CLUSTER COMPUTING Presented By, Navaneeth.C.Mouly 1AY05IS037

Slides:



Advertisements
Similar presentations
Tableau Software Australia
Advertisements

Full-System Timing-First Simulation Carl J. Mauer Mark D. Hill and David A. Wood Computer Sciences Department University of Wisconsin—Madison.
Clusters Part 1 - Definition of and motivation for clusters Lars Lundberg The slides in this presentation cover Part 1 (Chapters 1-4) in Pfister’s book.
2. Computer Clusters for Scalable Parallel Computing
1 Presented By Avinash Gutte Under The Guidance of Mrs. Hemangi Kulkarni Department of Computer Engineering Pimpri-Chinchwad College of Engineering, Pune.
Information Technology Center Introduction to High Performance Computing at KFUPM.
Introduction What is Parallel Algorithms? Why Parallel Algorithms? Evolution and Convergence of Parallel Algorithms Fundamental Design Issues.
Copyright © 2006 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill Technology Education Copyright © 2006 by The McGraw-Hill Companies,
DISTRIBUTED COMPUTING
SEARCH ENGINES By, CH.KRISHNA MANOJ(Y5CS021), 3/4 B.TECH, VRSEC. 8/7/20151.
Data Warehousing: Defined and Its Applications Pete Johnson April 2002.
CLUSTER COMPUTING Prepared by: Kalpesh Sindha (ITSNS)
Shilpa Seth.  Centralized System Centralized System  Client Server System Client Server System  Parallel System Parallel System.
PMIT-6102 Advanced Database Systems
Gilbert Thomas Grid Computing & Sun Grid Engine “Basic Concepts”
A Survey of Mobile Cloud Computing Application Models
CLUSTER COMPUTING STIMI K.O. ROLL NO:53 MCA B-5. INTRODUCTION  A computer cluster is a group of tightly coupled computers that work together closely.
Cluster Workstations. Recently the distinction between parallel and distributed computers has become blurred with the advent of the network of workstations.
High Performance Computing Processors Felix Noble Mirayma V. Rodriguez Agnes Velez Electric and Computer Engineer Department August 25, 2004.
1 CMPE 511 HIGH PERFORMANCE COMPUTING CLUSTERS Dilek Demirel İşçi.
CLUSTER COMPUTING TECHNOLOGY BY-1.SACHIN YADAV 2.MADHAV SHINDE SECTION-3.
Data Management for Decision Support Session-4 Prof. Bharat Bhasker.
Scalable Keyword Search on Large RDF Data. Abstract Keyword search is a useful tool for exploring large RDF datasets. Existing techniques either rely.
COMP381 by M. Hamdi 1 Clusters: Networks of WS/PC.
Enterprise Solutions Chapter 11 – In-memory Technology.
Tackling I/O Issues 1 David Race 16 March 2010.
Cluster computing. 1.What is cluster computing? 2.Need of cluster computing. 3.Architecture 4.Applications of cluster computing 5.Advantages of cluster.
The Anatomy of a Large-Scale Hypertextual Web Search Engine S. Brin and L. Page, Computer Networks and ISDN Systems, Vol. 30, No. 1-7, pages , April.
Configuring SQL Server for a successful SharePoint Server Deployment Haaron Gonzalez Solution Architect & Consultant Microsoft MVP SharePoint Server
 What is Cluster Computing  Benefits of Cluster Computing  Types of Cluster’s  Cluster Components  Cluster Applications  Performance Impacts and.
Chapter 16 Client/Server Computing Dave Bremer Otago Polytechnic, N.Z. ©2008, Prentice Hall Operating Systems: Internals and Design Principles, 6/E William.
Cloud Computing Ed Lazowska Bill & Melinda Gates Chair in Computer Science & Engineering University of Washington August 2012.
SEMINAR ON INTERNET SEARCHING PRESENTED BY:- AVIPSA PUROHIT REGD NO GUIDED BY:- Lect. ANANYA MISHRA.
High Performance Computing (HPC)
DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING CLOUD COMPUTING
Introduction to Parallel Computing: MPI, OpenMP and Hybrid Programming
Introduction Super-computing Tuesday
Advanced Topics in Concurrency and Reactive Programming: Case Study – Google Cluster Majeed Kassis.
N-Tier Architecture.
Improving searches through community clustering of information
Computer Hardware Mr. Singh ICS2O.
Chapter 1: Introduction
Job Scheduling in a Grid Computing Environment
Lecture 1: Network Operating Systems (NOS)
Grid Computing.
Chapter 1: Introduction
Cloud Computing Ed Lazowska August 2011 Bill & Melinda Gates Chair in
Grid Computing Colton Lewis.
Chapter 1: Introduction
Introduction to client/server architecture
Chapter 1: Introduction
Why PC Based Control ?.
Introduction.
Global Enterprise Search
Chapter 17: Database System Architectures
Web Server Administration
Ch 4. The Evolution of Analytic Scalability
CLUSTER COMPUTING.
Chapter 1: Introduction
Distributed computing deals with hardware
Subject Name: Operating System Concepts Subject Number:
Chapter 1: Introduction
Chapter 1: Introduction
Chapter 4 Multiprocessors
McGraw-Hill Technology Education
Database System Architectures
Chapter 1: Introduction
Chapter 1: Introduction
Chapter 1: Introduction
Presentation transcript:

CLUSTER COMPUTING Presented By, Navaneeth.C.Mouly 1AY05IS037 Under the guidance of, Prof.Umapathi G.R

AGENDA Abstract. Introduction. Why Clusters? Real Time Example. Architecture. Cluster Classification. Benefits. Dark side of cluster computing. Applications. Challenges. Conclusion.

Abstract Cluster computing is the technique of linking two or more computers into a network (usually through a local area network) in order to take advantage of the parallel processing power of those computers.

INTRODUCTION Very often applications need more computing power than a sequential computer can provide. One way of overcoming this limitation is to improve the operating speed of processors and other components so that they can offer the power required by computationally intensive applications. The viable and cost-effective solution is to connect multiple processors together and co-ordinate their computational efforts.

Shared Pool of Computing Resources: Processors, Memory, Disks Introduction contd.. Pfister points out, there are 3 ways to improve performance.. Work harder. Work smarter Get help Shared Pool of Computing Resources: Processors, Memory, Disks Interconnect

Why Clusters? The question may arise why clusters are designed and built when perfectly good commercial supercomputers are available on the market. Clusters are surprisingly powerful . They are cheap and easy way to take off-the-shelf components and combine them into a single supercomputer. In some areas of research clusters are actually faster than commercial supercomputer. Clusters also have the distinct advantage that they are simple to build using components available from hundreds of sources.

Real Time Example 270 GB RAM 8,700 GB Hard Disk Pentium 4 Xeon Cluster

Largest Cluster System IBM BlueGene, 2007 Memory: 73728 GB OS: CNK/SLES 9 Interconnect: Proprietary 106,496 nodes 478.2 Tera FLOPS on LINPACK

Architecture

Types Of Clusters High availability or Failover Clusters. Load Balancing Clusters. Parallel/Distributed processing clusters.

Failover Clusters

Load Balancing Cluster

Benefits Of Clusters 1. Reduced Cost 2. Processing Power 3. Improved Network Technology 4. Scalability 5. Availability

Dark Side Of Computing An eternal struggle in any IT department is in finding a method to squeeze the maximum processing power out of a limited budget. Today more than ever, enterprises require enormous processing power in order to manage their desktop applications, databases and knowledge management . Many business processes are extremely heavy users of IT resources, and yet IT budgets struggle to keep pace with the ever growing demand for yet more power.

Challenges The cluster computing concept also poses three pressing research challenges: A cluster should be a single computing resource and provide a single system image. This is in contrast to a distributed system where the nodes serve only as individual resources. The supporting operating system and communication Mechanism must be efficient enough to remove the performance Bottlenecks.

Challenges Cont’d… The system’s total computing power should increase proportionally to the increase in resources.

Applications 1. Google Search Engine. 2. Earthquake Simulation. Few important cluster application are: 1. Google Search Engine. 2. Earthquake Simulation. 3.Image Rendering.

Google contd… Google uses cluster computing to meet the huge quantity of worldwide search requests that comprise of a peak of thousands of queries per second. A single Google query needs to use at least tens of billions of processing cycles and access a few hundred megabytes of data in order to return satisfactory search result.

Google Cont’d… The first phase of query execution involves index servers consulting an inverted index that match each query keyword to a matching list of documents. In the second phase, document servers fetch each document from disk to extract the title and the keyword-in-context portion of the document. In addition to the 2 phases, the GWS also activates the spell checker and the ad server. The spell checker verifies that the spelling of the query keywords is correct, while the ad server generate advertisements that relate to the query and may therefore interest the user.

Conclusion Solve parallel processing paradox Offer incremental growth and matches with funding pattern New trends in hardware and software technologies are likely to make clusters more promising. Clusters based supercomputers can be seen everywhere!

? ANY QUESTIONS?