr interval up to 48 hours forecast time – Plotted parameter is OLR (outgoing longwave radiation) and horizontal wind at 10 m height for Asia region (60N - 30S, 70E - 160E) with horizontal resolution of 1 degree

• 2. Regional Model
• 3. Sub-regional and Local Models
• 4. Weather Forecast on Google Map

NCEP AVN/GFS Global Model

NWP Model Output (2/4)

• 1. NCEP AVN/GFS Global Model
• 2. Regional Model

– Downscaling the GFS model output using

Penn ¡State/NCAR ¡MM5 ¡model ¡

– Covers Indonesia and its neighbouring countries with horizontal resolution of 30 km.

• 3. Sub-regional and Local Models
• 4. Weather Forecast on Google Map

Regional Model Output

NWP Model Output (3/4)

• 1. NCEP AVN/GFS Global Model
• 2. Regional Model
• 3. Sub-regional and Local Models

– Covers the islands of Java, Bali, and South of Sumatera with a horizontal resolution of 10 km. – Plotted parameters are 3-hourly convective rainfall, temperature at 2 m height, and surface equivalent potential temperature θe.

• 4. Weather Forecast on Google Map

Sub-regional and Local Models

Convective Rainfall and 10 Meter Wind Analysis 2 Meter Temperature and 10 Meter Wind Analysis

Sub-regional and Local Models

• Equiv. Potensial Temperature

and 10 Meter Wind Analysis Cloud Water

NWP Model Output (4/4)

• 1. NCEP AVN/GFS Global Model
• 2. Regional Model
• 3. Sub-regional and Local Models
• 4. Weather Forecast on Google Map

– Experimental model, covers a few city in Indonesia. – Forecast put in Google Map spatially twice a day – Imsakiah (moslem praying time) and the newest earthquake information from USGS also provided in this map.

NWP Model Output (4/4)

Mitigation of Natural Disaster

• The focus area of the Disaster mitigation are Hazard

map for the mitigation and the vulnerabilities.

– The Hazard map focus on the seismic hazard map, earthquake hazard map, and information hazard map for the mitigation (peoples). – The vulnerabilities focus on the risk impact factors and risk area for infrastructure such as road, electricity, water and other impact to the peoples.

• The development of this domain need for

digitization, modeling and visualization in data processing that demands Grid-enabled high performance computing

Mitigation of Natural Disaster (2)

• Data which is going to be used in Mitigation of

Natural Disaster Application will be taken from USGS, NOAA, BMKG, etc., stored in grid.

• Develop application

– Map showing historical data of natural disaster – Disaster Mitigation Simulation – Firewatch system

• Reference: http://www.pdc.org

Earthquake maps

Eartquake map (II)

Firewatch monitoring

Computational Chemistry

• Department of Chemistry ITB have some

research that might have benefit from the use

• f the grid, they are:

– Molecular Dynamics Study of Thermal Stability of Polymerase I ITB-1 DNA – Computational Study of Spin-Crossover Fe(II) Complexes – Ab initio calculations of hydrogen production mechanisms using graphite as catalysts – Simulation of ZnO with Cd and Cu impurities using LAPW methods – Computational Study of Oxygen Migration in Solid-Oxide Electrolyte for Fuel-Cell

Bioinformatics and Biomedics

• The Bioinformatics in Indonesia are beginning

around three years ago. The activity is still using several computers with the paralel virtual machine (PVM), for the application in genome squence analysis.

• ITB wants to mirror the Genome data bank and made

squence analysis for the new structure especially in

• Indonesia. The squences analysis require the high

performance computing and grid facilities .

• With the TEIN3 Network , ITB has build the bio-

informatics mirror with the collaboration with APAN (Asia Pacific Advanced Network).

Grid Training in Indonesia

• Objectives

– Spread the knowledge about the state-of-art of Grid Technology – Assist e-science communities in Indonesia to be able to use the Grid – Encourage to provide resources to be added to the Grid Infrastructure

Grid Training in Indonesia (2/3)

Training that have been held:

• InGrid Training
• Training for gLite System Administrator, Dec 2009

– Explain EUAsiaGrid and gLite Grid Middleware – Practice installing gLite Middleware and Set-up Grid Site – Participants consists of some Lecturers/Researchers and mostly system administrator in some Departments in ITB. – Outcome expected:

• More gLite System Administrator
• Integrating existing clusters to Grid Infrastructure.

Grid Training in Indonesia (3/3)

• Near Future Training

– Aiming to spread the knowledge about Grid to other universities in Indonesia – Training Material

• Training for system administrator
• Training for grid users (basics)
• Training for application developer / advanced users

– Timing:

• 1st Quarter of 2010

Obstacle/Constraints

• There are various types of applications used by local

science communities, plus each application have specific requirements.

• The license restrictions of some software which is

used by currently running local application also need to be considered when going to run that application on Grid.

• Dissemination of information about grid will be done

in the form of training. For effectiveness, The training will be divided according to material that will be delivered and the expertise level of the participants.

Obstacle/Constraints

• Porting existing application to Grid will be performed

together between the team from Science Communities and the team from grid support.

• Integrating existing cluster to the grid will be

performed by the cluster’s administrator with the assistance from grid administrator.