Compute Web App (or CWA) is a web application designed to schedule and run data intensive computation processes.

This work has been done to the destination of SoQut Imaging company (2017-2021, official papers) and developed during my spare-time. This project is now open source. So feel free to visit and contribute to the project here.

Its main dreamed features:

  • Fast and easy to deploy,
  • Secured process parameters, data and results transfer,
  • Simple RESTfull API designed to:
    • upload data,
    • control and monitor processes and
    • retrieve results,
  • Simple and efficient web interface provided,
  • Designed to run processes in parallel,
  • Adapted to dedicated servers.
CWA in a Cloud environment

Prepare processes by interfacing them with CWA, develop a simple client application for uploading data and retrieve results and that’s it !

Data and results required to be kept in door? Great, just run it on a local HPC as an « on premise » solution.

CWA in an « on premise » environment

Use case examples

Computational Electromagnetics

Running heavy algorithms like MEEP FDTD to simulate electromagnetics structure may be time and ressource consuming. Using CWA lets one optimize time and efficiency for large simulations campaigns. Send simulations parameters, run them and retrieve results.

2D waveguide FDTD EM fields simulation (reference)

Quantitative Magnetic Resonance Imaging

Quantitative Magnetic Resonance Imaging (MRI, qMRI, Imagerie Quantitative par Résonance Magnétique, IRM) involves processing DICOM files. These files are not designed for data intensive and parallel computation. Using CWA, one can overcome this limitation and, paired with a well chosen PACS (Picture, Archiving and Communication System) software, get a complete data intensive computation software suite « on premise » or in the Cloud.

Quantitative MRI of articular cartilage, T and T2 maps (reference)

Artificial Intelligence Model Training

Training an AI model may be time and ressource consuming. One can chose a adequate HPC, deploy CWA on it to send data, control and monitor processes designed with  KerasPyTorch or TensorFlow. Send training data with consistent parameters, run model training, retrieve resulting model and it’s done.

From one brain scan, more information for medical artificial intelligence, segmentation example (reference)

For more details: request information