Grid & Cloud Group

Grid & Cloud Computing Group

gridgroup_logo

The GRID & Cloud Computing Group is a part of the Institute of Complex Systems of the University of Applied Sciences of Western Switzerland, Fribourg. This group, created and headed by Professor Pierre Kuonen, is working on topics related to parallel and distributed systems such as Cluster, Grid, Cloud or GPU computing systems. More specifically activities of the group are mainly focusing on the following aspects:

  • Parallel and distributing programing
  • Distributed architectures (Cloud, Grid, Clusters, Sensor networks, …)
  • Middelware for distributed systems (resource management,…)
  • Parallel and Distributed High Performance applications

The objective of the group is to be an excellence center able to provide support to industrial and to collaborate on research activities with other academic centers at national and international level. The GRID & Cloud Computing Group has been a partner of the European CoreGRID network of excellence.

The team

Current members

Name Function Office Phone email
Pierre Kuonen Professor D20.19 +41 26 429 6565 Email
François Kilchoer Professor D20.07 +41 26 429 6583 Email
Frédéric Bapst Professor D20.21 +41 26 429 6578 Email
Richard Baltensperger Professor D30.19 +41 26 429 6972 Email
Jean-François Roche Collaborator C00.14 +41 26 429 6569 Email
Beat Wolf Post Doc C10.08 …. Email

External members

Name Institution
Mehmet Emin Aydin University of the West of England, UK
Marcelo Pasin HE-ARC
Valentin Clément MeteoSwiss

Former members

Name Institution
Laurent Winkler Collaborator
Zhihua Lai Intern, PhD
Tran Que Nguyet Intern, Master
Kevin Cristiano PhD Student
Nicolas Brasey Collaborator
Ye Huang PhD Student
Tuan Anh Nguyen University of Technology, HoChiMinh City,Vietnam
Guilherme Peretti Pezzi Fellow
Augusto Born de Oliveira Santa Catarina Federal University, Brasil
Tiago Scheid Santa Catarina Federal University, Brasil
Ioan Sorin Comsa PhD Student
Jianping Chen PhD Student
Lu Yao PhD student

Projects

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.
TFC is a distributed application development framework, based on POP-Java. It allows developers to develop decentralized applications in which the users can share computing power and data in a secure manner. The connection between the different users of the software is made in a way similar to social networks, allowing users to create communities around certain applications.
DAPLAB aims at facilitating the access for enterprises and universities to emerging technologies in the area of big data and intelligent data analysis by managing an infrastructure composed of cluster of servers dedicated to storage and computation, to which universities and local companies will have access.
With a focus on complex systems, iCoSys approaches the different challenges of DNA analysis with its expertise in various techniques acquired in the different domains of computer science.
VideoProtector is an innovative solution to manage cameras streams in a central place. This centralization offers also the possibility to run incident detection algorithms in a Software-as-a-Service (SaaS) mode.

Tools

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.
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.
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.
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.
ETL is a header only library for C++ that provides vector and matrix classes with support for Expression Templates to perform very efficient operations on them.

All projects here.