CGNS I/O Performance on Parallel File Systems

Hauser, Thomas; Horne, Kyle

doi:10.2514/6.2010-1057

Cited by 2 publications

(2 citation statements)

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“…6,13 In an effort to improve performance and better integrate the parallel extension into the CGNS MLL, new routines were written that access HDF5 directly and take full advantage of the collective I/O support in HDF5 version 1.8-see Hauser and Horne. 9 The parallel extension is meant to be a supplement of the CGNS MLL. A single process should create the layout and structure of the CGNS file.…”

Section: Parallel Cgns Mllmentioning

confidence: 99%

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Recent Updates to the CFD General Notation System (CGNS)

Rumsey

Wedan²,

Hauser

et al. 2012

50th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition

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The CFD General Notation System (CGNS)-a general, portable, and extensible standard for the storage and retrieval of computational fluid dynamics (CFD) analysis data-has been in existence for more than a decade (Version 1.0 was released in May 1998). Both structured and unstructured CFD data are covered by the standard, and CGNS can be easily extended to cover any sort of data imaginable, while retaining backward compatibility with existing CGNS data files and software. Although originally designed for CFD, it is readily extendable to any field of computational analysis. In early 2011, CGNS Version 3.1 was released, which added significant capabilities. This paper describes these recent enhancements and highlights the continued usefulness of the CGNS methodology.

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Section: Parallel Cgns Mllmentioning

confidence: 99%

“…Every so often, referenceable documents concerning CGNS are published as well. [1][2][3][4][5][6][7][8][9] However, the up-to-date on-line documentation is the best way to learn the system and remain current. The main website address for CGNS is http://cgns.org, and all CGNS documentation is accessible via that site.…”

Section: Overview Of Cgnsmentioning

confidence: 99%

Recent Updates to the CFD General Notation System (CGNS)

Rumsey

Wedan²,

Hauser

et al. 2012

50th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition

Self Cite

View full text Add to dashboard Cite

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High Performance Storage for Big Data Analytics and Visualization

Fandango¹,

Rivera

2018

Advances in Data Mining and Database Management

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Scientific Big Data being gathered at exascale needs to be stored, retrieved and manipulated. The storage stack for scientific Big Data includes a file system at the system level for physical organization of the data, and a file format and input/output (I/O) system at the application level for logical organization of the data; both of them of high-performance variety for exascale. The high-performance file system is designed with concurrent access, high-speed transmission and fault tolerance characteristics. High-performance file formats and I/O are designed to allow parallel and distributed applications with easy and fast access to Big Data. These specialized file formats make it easier to store and access Big Data for scientific visualization and predictive analytics. This chapter provides a brief review of the characteristics of high-performance file systems such as Lustre and GPFS, and high-performance file formats such as HDF5, NetCDF, MPI-IO, and HDFS.

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CGNS I/O Performance on Parallel File Systems

Cited by 2 publications

References 0 publications

Recent Updates to the CFD General Notation System (CGNS)

Recent Updates to the CFD General Notation System (CGNS)

High Performance Storage for Big Data Analytics and Visualization

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