Grid and cluster_computing_chapter1

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Grid and cluster_computing_chapter1

  1. 1. Grid and Cluster Computing - Bharath Kumar M bharatkumarm@yahoo.com
  2. 2. 10CS845 VTU 10 scheme  VIII Semester elective subject  Part-B – Unit 5 
  3. 3. What is a Grid?  Early defs: Foster and Kesselman, 1998 ◦ “A computational grid is a hardware and software infrastructure that provides dependable, consistent, pervasive, and inexpensive access to high-end computational facilities”  Kleinrock 1969: ◦ “We will probably see the spread of ‘computer utilities’, which, like present electric and telephone utilities, will service individual homes and offices across the country.”  IBM : ◦ “A grid is a collection of distributed computing resources over a local or wide area network, that appear to an end-user or application as one large virtual computing system”
  4. 4. Vision of Grid:  Create virtual dynamic organizations through secure, coordinated resource sharing among individuals and institutions.  An approach that spans locations, organizations, machine architectures and software boundaries to provide unlimited power, collaboration and information access to everyone connected to the grid  The Internet is about getting computers together (connected), grid computing is about getting computers work together.  Combine the QoS of enterprise computing with ability to share the heterogeneous distributed resources – everything from applications to data storage and servers.
  5. 5. Grid basics:  Grid computing is a middleware software that manages and executes all the activities related to: ◦ Identification of resources ◦ Allocation and deallocation of resources ◦ Consolidation of resources  Organizations having under-utilized or over-utilized resources need a dynamically equitable distribution of resources.
  6. 6. Server Hardware
  7. 7. The Data Centre  Before the data centre concepts came, organizations maintained own servers and specialized software.  This approach was expensive and redundant  Data Centres shared resources with organizations.  Organizations connected to a data centre may not be able to use resources from other data centres  Concept of grid computing enables multiple data centres (same or different organizations) to be networked and shared.  Grid is a combination of: ◦ Distributed computing ◦ High Performance computing ◦ Disposable computing Grid provides a metacomputing environment, which can be a megacomputing facility for the users.  Grid provides computational utility to its consumers 
  8. 8. Cluster Computing and Grid computing  Clusters are aggregations of processors in parallel configurations.  Resource allocation is performed by a centralized resource manager and scheduling system.  All nodes of a cluster work cooperatively together, as a unified resource.  Grid has resource manager for each node. Grid does not provide a single system view.  Some grids are collections of clusters. Example: NSF Tera Grid 
  9. 9. Metacomputing  Metacomputing is all computing and computing-oriented activity which involves computing knowledge (science and technology) utilized for the research, development and application of different types of computing. ---- Wikipedia  Use of powerful computing resources, transparently available to the user via a networked environment is Metacomputing.  Three essential steps to achieve goals of metacomputing are: ◦ To integrate the large number of individual hardware and software resources into a combined networked resource ◦ To deploy and implement a middleware to provide a transparent view of resources available ◦ To develop and deploy optimal applications on the distributed metacomputing environment to take advantage of the resources.
  10. 10.  Challenges in metacomputing –  -Viability of the linking speeds for realistic application execution  -ability and feasibility to execute parallely the components of an application  Resources and originating points of data are geographically distributed – may need to processed in a distributed manner  Metacomputing is useful when a single point usage is required for large remotely located resources.  Metacomputing encompasses two broad categories:  - Seamless access to high performance  -Linking of computing resources, instruments and other resources.
  11. 11. Metacomputer composition  Metacomputer is a virtual computer – its components are individually not important  Metacomputer consists of: ◦ -Processors and memory  Single virtual view of several (large number) of processors and their associated memory units ◦ -Network and communication software  Interconnected network of physically distributed processors  High bandwidth and low latency is required to provide rapid and reliable communication ◦ -Remote data access and retrieval  Date sizing upto petabytes.  Retrieval, replication and mirroring support.  Ability to manage and manipulate large quantity of remote data ◦ -Virtual environment  A software like an operating system, that can configure, manage and maintain metacomputing env.
  12. 12. Evolution of Metacomputing projects  FAFNER (1995) - (Factoring via Network-Enabled Recursion) ◦ Finding factors of large numbers parallely, over a large network of mathematicians. ◦ Started by Bellcore Labs, Syracuse University ◦ To distribute the code for factorizing and related information data  I-WAY (1995) - Information Wide Area Year ◦ Experimental high-performance network, linking many servers and addressed virtualization environments
  13. 13. Scientific, Business and e-Governance Grids  Grid computing approach helped to all computing communities – businesses, scientific research and government applications.  Scientific grids – users belong to only scientist groups  Business grids – users may belong any citizen groups using business services.  The number of users in Businesses and e-Governance are high – hence setting up such girds are more complex  The user interfaces, access speeds and data sizes will be large.
  14. 14. Web Services and Grid Computing  Users of business and e-Governance grids will need we services over internet  Users of business grids will not be interested in hardware and software locations  They are not interested in resource allocation management as well.  Hence the need for integrating web services with grids.
  15. 15. Business computing and the Grid – a Potential Win-win situation  Grid was initially utilized for applications such as: weather forecasting models, molecular modelling, bioinformatics, drug design, etc  By harnessing the grid approach businesses can achieve cost reduction and better QoS.  Grid leverages its extensive information capabilities to support the processing and storage requirements to complete a task.  Hence grid can provide the maximum resource utilization, providing fastest, cheapest and maximum satisfaction.
  16. 16.  The grid computing for business is based on three factors: 1. The ability of grid to ensure more cost-effective use of a given amount of computer resources 2. A methodology to solve any difficult or large problem by using grid as a ‘large computer’ 3. All the computing resources of a grid such as CPUs, disk storage systems and software packages can be comparatively and synergistically harnessed and managed in collaboration towards a common business objective.
  17. 17. E-Governance and the Grid  Service oriented architecture  OGSA – Open grid services architecture  Globus toolkit
  18. 18. References:  Grid and Cluster Computing – C.S.R. Prabhu, PHI , Jan 2012

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