by Jon Wright, 2021.

If you are here to read your data you probably want hdf5plugin or bitshuffle instead.

These are research / experimental codes to see if we can read and reduce data from ID11-ESRF more quickly. You should be seeing about 1 GB/s per core already using the standard methods above.

Wishlish

This is not yet ready for general use, but the gpu kernels seem to run. The interests are:

• getting data decompressed directly inside a GPU
• reading an ROI without decompressing a full image (for CPU)
• learning about what is happening when reading compressed data

To build:

  git clone https://github.com/jonwright/bslz4decoders
  # compile some C extensions for CPU work:
  cd bslz4decoders/ccodes
  # python codegen.py              # if your numpy is different 
  python setup.py build_ext --inplace
  cd ../..
  python -m pip install -e .

To see it do something:

   cd bslz4decoders/test
   python make_testcases.py
   python bench_read.py      # single core serial cpu 
   python testcases.py       # gpu test cases

To see how long it takes to read some frame:

nvprof --openacc-profiling off                       \
    python -m bslz4decoders.lz4dc_cuda               \
        eiger_0000.h5 /entry_0000/measurement/data 0