Case Study Report PresentationGrid computing: The Grid (Mar 05, 2013) By Jivan Nepali, 066 BCT 517 Laxmi Kadariya, 066 BCT 518 Narayan Pd. Kandel, 066 BCT 520
IS There Any Computer Systemthat isn’t a Grid? Bio Data Knowledge Grids Grids Grids Commodity Compute Science Grids Grids Grids Cluster Tera Sensor Grids Grids Grids
Definitions “A computational grid is a hardware and software infrastructure that provides dependable, consistent, pervasive, and inexpensive access to high-end computational capabilities.” – Foster & Kesselman, 1998 “Grid computing is concerned with coordinated resource sharing and problem solving in dynamic, multi-institutional virtual organizations (VOs).” - Foster & Tuecke, 2000 It is NOT a cluster Architecture!
Grid: Building Blocks Networks Link together geographically distributed resources and allow them to be used collectively Computational ‘Nodes’ on the Grid Networks connect resources on the Grid – computational resources with data storage 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 being built
Grid Computing: ArchitecturalModel Hourglass Model Thin center: few standards Application Layer Wide top: many high-level Collective Layer behaviors can be mapped Wide bottom: many underlying Connectivity Layer Resource Layer technologies and systems Fabric Layer
Grid Models Distributed Super-Computing Aggregate computational resources to tackle problems that cannot be solved by a single system High-throughput Computing Schedule large numbers of independent tasks to exploit unused CPU cycles On-demand Computing Use Grid capabilities to meet short-term requirements for resources that cannot conveniently be located locally Data-Intensive Computing Synthesize data in geographically distributed repositories Collaborative Computing Enable shared use of data archives and simulations
Grid Computing: Challenges No clear Standard Debate on Concept Difficult to Develop Limited area & Applications Lack of Grid-enabled Software Centralized Management Security Management and Administration
Grid Computing: Applications Life Science Application Computational biology, bioinformatics, genomics, computational neuroscience e.g. the Protein Data Bank, the myGrid Project, the Biomedical Information Research Network (BIRN), MCell]. Engineering-oriented Application NASA operation its research through grid Data-oriented Application Data is emerging as the ‘killer application’ of the Grid. e.g. Distributed Aircraft Maintenance Environment (DAME).
Grid Computing: ApplicationsCont... Physical Science Application The National Virtual Observatory Project in the United States is using the Grid to federate sky surveys from several different telescopes Commercial Application Virtual 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
References Foster, I. & Kesselman C. (2005). “The Grid in aNutshell”. Mathematics and Computer Science Division,Argonne National Laboratory, Information SciencesInstitute, University of Southern California, USA. Engelen van R. (2008). “Concepts & Architecture ofGrid Computing”. Leiden University, Netherlands. Berman F., Hey A.J.G. & Fox G.C. (2003). “GridComputing – Making the Global Infrastructure aReality”. John Wiley & Sons Ltd, Chichester, England. Abbas A. (2004). “Grid Computing: A Practical Guideto Technology & Applications”. Firewall Media, AnImprint of Laxmi Publications Pvt. Ltd., Golden House,Daryaganj, New Delhi, India.