Tools

The project aims to implement methods for evaluating and optimizing the energy and environmental impact of applications based on artificial intelligence models with a view to creating a new center of expertise in Sustainable AI.
We all have been struggling to use a Linux machine at HEIA-FR because there is no official support for Linux machines... So this page is for you to gain some time if you have questions about different Linux related configurations.
At iCoSys Fribourg, we ave set up a microservice cluster to deploy machine learning models scheduled by Kubernetes, including shared GPU support for deep learning.
COJAC is a two-fold tool for Java. It provides a numerical sniffer that detects anomalies arising in arithmetic operations and an enriching wrapper that automatically converts every float/double data into richer number types. With COJAC you don't have to modify your source code or even recompile. All the work is done at runtime, when your application gets instrumented on-the-fly. Feel free to browse the source code at https://github.com/Cojac.
DLL is a machine learning framework that aims to provide a C++ implementation of neural networks and convolutional neural networks. The implementation provides significant speedups on cpu in comparison to other frameworks such as TensorFlow or Torch. It is then dedicated to the use phase of such deep models where performance on cpu is requested, such as in industry 4.0 applications.