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Parallel Computing With High Performance Computing Clusters (HPCs)

Parallel Computing With High Performance Computing Clusters (HPCs). By Jeremy Cathey. Super Computing. Began as early as late 1950’s Compute large mathematical calculations Large scale task management. Advantages of Super Computing. Power Configuration Administration.

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Parallel Computing With High Performance Computing Clusters (HPCs)

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  1. Parallel Computing With High Performance Computing Clusters (HPCs) By Jeremy Cathey

  2. Super Computing • Began as early as late 1950’s • Compute large mathematical calculations • Large scale task management

  3. Advantages of Super Computing • Power • Configuration • Administration Disadvantages of Super Computing • Cost • Scalability • Diversity

  4. Alternatives • Distributed Computing - Uses queuing system to manage multiple tasks on several computers serially • Parallel Computing - Uses several computers to work on one task in parallel

  5. Implementations of Alternatives • Shared Processors (Multiple Processors) • Shared Memory Pools • Messaging Systems

  6. Advantages of Parallel Computing • Cost • Scalability • Diversity Disadvantages of Parallel Computing • Power • Configuration • Administration

  7. Parallelization Techniques • Manual - Parallelization implemented by the programmer at creation of the program • Automatic - Parallelization implemented on the fly by the operating system

  8. Advantages of Manual Parallelization • Specific Customization • More Effective Parallelization Disadvantages of Manual Parallelization • Difficult to Implement • Not Very Portable

  9. Advantages of Automatic Parallelization • Easier to Implement • Portable Applications Disadvantages of Automatic Parallelization • Less Effective Parallelization

  10. Project Goals • Reduce Disadvantages of Parallel Computing • Learn more about Operating System development and parallel optimization • Provide a solution for optimized parallel computing for Dr. Salazar’s research

  11. Goal Techniques • Reduce power issue of parallel computing machines by custom building an operating system kernel for optimization • Research and Improve Open-Mosix Parallelization Technique • Create a cluster that is easy to assemble and disassemble • Create and/or implement an interface that simplifies cluster administration

  12. Operating System Choice • Windows Vs. Linux • Live vs. Install • Community Support • Creation vs. Customization • HARDWARE SUPPORT!!!!!!!! Bill!!!!

  13. Implementation • Dr. Salazar: Professor of Chemistry • Use cluster to reduce time for sophisticated mathematical computation

  14. Simulation Details • 2.6 GHz Computer - 2GB RAM • 1.2 GHz Computer - 256MB RAM • 5 Parallel 1.2GHz Computers – 1.28GB RAM

  15. Parallel

  16. Hurdles • HARDWARE DETECTION!!!!!! • HARDWARE DETECTION!!!!!! • HARDWARE DETECTION!!!!!! Did I Mention: • HARDWARE DETECTION!!!!!! • HARDWARE DETECTION!!!!!! • HARDWARE DETECTION!!!!!!

  17. Improvements • Redesign Operating System Kernel For More Advanced HARDWARE DETECTION • Try Simulations on More Advanced Computers • Create Custom Installer for Distribution

  18. Special Thanks • Dr. Kirk: For providing computers for experiment and for finding a place for me to store my project • My Wife: For not killing me while I had to store my project at our home • Dr. Wilms: for providing older versions of Red Hat, and for Operating Systems Class • Dr. Salazar: For time and effort spent helping me understand a SMALL part of his research

  19. Questions? Comments? Derogatory Remarks?

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