* [[recherche:projets|Projets soutenus]]

====== Flexible Approximate MUlti-layer Sparse Transforms (FAµST) ======

{{:recherche:projets:faust.png?100 |}} **IXXI, ENS-Lyon ** : Hakim Hadj-Djilani\\
**Centre Blaise Pascal :** Emmanuel Quémener

The FAµST toolbox provides algorithms and data structures to decompose a given dense matrix into a product of sparse matrices in order to reduce its computational complexity (both for storage and manipulation).  FaµST can be used to :

  * speedup / reduce the memory footprint of iterative algorithms commonly used for solving high dimensional linear inverse problems.
  * learn dictionaries with an intrinsically efficient implementation
  * compute (approximate) fast Fourier transforms on graphs.

A C++ implementation (versions 2.x), including Matlab and Python wrappers, is available under an Inria licence.

More information about FAµST is available on the dedicated website: https://faust.inria.fr

The CBP has provided resources to host virtual machines running Windows systems which are necessary in the process of gitlab continuous integration (for tests execution, generation of packages, etc.).

====== Contribution du CBP ======

The Centre Blaise Pascal provides :
  * support and ressources for deep learning training and optimization
  * expertise in GPU programming