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  1. HDF5 Performance

    HDF Knowledge BaseNov 29, 2017
  2. P4091-0713_2.pdf

    framework identified tunable parameters that substantially improved write performance over default system settings. We consistently demonstrate I/O write speedups between 2x and 50x for test configura tions. General Terms Parallel I/O, AutoTuning, Performance Optimization, Par allel file systems 2. INTRODUCTION Parallel I
  3. howison_hdf5_lustre_iasds2010.pdf

    the performance of the HDF5 and MPIIO libraries for the Lustre parallel file system. We selected three different HPC applications to represent the diverse range of I/O requirements, and measured their performance on three different systems to demonstrate the robustness of our optimizations across different file system
  4. howison_hdf5_lustre_iasds2010.pdf

    the performance of the HDF5 and MPIIO libraries for the Lustre parallel file system. We selected three different HPC applications to represent the diverse range of I/O requirements, and measured their performance on three different systems to demonstrate the robustness of our optimizations across different file system
  5. parallelhdf5hints.pdf

    doing IO defined as MPIIO standard; contrary to cesses must participate in doing IO. MPIIO can do IO performance by using MPIFILESETVIEW IO. how examples with 4 … performances for the parallel HDF5 application according to the table. In this document, we will only focus on the performance hint on how to wisely use parallel HDF5
  6. PerfofH5Gget_info_by_idx.pdf

    Improving the performance of H5Ggetinfobyidx and H5Lgetinfobyidx 17 November 2008 If you find that the function H5Ggetinfobyidx or H5Lgetinfobyidx is slow for the new format file in the release 1.8 of the library, you may want to adjust the metadata cache size to improve the performance. The degree of the performance
    HDF Knowledge Base / … / HDF5 PerformanceAug 14, 2017
  7. Memory not released after call to H5Fclose

    . Solution It is hard to answer this because there is a lot going on here. Here are some thoughts: Performance is probably going to be terrible. Variablelength data … . than using VL datatypes. So, to sum up some obvious potential performance improvements: Use the latest file format. Try not opening and closing datasets. Try out
    HDF Knowledge BaseJul 18, 2019
  8. Why are my files sizes different, if I open an HDF5 file more than once rather than writing the data out in one call?

    on the file to increase (reducing performance), because the library cannot cache as much metadata in memory. Performancewise, it would be better to hold the file open as long as possible and not to adjust the block size, but users will have to decide whether file size or I/O performance is their overall goal. faq hdf5 kbarticle
    HDF Knowledge BaseJun 29, 2017
  9. What happens if a process crashes when writing data in parallel?

    performance. With Parallel HDF5 objects are created collectively, and once created you can write to a dataset collectively or independently. As with the serial version of HDF5, if the metadata has not been written to the file at the time of the crash, then that metadata can be lost. Typically, for best performance, one process
    HDF Knowledge BaseApr 18, 2018
  10. Direct Chunk Read and Write Questions

    The Direct Chunk Read and Write APIs are for users with specialized data processing pipelines who do things like compress their data in hardware or something else highly unusual. They were moved to the main library so that they would work with VOL and also for performance reasons. Anyone who is not an obvious power
    HDF Knowledge BaseJun 17, 2020