The document provides an overview of grid computing, defining it as a collection of computer resources integrated to achieve common goals without centralized control. It discusses the architecture and middleware necessary for grid functionality, as well as its advantages, disadvantages, evolution, and various applications. Grid computing enables resource sharing across diverse systems and promotes efficiency in computing, particularly for large-scale problems.

1. Prepared By: Dikshita Viradia

2.  Introduction to Grid Computing
 Definition in brief
 History and Evaluation
 Classification and Architecture
 Real-time application
 Advantage
 Disadvantage
 Conclusion
 References

3. Grid Definition
 a Grid is "a set of information resources
(computers, databases, networks, instruments,
etc.) that are integrated to provide users with
tools and applications that treat those resources
as components within a 'virtual' system".
 Grid software solutions provide the underlying
mechanisms necessary to create such systems,
including authentication and authorization,
resource discovery, resource management,
communications, and information services, etc.

4. What is Grid Computing?
 Grid computing is the collection of computer
resources from multiple locations to reach a
common goal.
 Characteristics of a Grid:
 No centralized control center
 Heterogeneity (of resources)
 Scalability
 Dynamic and Adaptable

5. How do grid works?
o Grids use networks to link the computing resources
of many different computers.
o The cyber-glue that binds all of these resources
together is called “middleware.” There are many
different types of middleware, developed for many
different types of grid.
o Middleware does all the work to connect users’ jobs
to computing resources, thereby hiding the grid’s
complexity from the user.

6. 6
Why do we need Grids?
 Grids allow you to combine the resources of
hundreds of computers to create a massively
powerful, fully comprehensive computing resource, all
accessible from the comfort of your own personal
computer.
 This means grids can react quickly to changing
needs: a tremendous resource for crisis situations
like natural disasters or epidemics.

7. o The idea is that in the future, plugging into a
computing grid will be as simple as plugging into an
electrical grid. And, like an electrical grid, users will
simply plug in and use as much computing power as
they need, without knowing where it comes from or
how it was produced; you will simply plug in and use
as much as you need.

8. Grid application
User Resource Broker
Details of Grid resources
Grid Resources
Grid Information Service
A User sends computation
or data intensive application
to Global Grids in order to
speed up the execution of the
application.
1
A Resource Broker distribute the
jobs in an application to the Grid
resources based on user’s QoS
requirements and details of available
Grid resources for further executions.
Grid Resources (Cluster, PC,
Supercomputer, database,
instruments, etc.) in the Global
Grid execute the user jobs.
Grid Information Service
system collects the details of
the available Grid resources
and passes the information
to the resource broker.
Computation result
Computational jobs
Processed jobs
2
3
4

9. Introduction to Grid Architecture
 Grid’s protocols allow VO users and resources to
negotiate, establish, manage and exploit sharing
relationships.
 Interoperability a fundamental concern
 The protocols are critical to interoperability
 Services are important
We need to consider APIs and SDKs
VO: Virtual Organization

10. Introduction to Grid Architecture
 The components are
 numerous
 owned and managed by different, potentially
mutually distrustful organisations and individuals
 may be potentially faulty
 have different security requirements and policies
 heterogeneous
 connected by heterogeneous, multilevel
networks
 have different resource management policies
 are likely to be geographically separated

11. 11
Grid Architecture
Autonomous, globally distributed computers/clusters

12. Application
Collective
“Coordinating multiple resources”:
ubiquitous infrastructure services,
app-specific distributed services
“Sharing single resources”: Resource
negotiating access, controlling use
“Talking to things”: communication Connectivity
(Internet protocols) & security
“Controlling things locally”: Access Fabric
to, & control of, resources
Application
Transport
Internet
Link
Internet Protocol Architecture

13. History and Evolution of Grid

14. History and Evolution of Grid
 Early to mid 90s: numerous research projects on
distributed computing
 The term grid computing originated in the early
1990s as a metaphor for making computer
power as easy to access as an electric power
grid. The power grid metaphor for accessible
computing quickly became canonical when Ian
Foster and Carl Kesselman published their
seminal work, "The Grid: Blueprint for a new
computing infrastructure

15. History and Evolution of Grid
 1995, I-Way
 IEEE/ACM 1995 Super Computing (San Diego), 11 high
speed networks used to connect 17 sites to create one
super meta-computer
 Foster, Nature, 12/2002
 1996, Globus project started (ANL & USC)
 Followed I-Way
 1997, Unicore (Germany)

16.  Distributed Supercomputing
 High-Throughput Computing
 On-Demand Computing
 Data-Intensive Computing
 Collaborative Computing
 Logistical Networking

17. Criteria for a Grid:
Coordinates resources that are not subject to
centralized control.
Uses standard, open, general-purpose protocols
and interfaces.
Delivers nontrivial qualities of service.
Benefits:
 Exploit Underutilized resources
 Resource load Balancing
 Virtualize resources across an enterprise
 Data Grids, Compute Grids
 Enable collaboration for virtual organizations

18. Applications
 Computational Service
• Inherent part of ALL applications
 Data Service
• Scalable storage and access to distributed datasets
 Application Service
• Example: like web services
 Information Service
• Example: WWW portal
 Knowledge Service
• Example: data mining

19. Networking
ARPANET
Information Sharing:
WWW, HTTP, HTML
Communications
and Data Sharing:
Email, ftp, telnet, TCP/IP
Resource Sharing:
P2P, Web Services, Grids

20.  It extends the notions of computational and data grids.
 A Grid should provide the interfaces, libraries, utilities, and
programming APIs to support the development effort
required.
 Common tools and libraries for building Grid applications
includes
 High Performance C++ (HPC++)
 the Message Passing Interface (MPI).
 Access to any resources, for anyone, anywhere, anytime,
from any platform – portal (super) computing.

21.  Can solve larger, more complex
problems in a shorter time
 Easier to collaborate with other
organizations
 Make better use of existing hardware

22.  Grid software and standards are still evolving
 Learning curve to get started
 Non-interactive job submission

23. Conclusions
 Characteristics of a grid relevant to middleware
 Common design methodologies in grid middleware
 Grid Services and open standardization
 New and existing middleware systems are beginning
to adopt core grid middleware to become easily ‘grid-enhanced’

24. www.gridcomputing.com
www.dartmouth.edu
www.eecg.toronto.edu
www.sastra.edu
www.usermonas.edu
www.gridbus.org