1. CLUSTER COMPUTING

2. INTRODUCTION
Cluster is a widely used term meaning independent computers combined into a unified system through software and networking
Clusters are typically used for High Availability (HA) for greater reliability or High Performance Computing (HPC) to provide greater computational power than a single computer can provide.
Clusters are composed of many commodity computers, linked together by a high-speed dedicated network

3. Cluster categorization
High-availability (HA) clusters
Load balancing clusters
High-performance (HPC) clusters
Grid Cluster

4. Cluster Architecture
A cluster is a type of parallel or distributed processing system that consists of a collection of interconnected stand-alone computers working together as a single, integrated computing resource

5. Cluster Computing Features
Network technologies
Network Types
Communication Protocols
Operating system
Single System Image (SSI)
Quorum

6. Production of High Throughput Cluster Computing Applications
Divide and Conquer
Data Management
Shared Storage Architectures

7. HOMER CLUSTER Used for e-mail and information resources Architecture
A cluster is made up of six components
Compute servers
File servers
Password servers
Application servers
Mail servers
Reference systems

8. Hardware Topology :

9. Dell high performance computing
combines multiple Symmetric Multi-Processor (SMP) computer systems together with high-speed interconnects to achieve the raw-computing power of supercomputers
HPCC Architecture

10. HPCC Building Block

11. BENEFITS LIMITATIONS APPLICATIONS
scale to very large systems
replacing a "bad machine" within a cluster is trivial yields much higher Availability
LIMITATIONS
Typically latency is very high and bandwidth relatively low.
Currently there is very little software support for treating a cluster as a single system.
Problems exist in the interactions between mixed application workloads on a single time-shared computer
APPLICATIONS
execution platform for a range of application classes
to execute many Internet applications
execution environments for applications such as weather modeling, automobile crash simulations, life sciences, computational fluid dynamics etc.

12. Comparing with other distributed computing
Characteristic
Cluster
Grid
P2P
Resource Management (i.e. memory, objects, storage, network access, etc)
Centralized
Distributed
Resource Ownership
Singular
(Often locked to a single node to prevent data corruption)
Singular or multiple, varies from platform to platform
Singular, multiple, or distributed, depending on circumstance and architecture
Method of Resource Allocation / Scheduling
Centralized, allocated according configuration
Decentralized
N/A, there is no single permanent host for centralized data or resource management. Everything is transient.
External Representation
Single Image
Single or multiple image(s)
Unknown, it is circumstantial
Inter-Operability
Guaranteed within a cluster
Enforced within a framework
Multiple competing standards
Suggested Equipments
Mostly high-end, high capability systems
High-end or commodity systems
Any type, including wireless device and embedded systems.
Scaling
2- 16 way (Although, theoretically 128+ is possible)
Two to thousands units connection
Theoretically, infinite (In actuality, it depends on network backbone transmission speed, number of clients, and type of transmission protocol…..)
Discovery Mechanism
Defined membership (Static or Dynamic)
Centralized index, as well as, multiple decentralized mechanisms.
Always decentralized discovery mechanism.

13. CONCLUSION
Cluster computing has become a major part of many research programs because the price to performance ratio of commodity clusters is very good. Also, because the nodes in a cluster are clones, there is no single point of failure, which enhances the reliability to the cluster.

14. THANK Q