The Australian Ocean Data Network (AODN) provides a variety of physical, biological, and chemical data sets related to the waters around Australia. This repository of data supports a large amount and variety of research across many disciplines. Researchers at the Integrated Marine Observing System (IMOS, an NCRIS supported facility), provide acoustic data to the AODN. Previously this data has been either in a raw .dat format, which can be read with custom scripts, or as calibrated .wav format which is much more easily accessible with off the shelf software. Unfortunately not all of the data that has been collected by IMOS has been calibrated and converted into .wav format, and thus not all of the archival data is able to be provided via the AODN. Furthermore, whilst the custom script for calibrating and converting the data is freely available, it is not easily accessible, as it is written in MATLAB, which requires a licence to run, and is not easily incorporated into an HPC workflow.
In this project ADACS software developers took the existing custom MATLAB script and re-implemented in as a python library. The new implementation is easily accessible, and is modularised so that it can be incorporated into a larger workflow which might run on an HPC or cloud infrastructure. The pathway for bulk conversion of historical data is now within reach for the IMOS researchers.
Check out some of our other projects.
The HORMONE simulation code makes use of a novel self-gravity solver. ADACS implemented MPI parallelisation into the code, enabling it to scale across multiple compute nodes, facilitating larger and more detailed simulations.
The VASTER pipeline detects short timescale variability in ASKAP data. A new web-based classifier allows users to view, filter, classify, and download observation and candidate data for efficient transient analysis.
The CoCoNuT supernova simulation code has a 6-dimensional radiation solver module for simulating neutrino transport. This method is computationally expensive to run, so ADACS enhanced this module with MPI to run in parallel on supercomputers.