The HiePACS Inria team co-develops linear algebra libraries to solve very large numerical systems on supercomputers. To get good performances whatever the computing machine, these libraries are designed as task-based algorithms and make use of runtime systems such as OpenMP (task), Parsec or StarPU. One main advantage is that with a single algorithm we can deploy executions on different architectures (homogeneous, heterogeneous with GPUS, with few/many cores, different kind of architectures and networks) achieving relatively high performance without requiring a lot of parameter tuning. Three of these libraries will be highlighted within a thirty minutes presentation to which will succeed a one hour demonstration on our PlaFRIM supercomputer: Chameleon (parallel dense linear algebra), PaStiX (parallel sparse direct solver) and Maphys (parallel hybrid solver). We will show how to install each library, how to use it through examples, discuss how to get good performances by tuning some parameters and finally visualize execution traces. The demonstration will put the emphasis on the reproducibility of experiments and performance; we will do so thanks to the GNU Guix distribution.