Grid computing: The Grid(Mar 05, 2013)

ByJivan Nepali, 066 BCT 517Laxmi Kadariya, 066 BCT 518Narayan Pd. Kandel, 066 BCT 520

Case Study Report Presentation

IS There Any Computer System that isn’t a Grid?

Data Grids

Knowledge Grids

Bio Grids

Compute

GridsCommodity

GridsScience

Grids

Tera Grids

Sensor Grids

Cluster Grids

Definitions

“A computational grid is a hardware and software infrastructure that provides dependable, consistent, pervasive, and inexpensive access to high-end computational capabilities.”

– Foster & Kesselman, 1998 “Grid computing is concerned with coordinated

resource sharing and problem solving in dynamic, multi-institutional virtual organizations (VOs).”

- Foster & Tuecke, 2000It is NOT a cluster Architecture!

Grid: Building Blocks Networks Link together geographically distributed resources and

allow them to be used collectively Computational ‘Nodes’ on the Grid Networks connect resources on the Grid – computational

resources with data storage Pulling it together It involves the coordination and partnerships among the

remaining blocks for the complete model of a Grid Common Infrastructure: Standards Grid Standards to developers & users Standards on which the Grid is being built

Connectivity Layer

Grid Computing: Architectural Model

Hourglass Model Thin center: few standards Wide top: many high-level behaviors can be mapped Wide bottom: many underlying technologies and systems

 Collective Layer

Application Layer

Fabric Layer

Resource Layer

Grid Models Distributed Super-Computing

Aggregate computational resources to tackle problems that cannot be solved by a single system

High-throughput Computing Schedule large numbers of independent tasks to exploit unused

CPU cycles

On-demand Computing Use Grid capabilities to meet short-term requirements for

resources that cannot conveniently be located locally

Data-Intensive Computing Synthesize data in geographically distributed repositories

Collaborative Computing Enable shared use of data archives and simulations

Grid Computing: Challenges No clear Standard Debate on Concept Difficult to Develop Limited area & Applications Lack of Grid-enabled Software Centralized Management Security Management and Administration

Grid Computing: Applications Life Science Application

Computational biology, bioinformatics, genomics, computational neuroscience

e.g. the Protein Data Bank, the myGrid Project, the Biomedical Information Research Network (BIRN), MCell].

Engineering-oriented Application NASA operation its research through grid

Data-oriented Application Data is emerging as the ‘killer application’ of the Grid. e.g. Distributed Aircraft Maintenance Environment

(DAME).

Grid Computing: Applications Cont...

Physical Science Application The National Virtual Observatory Project in the United States

is using the Grid to federate sky surveys from several different telescopes

Commercial Application Virtual server hosting, Disaster recovery, Heterogeneous workload management, End-to-end systems management, End-to-end automation Reducing up-front investment Accessing new capability more quickly, Better performance

References[1] Foster, I. & Kesselman C. (2005). “The Grid in a Nutshell”. Mathematics and Computer Science Division, Argonne National Laboratory, Information Sciences Institute, University of Southern California, USA.[2] Engelen van R. (2008). “Concepts & Architecture of Grid Computing”. Leiden University, Netherlands.[3] Berman F., Hey A.J.G. & Fox G.C. (2003). “Grid Computing – Making the Global Infrastructure a Reality”. John Wiley & Sons Ltd, Chichester, England.[4] Abbas A. (2004). “Grid Computing: A Practical Guide to Technology & Applications”. Firewall Media, An Imprint of Laxmi Publications Pvt. Ltd., Golden House, Daryaganj, New Delhi, India.

Thank You!