Grid Computing – Introduction

1. Grid Computing –Introduction Sathish Vadhiyar

2. Resource Discovery & Allocation Generic Grid Architecture/Components Problem Solving Environments Application Science Portals Grid Access & Info User Portals Scheduling & Co- Scheduling Service Layers Naming & Files Fault Tolerance Events Authentication Computers Data bases Online instruments Software Resource Layer High speed networks and routers

3. OK, I have built some software.Is mine a Grid software? Ian Foster’s three-point checklist: • coordinates resources not subject to centralized control • using standard, open, general-purpose protocols and interfaces • to deliver non-trivial qualities of service

4. Some Myriad Definitions • “Coordinated resource sharing and problem solving in dynamic, multi-institutional virtual organizations” • “Anatomy of the grid – highly flexible sharing relationships, sophisticated and precise levels of control over use of shared resources, sharing of varied resources, diverse usage modes.” • “Controlled sharing – not free access” • “Infrastructure enabling integrated, collaborative use of resources” • “Sharing resources can vary dynamically vary over time” • More colorful definitions keep coming • Common keywords: Coordinated, shared, multi-institutions, controlled, usage, collaboration

5. Differences with Other Technologies • Enterprise-level distributed computing – limited cross-organizational support • Current distributed computing approaches do not provide a general resource-sharing framework that addresses Virtual Organization (VO) requirements. • WWW – just client-server. Lacks richer interaction models • Technologies like CORBA, Java, DCOM – single organization, limited scope • Some of the Grid techniques complement existing techniques.

6. Grids vs Conventional Distributed Computing (Nemeth and Sunderam) • Distributed Computing • Virtual Pool of nodes • Set of nodes static. Users have login access. They explicitly know about nodes • VM constructed out of a priori knowledge • Resource assignment implicit • Resource owning • Grid Computing • Virtual Pool of wide range of resources • Set of nodes static/dynamic. Resources dynamic and diverse – can vary in number, can vary in performance • Difficult for user to get a priori knowledge • User abstraction at resource layers • Resource sharing • Apps. – resource requirements more than can be solved on machines “owned”

7. Continued

8. Nemeth and Sunderam

9. Motivating examples

10. SETI@home • To search new life and civilizations • Use individual computers’ idle time through running SETI@home screen saver • Screen savers retrieves data, analyzes and reports results back to SETI project • Looking for extra-terrestrial signal over a 12-second period • Each work unit takes 10 to 50 hours on an average computer – 2.4 to 3.8 trillion floating point operations

11. Steps and Statistics Data collected from Arecibo telescope in Puerto Rico onto tapes and shipped to SETI@home lab in UC, Berkeley. Break tapes -> work units -> given to users Find candidate signals reported from users • Other steps: • Checking data integrity • Removing radio frequency interference (RFI) • Identify final candidates Statistics: 208,174,383 work units 1,261 tapes Images and statistics from SETI web site

12. Climateprediction.net • Forecast climate in 21st century • 3 steps – explore current model, validate against past climate, forecast 21st century climate • Different models (in terms of initial conditions, forcing [volcanoes, solar activity etc.], parameters [approximations or ranges of fixed values in the model. E.g. ice size in ocean, friction between different ocean layers]) distributed to different users • Massive ensemble experiment From climateprediction.net

13. Steps From climateprediction.net

14. Prime number generation - GIMPS • Finding Mersenne prime numbers – 2P-1 • GIMPS is to find largest known Mersenne prime numbers • 41st Mersenne prime found recently - 224,036,583-1 with 7,235,733 decimal digits !!! • GIMPS found seven • For mostly fun • 1000s of Pentium PCs involved. Setup similar to SETI@home • PCs do primality tests

15. Other @home Projects • genome@home – designing new genes that form working proteins in cells. To study protein evolution. Individual PCs design protein sequences • folding@home – to study why proteins fold/misfold. Each PC simulates a particular kind of protein folding • evolution@home – to understand and simulate evolution • Compute-against-cancer – to study cancer cells and to design new cancer drugs • FightAids@home – screen millions of candidate drug compounds • Distributed.net – cryptography, secret key challenges • More can be found in http://boinc.berkeley.edu/projects.php

16. The Telescience project • Grid for remote accessing microscopes, data analysis and visualization • To study complex interactions of molecular and cellular biological structures and hence understand brain diseases • Interactively steer a 400,000-volt electron microscope at UC San Diego From TeleScience web site

17. References • http://www.globus.org/research/papers/chapter2.pdf • What is the Grid? A three point checklist. Ian Foster. GRIDToday, July 20, 2002. • The Anatomy of the Grid: Enabling scalable virtual organizations. I. Foster, C. Kesselman, S. Tuecke. IJSA. 15(3), 2001. • A Complete History of the Grid. Dr. Rob Baxter. Pdf • Zsolt Nemeth, Mauro Migliardi, Dawid Kurzyniec and Vaidy Sunderam. A comparative analysis of PVM/MPI and computational grids. In EuroPVM/MPI 2002. • Zsolt Nemeth and Vaidy Sunderam. A comparison of conventional distributed computing environments and computational grids. ICCS 2002. • Zsolt Nemeth and Vaidy Sunderam. A formal framework for defining grid systems. CCGrid 2002.