1. Grid and Cluster Computing
- Bharath Kumar M
bharatkumarm@yahoo.com

2. 10CS845
VTU 10 scheme
 VIII Semester elective subject
 Part-B – Unit 5


3. What is a Grid?

Early defs: Foster and Kesselman, 1998
◦ “A computational grid is a hardware and software infrastructure that
provides dependable, consistent, pervasive, and inexpensive access to
high-end computational facilities”

Kleinrock 1969:
◦ “We will probably see the spread of ‘computer utilities’, which, like
present electric and telephone utilities, will service individual homes and
offices across the country.”

IBM :
◦ “A grid is a collection of distributed computing resources over a local
or wide area network, that appear to an end-user or application as one
large virtual computing system”

4. Vision of Grid:

Create virtual dynamic organizations through secure, coordinated resource sharing
among individuals and institutions.

An approach that spans locations, organizations, machine architectures and software
boundaries to provide unlimited power, collaboration and information access to
everyone connected to the grid

The Internet is about getting computers together (connected), grid computing is
about getting computers work together.

Combine the QoS of enterprise computing with ability to share the heterogeneous
distributed resources – everything from applications to data storage and servers.

5. Grid basics:

Grid computing is a middleware software that manages and executes all
the activities related to:
◦ Identification of resources
◦ Allocation and deallocation of resources
◦ Consolidation of resources

Organizations having under-utilized or over-utilized resources need a
dynamically equitable distribution of resources.

6. Server Hardware

7. The Data Centre

Before the data centre concepts came, organizations maintained own servers and
specialized software.

This approach was expensive and redundant

Data Centres shared resources with organizations.

Organizations connected to a data centre may not be able to use resources from
other data centres

Concept of grid computing enables multiple data centres (same or different
organizations) to be networked and shared.

Grid is a combination of:
◦ Distributed computing
◦ High Performance computing
◦ Disposable computing
Grid provides a metacomputing environment, which can be a megacomputing
facility for the users.
 Grid provides computational utility to its consumers


8. Cluster Computing and Grid computing

Clusters are aggregations of processors in parallel configurations.

Resource allocation is performed by a centralized resource manager and scheduling
system.

All nodes of a cluster work cooperatively together, as a unified resource.

Grid has resource manager for each node.
Grid does not provide a single system view.
 Some grids are collections of clusters. Example: NSF Tera Grid


9. Metacomputing

Metacomputing is all computing and computing-oriented activity which involves
computing knowledge (science and technology) utilized for the research,
development and application of different types of computing. ---- Wikipedia

Use of powerful computing resources, transparently available to the user via a
networked environment is Metacomputing.

Three essential steps to achieve goals of metacomputing are:
◦ To integrate the large number of individual hardware and software resources
into a combined networked resource
◦ To deploy and implement a middleware to provide a transparent view of
resources available
◦ To develop and deploy optimal applications on the distributed metacomputing
environment to take advantage of the resources.

10. 
Challenges in metacomputing –

-Viability of the linking speeds for realistic application execution

-ability and feasibility to execute parallely the components of an application

Resources and originating points of data are geographically distributed – may need
to processed in a distributed manner

Metacomputing is useful when a single point usage is required for large remotely
located resources.

Metacomputing encompasses two broad categories:

- Seamless access to high performance

-Linking of computing resources, instruments and other resources.

11. Metacomputer composition

Metacomputer is a virtual computer – its components are individually not
important

Metacomputer consists of:
◦ -Processors and memory
 Single virtual view of several (large number) of processors and their
associated memory units
◦ -Network and communication software
 Interconnected network of physically distributed processors
 High bandwidth and low latency is required to provide rapid and reliable
communication
◦ -Remote data access and retrieval
 Date sizing upto petabytes.
 Retrieval, replication and mirroring support.
 Ability to manage and manipulate large quantity of remote data
◦ -Virtual environment
 A software like an operating system, that can configure, manage and maintain
metacomputing env.

12. Evolution of Metacomputing projects

FAFNER (1995) - (Factoring via Network-Enabled Recursion)
◦ Finding factors of large numbers parallely, over a large network of
mathematicians.
◦ Started by Bellcore Labs, Syracuse University
◦ To distribute the code for factorizing and related information data

I-WAY (1995) - Information Wide Area Year
◦ Experimental high-performance network, linking many servers and addressed
virtualization environments

13. Scientific, Business and e-Governance Grids

Grid computing approach helped to all computing communities – businesses,
scientific research and government applications.

Scientific grids – users belong to only scientist groups

Business grids – users may belong any citizen groups using business services.

The number of users in Businesses and e-Governance are high – hence setting up
such girds are more complex

The user interfaces, access speeds and data sizes will be large.

14. Web Services and Grid Computing

Users of business and e-Governance grids will need we services over internet

Users of business grids will not be interested in hardware and software locations

They are not interested in resource allocation management as well.

Hence the need for integrating web services with grids.

15. Business computing and the Grid – a
Potential Win-win situation

Grid was initially utilized for applications such as: weather forecasting models,
molecular modelling, bioinformatics, drug design, etc

By harnessing the grid approach businesses can achieve cost reduction and better
QoS.

Grid leverages its extensive information capabilities to support the processing and
storage requirements to complete a task.

Hence grid can provide the maximum resource utilization, providing fastest,
cheapest and maximum satisfaction.

16. 
The grid computing for business is based on three factors:
1.
The ability of grid to ensure more cost-effective use of a given amount of computer
resources
2.
A methodology to solve any difficult or large problem by using grid as a ‘large
computer’
3.
All the computing resources of a grid such as CPUs, disk storage systems and
software packages can be comparatively and synergistically harnessed and managed
in collaboration towards a common business objective.

17. E-Governance and the Grid

Service oriented architecture

OGSA – Open grid services architecture

Globus toolkit

18. References:

Grid and Cluster Computing – C.S.R. Prabhu, PHI , Jan 2012