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TRANSCRIPT
GRID COMPUTING
4 UNIT
IS There Any Computer System that
isn’t a Grid?
Data Grids
Knowledge Grids
Bio Grids
Compute
GridsCommodity
GridsScience Grids
Tera Grids
Sensor Grids
Cluster Grids
Definitions
“A computational grid is a hardware and softwareinfrastructure that provides dependable,consistent, pervasive, and inexpensive access tohigh-end computational capabilities.”
– Foster & Kesselman,1998
“Grid computing is concerned with coordinatedresource sharing and problem solving in dynamic,multi-institutional virtual organizations(VOs).”
- Foster & Tuecke,2000
It is NOT a clusterArchitecture!
Grid: Building Blocks
Networks
▪ Link together geographically distributed resources and allow them to be usedcollectively
Computational ‘Nodes’ on the Grid
▪ Networks connect resources on the Grid –computational resources with datastorage
Pulling it together
▪ It involves the coordination and partnerships among the remaining blocks for the complete model of a Grid
Common Infrastructure: Standards
▪Grid Standards to developers &users
▪ Standards on which the Grid is beingbuilt
Connectivity Layer
Grid Computing: Architectural M
odel Hourglass Model
▪ Thin center: few standards
▪Wide top: manyhigh-level
behaviors can be mapped
▪Wide bottom: manyunderlying
technologies and systems
Collective Layer
Application Layer
Fabric Layer
Resource Layer
Grid Models
DistributedSuper-Computing
▪ Aggregate computational resources to tackle problems that cannotbe solved by a single system
High-throughputComputing
▪ Schedule large numbers of independent tasks to exploit unused CPUcycles
On-demandComputing▪ Use Grid capabilities to meet short-term
requirements for resources that cannot conveniently be locatedlocally
Data-Intensive Computing▪ Synthesize data in geographically distributed
repositories
Collaborative Computing▪ Enable shared use of data archives andsimulations
Grid Computing: Challenges
No clear Standard
Debate on Concept
Difficult to Develop
Limited area & Applications
Lack of Grid-enabled Software
Centralized Management
Security
Management andAdministration
Grid Computing: Applications
Life ScienceApplicationComputational biology, bioinformatics, genomics,computational neurosciencee.g. the Protein Data Bank, the myGrid Project, the Biomedical Information Research Network (BIRN), MCell].
Engineering-oriented ApplicationNASA operation its research through grid
Data-oriented ApplicationData is emerging as the ‘killer application’ ofthe Grid.e.g. Distributed Aircraft Maintenance Environment (DAME).
Grid
Computing:
Applications C
ont... Physical ScienceApplication
The National Virtual Observatory Project in the United Statesis using the Grid to federate sky surveys from severaldifferent telescopes
CommercialApplicationVirtual server hosting,
Disaster recovery,
Heterogeneous workload management,
End-to-end systems management,
End-to-end automation
Reducing up-front investment
Accessing new capability more quickly,
Better performance
Grid Protocol
Grid protocols play major role in implementing services that facilitate coordinated resource sharing across diverse organizations
What is protocol ?
In simplest words, a protocol can be defined as a communication procedure with
the specific rules governing the syntax,
semantics, sequence of statements, and synchronization of communication
between communicating entities
Grid Protocol: It is a protocol that mediates between user and resource during access to any resource in Grid environment.
Classification Grid Protocols
• Grid network communication and
• Grid data transfer protocols,
• Grid information security protocols
• Grid resource information protocols
• Grid management protocols
• Grid interface protocols
All the classified protocolsare also organized into layers of the Hourglass model of Grid architecture to understand dependency among these protocols
Contents
What is Grid Computing?
Why need grid computing?
Types of grid
Characteristics of Grid
Benefits
Applications
Advantage & Disadvantages
17
What is Grid Computing?Allows sharing and coordinated use of diverse resources in dynamic, distributed “virtual organizations”.
What is a Grid?❖ Grid Computing is a technique in which the idle systems in the Network and
their “wasted “CPU cycles can be efficiently used by uniting pools of servers,
storage systems and networks into a single large virtual system for resource sharing dynamically at runtime.
❖ These systems can be distributed across the globe; they're heterogeneous (some PCs, some servers, maybe mainframes and supercomputers); somewhat autonomous (a Grid can potentially access resources indifferent organizations).
❖ Grid computing is form of networking unlike conventional network thatfocus on communications amongdevices.
What is the Grid?
Internet
Internet
Grid Computing Resource
Certificate
Certificate
Gatekeeper
Jane User
Why need Grid Computing?❖Exploiting under utilized resources
❖Parallel CPU capacity
❖Virtual resources and virtual organizations for collaboration
❖Access to additional resources
❖Many large-scale problems cannot be solved by a singlecomputer
❖Globally distributed data and resources
Types of Grids❖Computational Grid:
A computational grid is focused on setting aside resources specifically for computing power. In this type of grid, most of the machines are high-performance servers.
❖Scavenging grid:
A scavenging grid is most commonly used with large numbers of desktop machines. Machines are scavenged for available CPU cycles and other resources. Owners of the desktop machines are usually given control over when their resources are available to participate in the grid.
❖Data Grid:
A data grid is responsible for housing and providing access to dataacross multiple organizations. Users are not concerned with where this data is located as long as they have access to the data.
Characteristics of Grids
Grids coordinate resources that are not subject to centralized control.
Grids use standard, open, general-purpose protocols and interfaces.
Grids deliver high qualities of service.
❖Grid User Roles
(A User’sPerspective)
Enrolling and installing grid software
Logging onto the grid
Queries and submitting jobs
Data configuration
Monitoring progress and recovery
Reserving resources
❖Grid User Roles
(An Administrator’s Perspective)
Planning
Installation
Managing enrollment of donors and users
Certificate authority
Resource management
Data sharing
IssuesSecurity:
Security issues include secure authentication, access rightsand privileges. Reliable and secure communications, perhaps with encryption, are also arequirement.
Maintaining confidentiality and privacy will also be issues if you are transferring personal data.
Performance:
For a grid performance is the main key is to delivernontrivialqualities of service “. Some grid services might fall short because the
scattering and gathering steps can incur significantdelay.
Grid performances include resource availability and reliability, utilization and load, response time, delay and delay variation. Data Integrity is another consideration.
Benefits
(1)BUSSINESS BENEFITS:
➢ Can help improve productivity and collaboration.
➢ Bring together not only IT resources but alsopeople.
➢ Create flexible, resilient operational infrastructures.
(2) INFRASTRUCTURE OPTIMIZATION:
➢ Consolidate workload management.
➢ Reduce cycle times.
Benefits…
(3) INCREASE ACCESS TO DATA AND COLLABORATION:
➢ Federate data and distribute it globally.
➢ Support large multi-disciplinary collaboration..
➢ Enable collaboration across organizations and among businesses.
(4) RESILIENT, HIGHLY AVAILABLE INFRASTRUCTURE:
➢Balance workloads.
➢Foster business community
➢Enable recovery and failure.
ADVANTAGES:➢ Can solve larger, more complex problems in a shorter time
➢ Easier to collaborate with otherorganizations
➢ Make better use of existing hardware
DISADVANTAGES:➢ Grid software and standards are still evolving.
➢ Learning curve to get started.
➢ Non-interactive job submission.
Characteristics of Grid Applications
Data acquired by scientific instruments.
Data are stored in archives on separate, perhapsgeographically-separated sites.
Data are managed by teams belonging to differentorganizations.
Large quantities of data (tera- or petabytes) arecollected.
Software used to analyze and summarize the rawdata.