Toward simulation-time data analysis and I/O acceleration on leadership-class systems

The performance mismatch between computing and I/O components of current-generation HPC systems has made I/O the critical bottleneck for scientific applications. It is therefore critical to make data movement as efficient as possible, and, to facilitate simulation-time data analysis and visualizatio...

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Vydáno v:2011 IEEE Symposium on Large Data Analysis and Visualization s. 9 - 14
Hlavní autoři: Vishwanath, V., Hereld, M., Papka, M. E.
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.10.2011
Témata:
Analytical models
Computational modeling
Data analysis
Data models
Data visualization
Fractals
Network topology
ISBN:9781467301565, 1467301566
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Shrnutí:The performance mismatch between computing and I/O components of current-generation HPC systems has made I/O the critical bottleneck for scientific applications. It is therefore critical to make data movement as efficient as possible, and, to facilitate simulation-time data analysis and visualization to reduce the data written to storage. These will be of paramount importance to enabling us to glean novel insights from simulations. We present our work in GLEAN, a flexible framework for data-analysis and I/O acceleration at extreme scale. GLEAN leverages the data semantics of applications, and fully exploits the diverse system topologies and characteristics. We discuss the performance of GLEAN for simulation-time analysis and I/O acceleration with simulations at scale on leadership class systems.
ISBN:9781467301565
1467301566
DOI:10.1109/LDAV.2011.6092178