/ch_vdif_assembler

a multithreaded, real-time acqusition system for CHIME high-speed data.

Primary LanguageC++

ch_vdif_assembler: a multithreaded, real-time acqusition system for CHIME high-speed data.

A vdif_assembler instance consists of a "stream" of high-speed baseband data (vdif packets), which is transposed and assembled into a contiguous buffer, and handed off to one or more "processor" threads.

The stream can be either a real-time network stream or a saved capture. Examples of processing threads include disk writers, plotters, and real-time transient searches.

Example usage (for a complete list of flags, do ./run-vdif-assembler with no arguments)

./run-vdif-assembler -n \     # -n flag sets input stream to be a real-time network capture
    -d \                     # -d flag saves baseband data to disk (information-preserving)
    -i INTENSITY_DIR \       # -i flag saves downsampled intensity data (e.g. for offline FRB search)
    -w WATERFALL_DIR         # -w flag saves .png waterfall plots

INSTALLATION

  • You'll need the following prerequisites. Boost is no longer needed but you'll need a newish C++ compiler with C++11 support.

    • python
    • numpy
    • cython
    • libpng
    • libhdf5

  • Create a file Makefile.local as described in comments in the Makefile. You can probably start with one of the examples in site/ (or just symlink one of these examples to ./Makefile.local)

  • You should now be able to compile with make all install.

  • If you want to run some unit tests:

./test-timestamp-unwrapper
./test-kernels
./test-downsampled-intensity
./run-vdif-assembler -u

  • To try it out, run the executable ./run-vdif-assembler and follow the instructions!

  • A performance puzzle: the assembly-language-kernel-enabled assembler runs 5 times faster on moose (3.5 GHz Haswell-E, gcc 4.4.7) than on my desktop (2.4 GHz Haswell, gcc 4.8.3)! This seems worth understanding and fixing, but I haven't gotten to the bottom of it yet. In the meantime, if you use moose you should be fine, but you may find poor performance on other machines. For a performance test, do ./run-vdif-assembler -t. This gives ~13 Gbps on moose and 2.5 Gbps on my desktop, where 6.4 Gbps is the minimum needed to keep up with a real-time network capture.

WRITING EXTENSIONS

To integrate C++ code with ch_vdif_assembler, you'll want to define a subclass of the virtual base class vdif_processor. For a lot more detail, see comments in ch_vdif_assembler.hpp or an example C++ class in waterfall_plotter.cpp.

There's also a python interface which will probably never be fast enough for realtime processing, but may be useful for prototyping code using captured data on disk.