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2017 IEEE International Conference on Cluster Computing (CLUSTER) (2017)
Honolulu, Hawaii, United States
Sept. 5, 2017 to Sept. 8, 2017
ISSN: 2168-9253
ISBN: 978-1-5386-2326-8
pp: 563-571
ABSTRACT
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.
INDEX TERMS
Tools, Benchmark testing, Generators, Computational modeling, Hardware, Bandwidth, Data models
CITATION

J. Logan et al., "Extending Skel to Support the Development and Optimization of Next Generation I/O Systems," 2017 IEEE International Conference on Cluster Computing (CLUSTER), Honolulu, Hawaii, United States, 2017, pp. 563-571.
doi:10.1109/CLUSTER.2017.30
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