grid computiing

GRID COMPUTIING

Flow of Presentation• INTRODUCTION TO GRID COMPUTING• FACTS AND FIGURES• WHY NOT POPULAR• SOME TERMS BEFORE WE RECOMMEND• PROBLEM WITH IT INFRASTUECTURE SERVICES• SOLUTION• BUSINESS ASPECT• YOUR RECOMMENDATION OR SCOPE OF

RECOMMENDATON

DEFINITION• Grid computing is the federation of computer

resources from multiple administrative domains to reach a common goal.

• “computational of grid is a hardware and software infrastructure that provides independent pervasive and inexpensive access to high end computational capabilities”.

Methods of Grid Computing• Distributed Supercomputing• High-Throughput Computing• On-Demand Computing• Collaborative Computing• Logistical Networking

Distributed Supercomputing• Combining multiple high-capacity resources on a

computational grid into a single, virtual distributed supercomputer.

• Tackle problems that cannot be solved on a single system.

High-Throughput Computing

• Uses the grid to schedule large numbers of loosely coupled or independent tasks, with the goal of putting unused processor cycles to work.

On-Demand Computing

• Uses grid capabilities to meet short-term requirements for resources that are not locally accessible.

• Models real-time computing demands.

Collaborative Computing

• Concerned primarily with enabling and enhancing human-to-human interactions.

• Applications are often structured in terms of a virtual shared space.

Logistical Networking

• Global scheduling and optimization of data movement.

• Contrasts with traditional networking, which does not explicitly model storage resources in the network.

• Called "logistical" because of the analogy it bears with the systems of warehouses, depots, and distribution channels.

Business Benefits

Improve efficiency by improving computational capabilities

Bring together not only IT resources but also people. Create flexible, resilient operational infrastructures Address rapid fluctuations in customer demands.

Technology benefits Federate data and distribute it globally.• Support large multi-disciplinary collaboration

across organizations and business. Enable recovery and failure Ability to run large-scale applications comprising

thousands of computes, for wide range of applications.

Reduces signal latency – the delay that builds up as data are transmitted over the Internet.

Why need Grid Computing?

• Core networking technology now accelerates at a much faster rate than advances in microprocessor speeds

• Exploiting under utilized resources• Parallel CPU capacity• Virtual resources and virtual organizations for

collaboration• Access to additional resources

Software implementations and middleware

• Advanced Resource Connector (NorduGrid's ARC)• Berkeley Open Infrastructure for Network Computing (BOINC)• Globus Toolkit• Sun Grid Engine• ProActive• UNICORE• SDSC Storage resource broker (data grid)• gLite (EGEE)• NInf GridRPC• IceGrid• Java CoG Kit

• Alchemi • GridGain • gridGISTICS • Gridbus Middleware• Vishwa • UGP • GRIA

Analyze Grid Performance• Grid computing middleware

S/W which is used to manage the internal working of a grid computing system.

Eg: 1:Alchemi: A .NET-based Enterprise Grid

System and Framework.

How Alchemi Works There are four types of distributed components

(nodes) involved in the construction of Alchemi grids and execution of grid applications: Manager, Executor, User & Cross-Platform Manager.

• A grid is created by installing Executors on each machine that is to be part of the grid and linking them to a central Manager component.

Dedicated No Dedicated

Executors

• Dedicated :-Meaning the Manager initiates thread execution directly.Dedicated Executors are more suited to an intranet

environment

• No-Dedicated:-Meaning that thread execution is initiated by the Executor.Works through firewalls and NAT servers since there is

only one-way communication between the Executor and Manager.

Non-dedicated Executors are more suited to the Internet environment.

• Users can develop, execute and monitor grid applications using the .NET API and tools which are part of the Alchemi SDK. Alchemi offers a powerful grid thread programming model.

• An optional component (not shown in fig:) is the Cross Platform Manager web service which offers interoperability with custom non-.NET grid middleware.

Installation, Configuration and Operation

Application• Server performance by integration with QA and

Test (preventive measure )• Temp. solution for outdated system to improve

performance (longevity measure)• Making normal graphics computer to a high

performance gaming computer

Preventive Measure • When CPU utilization going high• Threat of downtime• Threat of 100% processor utilization lead to

system crash

Parameters for performance measurement• CPU utilization• Downtime• Performance improvement

Flow chart

Longevity application

• Outdated server• Not much capital to invest into it instantly

Grid computing

Outdated server

Improved performance/ Longer life

Parameters• CPU utilization• Processing capabilities• Processing speed• Processing time

Flow chart

Gaming

Parameters • Cost• Process capability• Processing speed• Resource sharing

Flow chart

• The Department of Information Technology (DIT), Government of India has funded the Centre for

Development of Advanced Computing (C-DAC) to deploy the nation-wide computational grid 'GARUDA' which will connect 17 cities across the country in its Proof of Concept (PoC) phase with an aim to bring "Grid" networked computing to research labs and industry. A total of 45 institutions have been connected. GARUDA will accelerate India’s drive to turn its substantial research investment into tangible economic benefits.

• The GARUDA High-Speed network is a Layer 2/3 MPLS Virtual Private Network (VPN) connecting select 45 institutions across 17 cities at 10/100 Mbps with Stringent Service Level Agreements with the service provider.

Disadvantages of Grid Computing

Resource sharing is further complicated when grid is introduced as a solution for utility computing where commercial applications and resources become available as shareable and on demand resources.

The concept of commercial on-demand shareable adds new, more difficult challenges to the already complicated grid problem list including service level features, accounting, usage metering, flexible pricing, federated security, scalability, and open-ended integration.  

Some applications may need to be tweaked to take full advantage of the new model.

Licensing across many servers may make it prohibitive for some apps. Vendors are starting to be more flexible with environment like this.