1. Case Study Report Presentation
Grid computing: The Grid
(Mar 05, 2013)
By
Jivan Nepali, 066 BCT 517
Laxmi Kadariya, 066 BCT 518
Narayan Pd. Kandel, 066 BCT 520
2. IS There Any Computer System
that isn’t a Grid?
Bio Data Knowledge
Grids Grids Grids
Commodity Compute Science
Grids Grids Grids
Cluster Tera Sensor
Grids Grids Grids
3. 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, 2000
It is NOT a cluster Architecture!
4. 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
5. Grid Computing: Architectural
Model
Hourglass Model
Thin center: few standards Application Layer
Wide top: many high-level
Collective Layer
behaviors can be mapped
Wide bottom: many underlying
Connectivity Layer Resource Layer
technologies and systems
Fabric Layer
6. 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
7. 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
8. 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).
9. 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
10. 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.