This software is part of the research paper:

• Real-time and post-hoc compression for data from distributed acoustic sensing, Bin Dong, Alex Popescu, Ver ́onica Rodr ́ıguez Tribaldos, Suren Byna, Jonathan Ajo-Franklin, Kesheng Wu, and the Imperial Valley Dark Fiber Team. Submitted on Sept 2021.*

Please see the Copyright and the License at the end of this doc

• Install HDF5 (skip if you already have it)

  Please use 1.10.X (e.g. hdf5-1.10.7 https://www.hdfgroup.org/packages/hdf5-1107-source/). The HDf5 1.12 has issues with plug-in support. Below are some steps to install it

  > tar zxvf hdf5-1.10.7.tar.gz
  > ./autogen.sh
  > ./configure --prefix=$PWD/build 
    # You may need "--enable-parallel CC=mpicc" to enable parallel version
  > make 
  > make install
  > export HDF5_HOME=$PWD/build
  

  If on NERSC machine or machine with HDF5 as module. Just use the pre-compiled HDF5

  > module load cray-hdf5-parallel/1.10.5.2

• Install TurboPFor

  > git clone https://github.com/powturbo/TurboPFor-Integer-Compression.git
  > cd TurboPFor-Integer-Compression
  > make
  > export TurboPFor_HOME=$PWD

> git clone https://github.com/dbinlbl/H5TurboPFor.git
> cd H5TurboPFor
> cmake .
> make
> make install
> source setup.sh   ##setup the path to load the H5TurboPFor

 Note:
 (1) You may want to edit the CMakeLists.txt files for proper installtaion of TurboPFor
 
   set(turbopfor_ROOT_DIR $ENV{TurboPFor_HOME})

 (2)the default installation directory is set as $PWD/build.
  You can adjust it if you want

  set(PLUGIN_INSTALL_PATH "./build" CACHE PATH "Where to install the dynamic HDF5-plugin")

Note: please make sure you have ran "source setup.sh" and then start python/jupyter-notebook with the same terminal to avoid issues like "ValueError: Unknown compression filter number: 62016"

> python3 py-example.py
> h5dump -pH das_example_compressed.h5

HDF5 "das_example_compressed.h5" {
GROUP "/" {
   DATASET "Acoustic" {
      DATATYPE  H5T_STD_I16LE
      DATASPACE  SIMPLE { ( 30000, 21 ) / ( 30000, 21 ) }
      STORAGE_LAYOUT {
         CHUNKED ( 30000, 21 )
         SIZE 668260 (1.885:1 COMPRESSION)
      }
     ... ...
}}}

Please see the H5TurboPFor-Example-Jupyter.ipynb for the example

About how to install Jupytor Notebook: https://jupyter.org/

Error is h5repack: "UD=62016,0,4,0,1,30000,21" v.s. "UD=62016,4,0,1,30000,21" Based on the h5repack doc h5repack. Don't know why there is extra "0" after "62016" to make it work .

> h5repack -f UD=62016,0,4,0,1,30000,21  das_example.h5  das_example_rpk.h5
> h5dump -pH das_example_rpk.h5
HDF5 "das_example_rpk.h5" {
GROUP "/" {
   DATASET "Acoustic" {
      DATATYPE  H5T_STD_I16LE
      DATASPACE  SIMPLE { ( 30000, 21 ) / ( 30000, 21 ) }
      STORAGE_LAYOUT {
         CHUNKED ( 30000, 21 )
         SIZE 668260 (1.885:1 COMPRESSION)
      }
      FILTERS {
         USER_DEFINED_FILTER {
            FILTER_ID 62016
            COMMENT TurboPFor-Integer-Compression: https://github.com/dbinlbl/H5TurboPFor
            PARAMS { 0 1 30000 21 }
         }
      }
      FILLVALUE {
         FILL_TIME H5D_FILL_TIME_IFSET
         VALUE  H5D_FILL_VALUE_DEFAULT
      }
      ALLOCATION_TIME {
         H5D_ALLOC_TIME_INCR
}}}}

Based on the H5TurboPFor_HOME and HDF5_HOME set above

> export HDF5_PLUGIN_PATH=$HDF5_PLUGIN_PATH:$H5TurboPFor_HOME/lib
> export LD_LIBRARY_PATH=$HDF5_PLUGIN_PATH:$HDF5_HOME/lib
> export DYLD_LIBRARY_PATH=$LD_LIBRARY_PATH

The DYLD_LIBRARY_PATH may be needed only on MacOS

The blow is the minimum code to use the H5TurboPFor

   unsigned int filter_flags = H5Z_FLAG_MANDATORY;
   H5Z_filter_t filter_id = 62016;
   hid_t create_dcpl_id = H5Pcreate(H5P_DATASET_CREATE);

   * @param cd_values: the pointer of the parameter 
   * 			cd_values[0]: type of data:  short (0),  int (1)
   *          cd_values[1]: 0/1 pre-processing method: zipzag  
   *          cd_values[2, -]: size of each dimension of a chunk 
   filter_cd_nelmts = 4
   filter_cd_values[0] = 0;
   filter_cd_values[1] = 1;
   filter_cd_values[2] = 100;
   filter_cd_values[3] = 100;

   H5Pset_filter(create_dcpl_id, filter_id, filter_flags, filter_cd_nelmts, filter_cd_values);
   endpoint_ranks = 2;
   filter_chunk_size[0] = 100;
   filter_chunk_size[1] = 100;
   H5Pset_chunk(create_dcpl_id, endpoint_ranks, filter_chunk_size);
   
   did = H5Dcreate(fid, "FNAME", "FILE DISK TYPE", "DATA SPACE", H5P_DEFAULT, create_dcpl_id, H5P_DEFAULT);
   

https://bitbucket.org/dbin_sdm/dassa/src/master/

H5TurboPFor Copyright (c) 2021, The Regents of the University of California, through Lawrence Berkeley National Laboratory (subject to receipt of any required approvals from the U.S. Dept. of Energy). All rights reserved.

If you have questions about your rights to use or distribute this software, please contact Berkeley Lab's Intellectual Property Office at [email protected].

NOTICE. This Software was developed under funding from the U.S. Department of Energy and the U.S. Government consequently retains certain rights. As such, the U.S. Government has been granted for itself and others acting on its behalf a paid-up, nonexclusive, irrevocable, worldwide license in the Software to reproduce, distribute copies to the public, prepare derivative works, and perform publicly and display publicly, and to permit others to do so.

*** License Agreement ***

H5TurboPFor Copyright (c) 2021, The Regents of the University of California, through Lawrence Berkeley National Laboratory (subject to receipt of any required approvals from the U.S. Dept. of Energy). All rights reserved.

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

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