Extending Skel to Support the Development and Optimization of Next Generation I/O Systems
Autor: | Lipeng Wan, Kevin Huck, William F. Godoy, Jeremy Logan, Matthew Wolf, Scott Klasky, Chad Wood, George Ostrouchov, Norbert Podhorszki, Greg Eisenhauer, Erich Lohrmann, Jong Youl Choi |
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Rok vydání: | 2017 |
Předmět: |
Input/output
business.industry Computer science Process (engineering) Data management 020206 networking & telecommunications 02 engineering and technology Troubleshooting computer.software_genre 01 natural sciences Data science System model Data modeling 010104 statistics & probability Analytics Middleware (distributed applications) 0202 electrical engineering electronic engineering information engineering 0101 mathematics business Software engineering computer |
Zdroj: | CLUSTER |
Popis: | As the memory and storage hierarchy get deeper and more complex, it is important to have new benchmarks and evaluation tools that allow us to explore the emerging middleware solutions to use this hierarchy. Skel is a tool aimed at automating and refining this process of studying HPC I/O performance. It works by generating application I/O kernel/benchmarks as determined by a domain-specific model. This paper provides some techniques for extending Skel to address new situations and to answer new research questions. For example, we document use cases as diverse as using Skel to troubleshoot I/O performance issues for remote users, refining an I/O system model, and facilitating the development and testing of a mechanism for runtime monitoring and performance analytics. We also discuss data oriented extensions to Skel to support the study of compression techniques for Exascale scientific data management. |
Databáze: | OpenAIRE |
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