29-06-2012, 03:06 PM
AN INTRODUCTION OF GRID COMPUTING
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INTRODUCTION
Grid computing is a form of distributed computing whereby a "super and virtual computer" is composed of a cluster of networked, loosely coupled computers, acting in concert to perform very large tasks.
Grid computing (Foster and Kesselman, 1999) is a growing technology that facilitates the executions of large-scale resource intensive applications on geographically distributed computing resources.
Facilitates flexible, secure, coordinated large scale resource sharing among dynamic collections of individuals, institutions, and resource
Enable communities (“virtual organizations”) to share geographically distributed resources as they pursue common goals
Grid Applications
Data and computationally intensive applications:
This technology has been applied to computationally-intensive scientific, mathematical, and academic problems like drug discovery, economic forecasting, seismic analysis back office data processing in support of e-commerce
A chemist may utilize hundreds of processors to screen thousands of compounds per hour.
Teams of engineers worldwide pool resources to analyze terabytes of structural data.
Meteorologists seek to visualize and analyze petabytes of climate data with enormous computational demands.
Resource sharing
Computers, storage, sensors, networks, …
Sharing always conditional: issues of trust, policy, negotiation, payment, …
Coordinated problem solving
distributed data analysis, computation, collaboration, …
Grid Topologies
• Intragrid
– Local grid within an organisation
– Trust based on personal contracts
• Extragrid
– Resources of a consortium of organisations
connected through a (Virtual) Private Network
– Trust based on Business to Business contracts
• Intergrid
– Global sharing of resources through the internet
– Trust based on certification
Data Grid
A data grid is a grid computing system that deals with data — the controlled sharing and management of large amounts of distributed data.
Data Grid is the storage component of a grid environment. Scientific and engineering applications require access to large amounts of data, and often this data is widely distributed. A data grid provides seamless access to the local or remote data required to complete compute intensive calculations.
Example :
Biomedical informatics Research Network (BIRN),
the Southern California earthquake Center (SCEC).
Methods of Grid Computing
Distributed Supercomputing
High-Throughput Computing
On-Demand Computing
Data-Intensive Computing
Collaborative Computing
Logistical Networking