Clustering

LOW COST SUPERCOMPUTING
USING LINUX CLUSTERS

Topics :

1. Introduction
2. Overview of Parallel Processing
3. Conceptual Overview of Clusters
4. Cluster Design
5. Features & Benefits
6. Application Areas
7. References

Introduction To Clusters

o Parallel processing, the method of having many small tasks solve
one large problem, has emerged as a key enabling technology in
modern computing .
o In past several years Parallel Processing is increasing for :
 High performance scientific computing
 General purpose applications
o It results in :
 High performance
 Low cost
 Sustain productivity

What is Clustering ?

Meaning :
o Clustering is a parallel or distributed system consisting of
independent computers that corporate as a single system.
o Cluster offers a way to use a computer more productively in
comparison to when number of machines working standalone.

2. OVERVIEW OF
PARALLEL PROCESSING

Introduction to Parallelism

o Parallel Processing refers to the concept of speeding-up the
execution of the program by dividing the program into multiple
fragments.
o Parallel Processing operates on two levels :
a. Hardware Parallelism
b. Software Parallelism

Parallel Processing Schemes

o There are different approaches to creating effective parallel
computers , and all of them have different levels of effectiveness
for different kind of problems.
o Some of the methods are :
 Symmetric Multiprocessing (SMP)
 Non-Uniform Memory Access (NUMA)
 Uniform Memory Access (UMA)
 Single Instruction Multiple Data (SIMD)
 Multiple Instruction Multiple Data (MIMD)

3. CONCEPTUAL
OVERVIEW OF CLUSTERS

Brief History Of Clusters

o In the summer of 1994 Thomas Sterling and Don Becker working
at CESDIS under sponsorship of the EES project, built a cluster of
16 DX4 processors connected by channel bonded Ethernet .
o They called their machines Beowulf .

Cluster Design

o Cluster design includes :
 Design Considerations
 Topology
 Cluster Style
 Hardware Specification
 Software Requirements
 Cluster Architecture

Design Issues

o Design Issues considers :
1. Size Scalability (physical & application)
2. Enhanced Availability (failure management)
3. Single System Image (SSI look-and-feel of same system)
4. Fast Communication (network & protocols)
5. Programmability (simple API if required)

Cluster Style

Cluster
Styles

Homogeneous Heterogeneous

Topology
o Currently used topologies in networking are :
 Ring
 Bus
 Star
 Line
 Mesh
 Tree etc.
o We are using star topology due to following reason :
 Failure of one node does not effect entire network
 Range provided by star topology is greater than that of bus topology
 Range can be extended by using routers

Hardware Specification

o Hardware configuration of cluster mainly consists of two
components.
 Nodes or Workstations

Hardware Requirements

Hardware Requirement for MASTER NODE :
o Master mode is where the users of the system will log in.

o They submit their job processed by system and look at the result
of their work.
o It requires :
 CPU capable system as master node with fast CPU
 Greater than 128 MB RAM
 8 GB HDD or more
 10 Mbps/ 100 Mbps Ethernet adapter.

Hardware Requirement for SLAVE NODE:
o Slave nodes are useful for computation only.
o For Slave node hard disk capacity need to be very large for
better storage capacity.
o It requires,
CPU based system with fast CPU
 32 MB or more memory modules
 4 GB HDD or more
 10 Mbps/ 100 Mbps Ethernet adapter.

Software Requirement

o The platform (O.S.) for developing cluster is very important
because the throughput and performance of machine is totally
depends upon how the platform manages the whole cluster.
o Some of the O.S that supports Clustering are,
 Linux
 Unix
 Windows 2000
 Windows NT

Why Linux ?

o Linux is generally cheaper than other O.S and is frequently less
problematic than many commercial systems.
o Linux is chosen because :
1. It is a 32-bit multitasking Operating System.
2. It runs on hardware ranging from low-end 386 boxes to massive ultra-
parallel machines.
3. Linux has a very strong networking support & also its efficient processing
support.
4. The programming environments & development tools for parallel
programming are more mature in Linux.

Cluster Architecture

o It covers :
 Network Interface Hardware
 Communication Software
 Cluster Middleware

Features & Benefits

o Data sharing across the interface
o Parallel processing of small tasks
o Easy server maintenance

Applications

o General high performance computing
o Bulk disk servers
o High performance web servers
o Flight simulators
o Alife

Clustering Examples

o It is used in :
 NASA uses Beowulf which was started in a project headed up by CESDIS
 NOAA uses several Clustering technologies in their project
 Google.com introduced largest ever LINUX cluster which powers their popular
web search engine

Book References :

o Red Hat Linux System & Network Administration
o Building Linux Clusters -David HM Spector (Oreilley Publications)
o Beginning Linux Programming - Wrox Publications

Web Reference :

 www.beowlf.org
 www.redhat.com/mirrors/LDP
 www.jics.utk.edu Parallel Computing Resources
 www.linux-mag.com/gallery.html Linux Magazine Open Source

Clustering

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Clustering