Parallel Computing With High Performance Computing Clusters (HPCs) By Jeremy Cathey.
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Transcript of Parallel Computing With High Performance Computing Clusters (HPCs) By Jeremy Cathey.
![Page 1: Parallel Computing With High Performance Computing Clusters (HPCs) By Jeremy Cathey.](https://reader036.fdocuments.in/reader036/viewer/2022081515/56649f565503460f94c7b04f/html5/thumbnails/1.jpg)
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Parallel Computing With High Performance
Computing Clusters (HPCs)
By Jeremy Cathey
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Super Computing
• Began as early as late 1950’s
• Compute large mathematical calculations
• Large scale task management
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Advantages of Super Computing
• Power
• Configuration
• Administration
• Cost
• Scalability
• Diversity
Disadvantages of Super Computing
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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
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Implementations of Alternatives
• Shared Processors (Multiple Processors)
• Shared Memory Pools
• Messaging Systems
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Advantages of Parallel Computing• Cost
• Scalability
• Diversity
• Power
• Configuration
• Administration
Disadvantages of Parallel Computing
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Parallelization Techniques
• Manual
- Parallelization implemented by the
programmer at creation of the program
• Automatic
- Parallelization implemented on the fly by
the operating system
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Advantages of Manual Parallelization
• Specific Customization
• More Effective Parallelization
Disadvantages of Manual Parallelization
• Difficult to Implement
• Not Very Portable
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Advantages of Automatic Parallelization
• Easier to Implement
• Portable Applications
Disadvantages of Automatic Parallelization
• Less Effective Parallelization
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• 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
Project Goals
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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
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Operating System Choice
• Windows Vs. Linux
• Live vs. Install
• Community Support
• Creation vs. Customization
• HARDWARE SUPPORT!!!!!!!!
Bill!!!!
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Implementation
• Dr. Salazar: Professor of Chemistry
• Use cluster to reduce time for sophisticated mathematical computation
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Simulation Details
• 2.6 GHz Computer - 2GB RAM
• 1.2 GHz Computer - 256MB RAM
• 5 Parallel 1.2GHz Computers – 1.28GB RAM
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Computer Simulation Results
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Number of Atoms
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Group 21.2GHz
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Computer Simulation Results
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Number of Atoms
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Group 2
2.6GHz
1.2GHz
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Parallel
Computer Simulation Results
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Number of Atoms
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Group 3
1.2GHz
2.6GHz
Parallel
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Hurdles
• HARDWARE DETECTION!!!!!!
• HARDWARE DETECTION!!!!!!
• HARDWARE DETECTION!!!!!!
Did I Mention:
• HARDWARE DETECTION!!!!!!
• HARDWARE DETECTION!!!!!!
• HARDWARE DETECTION!!!!!!
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Improvements
• Redesign Operating System Kernel For More Advanced HARDWARE DETECTION
• Try Simulations on More Advanced Computers
• Create Custom Installer for Distribution
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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
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Questions? Comments? Derogatory Remarks?