Group # 14 Dhairya Gala Priyank Shah. Introduction to Grid Appliance The Grid appliance is a plug-and-play virtual machine appliance intended for Grid.

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Presentation transcript:

Group # 14 Dhairya Gala Priyank Shah

Introduction to Grid Appliance The Grid appliance is a plug-and-play virtual machine appliance intended for Grid computing to execute many long-running simulations concurrently in resources across virtual machines that can be distributed across the world.

Features: Setting up on demand ad-hoc virtual resource pools. OS independent. Use of VM’s helps run multiple operating systems simultaneously and isolated from each other, but on the same computer. Application independent, i.e. Supports existing, unmodified applications. Easy to configure and use. Plug and play solution that can run on the desktop.

Works on: The same appliance software: Works in an open wide-area environment E.g. global bootstrap infrastructure Works in a local-area environment E.g. your department, lab, college Works in a private wide-area environment A “virtual organization” Strong public key infrastructure for security; can connect resources across a restricted set of institutions.

Insight: Grid Appliance is a virtual machine with its own operating system. Linux and Grid middleware Connects individual appliances in the virtual network using IPOP at P2P level. Uses Condor for job scheduling.

Proposal: Configure Twister Appliance environment by packaging Twister Iterative MapReduce along with the Grid Appliance framework. Run distributed applications over the configured Virtual network and existing clusters like bare-metal. Evaluate the computational performance of the two environments. Evaluate against (Parameters): Different applications. Data size. Number of nodes. Comment on its real world use.

Timeline: TaskSchedule Configure Twister Appliance environmentOct 24, 2011 Run distributed applications over the configured Virtual network Oct 31, 2011 Running distributed applications over existing clusters like bare-metal Nov 14, 2011 Evaluate the computational performance of the two environments Nov 28, 2011

Thank You