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SEE-GRID-SCI

The SEE-GRID-SCI initiative is co-funded by the European Commission under the FP7 Research Infrastructures contract no. 211338

Introduction of Grid Computing

ASNET-AM Annual Report,Yerevan, Armenia, 17 December 2008

Hrachya AstsatryanInstitute for Informatics and Automation Problems

National Academy of Sciences of the Republic of Armeniahrach@sci.am

Outline

Definition of Grid computing

Grid Computing Components

E-Infrastructures

Grid Monitoring & Information Services

Grid Definition: Word Meaning

The term Grid computing or Grid suggest a computing paradigm similar to an electric power grid - a variety of resources contribute power into a shared "pool" for many consumers to access on an as-needed basis.

Grid Definition (2)

In 1998 Ian Foster and Carl Kesselman (The Grid: Blueprint for a New Computing Infrastructure)“A computational grid is a hardware and software infrastructure that provides dependable, consistent, pervasive, and inexpensive access to high-end computational capabilities.”

In 2002 Ian Foster (What is the Grid? A Three-Point Checklist) A Grid is a system thatcoordinates resources that are not subject to centralized controlusing standard, open, general-purpose protocols and interfacesto deliver nontrivial qualities of service.”

Grid Definition (3): A Working Definition

A distributed computing environment that coordinates Computational jobs Data placement Information management

Scales from one computer to thousands

Capable of working across many administrative domains

Outline

Definition of Grid computing

Grid Computing Components

E-Infrastructures

Grid Monitoring & Information Services

Distributed People Research communities who need to share data, or

codes, or computers, or equipment to work on and understand common problems

Example: Astrophysics Network: relativists, astrophysicists, computer scientists, mathematicians, experimentalists, data analysts.

Distributed Resources Computers: supercomputers, clusters, workstations Storage devices, databases, networks Experimental equipment: telescopes/interferometers

Grid Computing Components

Software infrastructure Links all these together Low level: security, information, communication, … Middleware: data management, resource brokers, web portals,

monitoring, workflow, …

Examples Globus Condor Glite

Grid Computing Components (2)

Groups of organizations that use the Grid to share resources for specific purposes

Support a single community

Deploy compatible technology and agree on working policies Security policies – difficult

Deploy different network accessible services: Grid Information Grid Resource Brokering Grid Monitoring Grid Accounting

Grid Computing Components (3)Virtual Organizations

MIDDLEWARE

Visualization

User

Access

Suprecomputers, clusters

Internet, networks

Experiments, sensors, etc..

Grid Computing Components (10)

Hardware Components: Brief History of Computing

1980: "DOS addresses only 1 Megabyte of RAM because we cannot imagine any applications needing more." -Microsoft on the development of DOS.

1981: "640k ought to be enough for anybody." -Bill Gates

0

2000

4000

6000

8000

10000

12000

14000

1960 1970 1980 1990 2000 2010

MIPS

Series2

Distributed systems built from Computing elements (processors) Communication elements (networks) Storage elements (disk, attached or networked)

New elements Visualization/interactive devices Experimental and operational devices

Hardware Components (2):Basic Elements

Definition of supercomputer Machine on Top500.org? Machine costing over $1M? Most powerful machines One-of-a-kind

Top 1 (Latest 2008) Roadrunner - BladeCenter QS22 (US) 1026TFTop 1 (November 2006)

IBM Blue Gene/L (US) 131k procs, 280 TFTop 1 (2003)

Earth Simulator (JAPAN) 5K procs/36 TF (6)

Hardware Components (4):Basic Elements

Supercomputers

Outline

Definition of Grid computing

Grid Computing Components

E-Infrastructures

Grid Monitoring & Information Services

E-Infrastructures: network layer

E-Infrastructures (2): Grid layer

Standards

OGF

E-Infrastructures (3): Data layer

E-Infrastructures (4): Global perspective

Potential for linking ~80 countries by 2008

E-Infrastructures (5): Grid Examples

Applicationsimproved services for academia,

industry and the public

Support Actionskey complementary functions

Infrastructuresgeographical or thematic coverage

E-Infrastructures (6): Collaborating Projects

SEE GRID SCI Project

ContractorsGRNET GreeceCERN SwitzerlandSZTAKI Hungary IPP-BAS BulgariaICI RomaniaTUBITAK TurkeyASA/INIMA AlbaniaUoBL Bosnia-HerzegovinaUKIM FYR of MacedoniaUOB SerbiaUoM MontenegroRENAM MoldovaRBI CroatiaIIAP-NAS-RA ArmeniaGRENA Georgia

Third Party ssociate universities / research centres

GRNET.gr

SEE-GRID-SCI partnership

MTA SZTAKI .hu

IPP .bg

ICI .ro

TUBITAK.tr

UPT.al

UKIM.mk

UoBL.ba

RBI.hr

UOB.rs

RENAM.md

UOM.me

GRENA.ge

IIAP-NAS-RA.am

The SEE-GRID-SCI initiative is co-funded by the European Commission under the FP7 Research Infrastructures contract no. 211338

SEE GRID SCI: converged communication and service infrastructure for SEE

GRNET.gr

MTA SZTAKI .hu

IPP .bg

ICI .ro

TUBITAK.tr

UPT.al

UKIM.mk

UoBL.ba

RBI.hr

UOB.rs

RENAM.md

UOM.me

GRENA.ge

IIAP-NAS-RA.am

SEEFIRE + Geant Support

SEE-GRID

SeismologyVO

MeteorologyVO

EnvironmentalVO

SeismologyVO

MeteorologyVO

EnvironmentalVO

SEE-SCI

e-Infrastru

cture

The SEE-GRID-SCI initiative is co-funded by the European Commission under the FP7 Research Infrastructures contract no. 211338

SEE GRID SCI Open Applications: Earthquake

SEE GRID SCI Open Applications: Meteorology

Advances in numerical weather prediction (NWP) has been always very closely related with advances in computing sciences as NWP requires numerical calculations that are also parallelizable.

The computer resources needed for NWP applications are important both in terms of CPU usage and disk storage. Although many institutions are working/ have experience on NWP, they may not have access to the necessary computer resources for operational implementation of such applications or for large experiments.

So the porting of any NWP application to the grid is a natural choice.

SEE GRID SCI Open Applications: Meteorology

•The REFS application will allow the meteorological entities participating in the project to assess the probability of a particular weather event to occur and to provide this information to the authorities, the general public, etc, in order to help them make the necessary decisions based on this probabilistic information.

•The WRF-ARW application will permit the entities participating in the project to improve the quality of the forecasts of the airflow over regions characterised by complex terrain with a positive impact to related applications such as air-pollution dispersion modelling.

SEE GRID SCI Open Applications: Environment

•The aim of the Monte Carlo Sensitivity Analysis for Environmental Systems application is to develop an efficient Grid implementation of a Monte Carlo technique for sensitivity studies in the domains of Environmental modeling and Environmental security. The developed application will be applied for studying the damaging effects that can be caused by high pollution levels (especially effects on human health), when the main tool will be the Danish Eulerian Model (DEM).

Multi-Scale Atmospheric Composition Modelling. Atmospheric composition directly affect many aspects of life. AQ studies are fundamental for the future orientation of national, regional and Europe’s Sustainable Development strategy. Expected results and their consequences

•high quality scientifically robust assessments of the air pollution and its origin from urban to local to regional (Balkan) scales•Determination of the main pathways and processes that lead to atmospheric composition formation in different scales

Armenian National Grid Initiative

The Armenian National Grid Initiative (ArmNGI) represents an effort to establish a sustainable grid infrastructure in Armenia. The establishment of ArmNGI foundation is in process. Main aims of the initiative are;

•create a national GRID development policy •to build up the national grid infrastructure •to expand the high performance computing resources with collaboration of academic and commercial participants •to give the information to the national user community about high performance computing, grid infrastructure and international grid projects •to improve national applications •to take place the international grid projects actively

Armenian National Grid Initiative

•State Scientific Committee of the Ministry of Education and Science of the Republic of Armenia

•National Academy of Sciences of the Republic of Armenia

•State Engineering University of Armenia

•Yerevan State University

•Yerevan Physics Institute after A. Alikhanian

•Institute for Informatics and Automation Problems of the National Academy of Sciences of the Republic of Armenia

•Armenian e-Science Foundation

European Commission

“…for Grids we would like to see the move towards

long-term sustainable initiatives less dependent upon

EU-funded project cycles”

Viviane Reding, Commissioner, European Commission, at the EGEE’06 Conference,

September 25, 2006

European Grid Initiative

Goal: Creating a long-term sustainability of grid

infrastructures in Europe

Approach: Establishment of a new federated model bringing

together National Grid Initiatives (NGIs) to build the EGI Organisation

Characteristics of NGIs

Each NGI … should be a recognized national body

with a single point-of-contact … should mobilise national funding and resources … should operate the national e-Infrastructure … should support user communities (application

independent, and open to new user communities and resource providers)

… should contribute and adhere to international standards and policies

Responsibilities between NGIs and EGI are split to be federated and complementary

www.eu-egi.org

38 National Grid Initiatives

European Grid Initiative

EGI Organisation:Coordination and operation of a common multi-national, multi-disciplinary Grid infrastructure To enable and support international Grid-based collaboration To provide support and added value to NGIs To liaise with corresponding infrastructures outside Europe

Outline

Definition of Grid computing

Grid Computing Components

E-Infrastructures

Grid Monitoring & Information Services

Monitoring provides information for several purposes

Operation of Grid Monitoring and testing Grid

Deployment of applications What resources are available to me? (Resource discovery) What is the state of the grid? (Resource selection) How to optimize resource use? (Application configuration and

adaptation)

Information for other Grid Services to use

Grid Monitoring

Monitoring information is either static or dynamic, broadly.

Static information about a site: Number of worker nodes, processors Storage capacities Architecture and Operating systems

Dynamic information about a site Number of jobs running on each site CPU utilization of different worker nodes Overall site “availability”

Time-varying information is critical for scheduling of grid jobs

More accurate info costs more: it’s a tradeoff.

Grid Monitoring (2)

http://monalisa.caltech.edu/

Grid Monitoring (3) MonALISA

http://monalisa.caltech.edu/

Grid Monitoring (4): GSTAT

Status of resource on gridUp/down?How much load?

DiscoveryStart with a task to perform on the gridFor example, want to perform run a simulationHow do we find resources to use?How do we choose which resource to use?

Grid Monitoring (7): Monitoring Grid Resources