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Grid Computing

Grid Computing. Trenton Fairbanks Sung Wan Kim Laura Samartin Jumpei Takatsuki. Why Grid Computing?. 40% Mainframes are idle 90% Unix servers are idle 95% PC servers are idle 0-15% Mainframes are idle in peak-hour 70% PC servers are idle in peak-hour.

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Grid Computing

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  1. Grid Computing Trenton Fairbanks Sung Wan Kim Laura Samartin Jumpei Takatsuki

  2. Why Grid Computing? • 40% Mainframes are idle • 90% Unix servers are idle • 95% PC servers are idle • 0-15% Mainframes are idle in peak-hour • 70% PC servers are idle in peak-hour Source: “Grid Computing” Dr Daron G Green

  3. How Grid Computing Works Idol time Idol CPU Super computer, Big mainframe… Idol CPU Idol time Source: “The Evolving Computing Model: Grid Computing” Michael Teyssedre

  4. How Grid Computing Works Virtual machine Virtual CPU… Idol time Idol CPU Idol CPU Idol time Source: “The Evolving Computing Model: Grid Computing” Michael Teyssedre

  5. How Grid Computing Works Grid Computing 0% idol 0% idol 0% idol 0% idol Source: “The Evolving Computing Model: Grid Computing” Michael Teyssedre

  6. Definition Grid computing is… • A distributed computing system • Where a group of computers are connected • To create and work as one large virtual computing power, storage, database, application, and service

  7. Definition Grid computing… • Allows a group of computers to share the system securely and • Optimizes their collective resources to meet required workloads • By using open standards

  8. Key Technologies • OGSA: Open Grid Services Architecture • Web services: XML, WSDL, SOAP

  9. Open Grid Services Architecture OGSA architecture with Web services-enabled service interface Applications Web Services OGSA Security Workflow Database File systems Directory Messaging Servers Storage Network Source: "Evolution of grid computing architecture and grid adoption models" J. Joseph, M. Ernest, and C. Fellenstein

  10. Communities • Global Grid Forum • The Globus Alliance: Globus Toolkit 4.0

  11. How it Evolves Utility computing Service grid Data grid Virtualization Service-oriented Open standard Processing grid

  12. Early adopters • Academic • Big science • Life science • Nuclear engineering • Simulation…

  13. Market Potential • Financial services:risk management and compliance • Automotive:acceleration of product development • Petroleum:discovery of oils Source: “Perspectives on grid: Grid computing - next-generation distributed computing" Matt Haynos, 01/27/04

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