HDF5

HDF5 is a data model, library, and file format for storing and managing data. It supports an unlimited variety of datatypes, and is designed for flexible and efficient I/O and for high volume and complex data. HDF5 is portable and is extensible, allowing applications to evolve in their use of HDF5. The HDF5 Technology suite includes tools and applications for managing, manipulating, viewing, and analyzing data in the HDF5 format.


References in zbMATH (referenced in 17 articles )

Showing results 1 to 17 of 17.
Sorted by year (citations)

  1. Jens-Kristian Krogager: VoigtFit: A Python package for Voigt profile fitting (2018) arXiv
  2. Benger, Werner; Dobler, Wolfgang: Massive geometric algebra: visions for C++ implementations of geometric algebra to scale into the big data era (2017)
  3. Daniel Johnson, E. A. Huerta, Roland Haas: Python Open Source Waveform Extractor (POWER): An open source, Python package to monitor and post-process numerical relativity simulations (2017) arXiv
  4. Jesus Carrete, Bjorn Vermeersch, Ankita Katre, Ambroise van Roekeghem, Tao Wang, Georg K. H. Madsen, Natalio Mingo: almaBTE: a solver of the space-time dependent Boltzmann transport equation for phonons in structured materials (2017) arXiv
  5. Ruthotto, Lars; Treister, Eran; Haber, Eldad: jInv -- a flexible Julia package for PDE parameter estimation (2017)
  6. Ribés, Alejandro; Lorendeau, Benjamin; Jomier, Julien; Fournier, Yvan: In-situ visualization in computational fluid dynamics using open-source tools: Integration of Catalyst into \itCode_Saturne (2015)
  7. de Buyl, Pierre: The vmf90 program for the numerical resolution of the Vlasov equation for mean-field systems (2014)
  8. Cores, Iván; Rodríguez, Gabriel; Martín, Mará J.; González, Patricia; Osorio, Roberto R.: Improving scalability of application-level checkpoint-recovery by reducing checkpoint sizes (2013) ioport
  9. Wu, Kesheng; Bethel, E.Wes; Gu, Ming; Leinweber, David; Rübel, Oliver: A big data approach to analyzing market volatility (2013)
  10. Flaig, Cyril; Arbenz, Peter: A scalable memory efficient multigrid solver for micro-finite element analyses based on CT images (2011) ioport
  11. Kačeniauskas, Arnas; Kačianauskas, Rimantas; Maknickas, Algirdas; Markauskas, Darius: Computation and visualization of discrete particle systems on gLite-based grid (2011)
  12. De Buyl, Pierre: Numerical resolution of the Vlasov equation for the Hamiltonian mean-field model (2010)
  13. Linxweiler, Jan; Krafczyk, Manfred; Tölke, Jonas: Highly interactive computational steering for coupled 3D flow problems utilizing multiple GPUs (2010)
  14. Piernas-Canovas, Juan; Nieplocha, Jarek: Implementation and evaluation of active storage in modern parallel file systems (2010)
  15. Arbenz, Peter; van Lenthe, G.Harry; Mennel, Uche; Müller, Ralph; Sala, Marzio: A scalable multi-level preconditioner for matrix-free $\mu $-finite element analysis of human bone structures (2008)
  16. Faerman, Marcio; Moore, Reagan; Cui, Yifeng; Hu, Yuanfang; Zhu, Jing; Minster, Bernard; Maechling, Philip: Managing large scale data for earthquake simulations (2007) ioport
  17. Makowski, Marek: Modeling paradigms applied to the analysis of European air quality (2000)