GRID COMPUTING
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GRID COMPUTING
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What is Grid Computing?
Grid Computing combines computers from multipleadministrative domains to reach a common goal, tosolve a single task.
It enables virtual organizations to share geographicallydistributed resources.
A resource is an entity that is to be sharedComputational Resource
Storage Resources
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Definition
Foster and Kesselman, 1998
―A computational grid is a hardware and
software infrastructure that provides dependable,
consistent, and inexpensive access to high-end
computational facilities.‖
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3-point checklist (Foster 2002)
1. Coordinates resources not subject to centralizedcontrol.
2. Uses standard, open, general purpose protocols andinterfaces.
3. Deliver nontrivial qualities of servicee.g., response time, throughput, availability,security
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Grid Architecture
Autonomous, globally distributed computers/clusters
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Why do we need Grid? Many large-scale problems cannot be solved by a single
computer.
Globally distributed data and resources.
Following table shows under utilized Infrastructure:
IT Resource Average Daytime
Utilization
Windows Servers <5%
UNIX Servers 15 – 20%
Desktops <5%
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ValuesDeveloped strong roots in the global academic and
research communities over the last decade
Integrating large scale computing facility and resources.
Re-use unutilized resources.
Leverage multidisciplinary collaboration.
Change the culture of academic research.
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ValuesGrid Computing for business enterprises
Accelerating product development.
Reducing infrastructure and operational costs.
Leveraging existing technology investments.
Increasing corporate productivity.
Strongest low cost but high throughput solution that
allows companies to optimize and leverage existing IT
infrastructure and investments .
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Grid Computing Value Element #1:
Leveraging Existing Hardware
Investments and ResourcesThere is a tremendous amount of unused capacity
in IT infrastructure at a typical enterprise.
Grids can be deployed on an existing
infrastructure.
Costs savings are not limited to hardware and
software expenditure.
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Grid Computing Value Element #2: Reducing
Operational Expenses
Grid Computing brings a level of automation and
ease previously unseen in the IT environments.
The ability of Grids to cross departmental andgeographical boundaries uniformly increases the
level of computational capacity across the whole
academic or enterprise.
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Grid Computing Value Element #3: Creating a
Scalable and Flexible Enterprise IT Infrastructure
Traditionally, IT managers have been forced
into making large-step function increases in
spending to accommodate slight increases in
infrastructure requirements.
Grid Computing allows companies to add
resources linearly based on real-time business
requirements.These resources can be derived from within
the enterprise or from utility computing
services.
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Grid Computing Value Element #3: Creating a
Scalable and Flexible Enterprise IT
Infrastructure
While departments will be making their
resources accessible to the whole enterprise,
Grid Computing still allows them to maintain
local control.
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Grid Computing Value Element #4:
Accelerating Product Development, Improving
Time to Market, and Raising CustomerSatisfaction
Grid Computing has a direct impact accelerating
product development at enterprises and helping bringproduct to market quicker.
for example, simulation times can get products
completed quickly.
This also provides the capability to perform a lot more
detailed product design.
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Grid Computing Value Element #5:
Increasing Productivity
Enterprises that have deployed Grid Computing are
seeing tremendous productivity gains. E.g.
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Risk Analysis
In this section we will evaluate the key risk
factors,
That usually plague technology deployments
and analyze the vulnerabilities of Grid
Computing deployments.
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Risk Analysis: Lock-in
Like most software (and hardware) vendors,
Grid Computing vendors would probably prefer it if their
software locked-in a customer for a recurring or a future
revenue stream.
Customers should pay keen attention to which vendors are
supporting the Grid Computing standards activities at the
Global Grid Forum.
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Risk Analysis: Project Implementation
failure
The final risk factor is of project failure,
either due to bad project management or incorrect needs
assessment.
One way to mitigate the risk of project failure is to take
advantage of hosted pilot and professional services offered
by grid software vendors.
Hosted pilots are conducted solely on the vendor’s datacenters and have no impact on the operations of the company.
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History of Grid Computing
Early to mid 1990s: Research projects in the academic andresearch community that were focused on distributed
computing.
One key area was developing tools that would allow
distributed high performance computing systems to actlike one large computer.
1995: The IEEE/ACM Super Computing conference in
San Diego 11 high speed networks were used to connect 17
sites with high-end computing resources for ademonstration to create one super ―metacomputer.‖
This demonstration was called I-Way and was led by Ian
Foster.
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History of Grid Computing
1996: GLOBUS was foundation tools for Grid
computing.
The research project was led by Ian Foster of ANL and
Carl Kesselman of University of Southern California.
1997: At Super Computing Conference
- 80 sites worldwide running software based on the
Globus Toolkit were connected together.
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History of Grid Computing
•
1997: Entropia- was launched to harness the idle computers worldwide
to solve problems of scientific interest.
2000: articles on Grid Computing moved from the trade
press to the popular press.
Today, large corporations such as IBM, SunMicrosystems and Intel are using for business
applications.
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Background: Related Technologies
High Performance Computing
Cluster computing
Peer-to-peer computing
Internet computing
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High Performance Computing
Traditionally called supercomputing.
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Cluster Computing
Cluster computing has been around since 1994.
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Cluster Architecture
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Peer to Peer Computing
Connect to other computers.
Can access files from any computer on the network.
Allows data sharing without going through centralserver.
Models:
- centralized model, such as the one used by Napster.
- decentralized model, like the one used by Gnutella.
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Peer to Peer Computing
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Internet computing
It utilizes the vast processing cycles available at
user’s desktops.
In this type of computing tasks can be broken down
into smaller subtasks and distributed over the
Internet for processing. Desktop clients periodically communicates with the
central server to receive tasks.
The central server aggregates the information
received from all the different desktops and compiles
the results.
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Grid ComputingGrid computing tries to bring, under one
definitional umbrella all the work being done in the
high performance, cluster, peer-to-peer, and
Internet computing arenas.
Some of the definitions of Grid Computing are as
follows:
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The flexible, secure, coordinated resource sharing
among dynamic collections of individuals, institutions,and resources.
The ability to form virtual, collaborative organizations
that share applications and data in an open
heterogeneous server environment in order to work on
common problems.
The Web provides us information — the grid allows us
to process it.
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A Grid Computing Model
Some of the key requirements:
Identity and Authentication.
Authorization and Policy.
Resource Discovery. Resource Characterization.
Resource Allocation.
Resource Management.
Accounting/Billing/Service Level Agreement (SLA).
Security.
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To overcome the systems problem,
a set of protocols and mechanisms need to be defined thataddress the security and policy concerns of the resource
owners and users.
A set of grid applications programming interfaces (APIs) and
software development toolkits (SDKs) need to be defined. They provide interfaces to the grid protocols and services as
well as facilitate application development by supplying
higher-level abstraction.
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A Grid Computing Model
The Fabric Layer
Includes the protocols and interfaces that providesaccess to the resources that are being shared suchas compute resources, data resources, etc.
The Connectivity Layer
Defines core protocols required for grid-specificnetwork transactions.
Utilizes the existing Internet protocols such as IP,Domain Name Service, various routing protocols.
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A Grid Computing Model
The Resource Layer defines protocols required to initiate and control
sharing of local resources. Protocols defined at this
layer include:
- Grid Resource Allocation Management (GRAM) —
Remote allocation, reservation, monitoring, and
control of resources
- GridFTP (FTP Extensions) –
High performance dataaccess and transport
- Grid Resource Information Service (GRIS) –
Access to structure and state information.
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A Grid Computing Model
The Collective Layer
defines protocols that provide system oriented (versus local) capabilities for wide scale deployment.
includes index or meta-directory services so that acustom view can be created of the resourcesavailable on the grid.
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A Grid Computing Model
The Application Layer
defines protocols and services that are targeted
toward a specific application or a class ofapplications.
Following figure shows the relationship between APIs, services, and protocols.
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Grid Computing Protocols
Grid Security Infrastructure
Grid Resource Allocation Management
Grid File Transfer Protocol
Grid Information Services
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Security: Grid Security Infrastructure
Security is defined in the resource layer of the grid
architecture.
The security problem in grid computing is
complex:
- resources are located in different administrativedomains.
- each resource potential having its own policies and
procedures.- there are different requirements by users, resource
owners, and developers.
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The user’s expectations are that a secure grid system
will be easy to use, provide single sign-on capability,
allow for delegation, and support all keyapplications.
The resource owners require that security shouldspecify local access control, have robust and detailed
auditing and accounting, and should be able to
integrate with local security infrastructure.
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From a developer’s standpoint, the grid security
protocol should have a robust API/SDK .
GSI for grid has been defined by creating extension to
Secure Socket Layer/ Transport Layer Security
(SSL/TLS) and X.509. Following diagram shows the Grid Security
Infrastructure in action.
The request submitted is as follows: ―Create processes at
A and B that Communicate & Access Files at C.‖
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R M t G id R
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Resource Management: Grid Resource
Allocation Management Protocol
GRAM allows programs to be started on remoteresources.
Resource Specification Language (RSL): a common
notation for exchange of information between
applications, resource brokers, and local resourcemanagers.
RSL provides two types of information:
– Resource requirements: machine type, number of
nodes, memory, etc.
– Job configuration: directory, executable, arguments,
environment
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GRAM
GRAM protocol is a simple, HTTP-based remote procedure call (RPC).
It sends messages such as job request, job cancel, status,
and signal.
Event notifications for state changes include pending,
active, done, failed, or suspended.
Data Transfer: Grid File Transfer
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Data Transfer: Grid File Transfer
Protocol
Users who need access to the data are distributed across theglobe.
Key requirement for data-intensive grids is high-speed and
reliable access to remote data.
The standard FTP protocol has been extended while
preserving interoperability with existing servers to develop
GridFTP.
Information Services: Grid Information
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Information Services: Grid Information
Services
A set of protocols and APIs defined in the resource layer,
provides key information about the grid infrastructure.
Grid Information Service (GIS) provides access to staticand dynamic information regarding a grid’s various
components,
that includes the type and state of available resources.
Th f G id I f i
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There are two types of Grid Information
Services.
The Grid Resource Information Service (GRIS):
The GRIS supplies information about a specificresource.
Grid Index Information Service (GIIS):
GIIS provides a collection of information that has beengathered from multiple GRIS servers.
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Conclusion
Grid Computing enables virtual organizations, toshare geographically distributed resources.
Resources can be supercomputers, clusters, desktopstorage systems, sensors, scientific instruments, etc.
Grid Computing is not a new concept. It leveragesknowledge acquired by high performance computing,cluster computing, peer to peering, and Internetcomputing communities.
Grid Computing protocols are based on protocols
developed and refined by the Internet community.Existing protocols have been extended to provide gridspecific functionality.