Application-level Performance Optimization: A Computer Vision Case Study on STHORM. - Vítor Schwambach; Sébastien Cleyet-Merle; Alain Issard; Stéphane Mancini (ICCS, 2014)

Fast parallel application and multiprocessor design space exploration from sequential code. - Vítor Schwambach; Sébastien Cleyet-Merle; Alain Issard; Stéphane Mancini (CODES+ISSS, 2015)

Image tiling for embedded applications with non-linear constraints. - Vítor Schwambach; Sébastien Cleyet-Merle; Alain Issard; Stéphane Mancini (DASIP, 2015)

Estimating the Potential Speedup of Computer Vision Applications on Embedded Multiprocessors. - Vítor Schwambach; Sébastien Cleyet-Merle; Alain Issard; Stéphane Mancini (CoRR, 2015)

Speeding-up CNN inference through dimensionality reduction. - Lucas Fernández Brillet; Nicolas Leclaire; Stéphane Mancini; Sébastien Cleyet-Merle; Marina Nicolas; Jean-Paul Henriques; Claude Delnondedieu (DASIP, 2019)

Scaling Erlang distribution: going beyond the fully connected mesh. - Adam Lindberg; Sébastien Merle; Peer Stritzinger (Erlang Workshop, 2019)

Tunable CNN Compression Through Dimensionality Reduction. - Lucas Fernández Brillet; Stéphane Mancini; Sébastien Cleyet-Merle; Marina Nicolas (ICIP, 2019)

Scalable and Resilient Network Traffic Engineering Using Erlang-based Path Computation Element. - Sébastien Merle; Juan Pedro Fernández-Palacios; Óscar González de Dios; Lluís Gifre; Ricard Vilalta; Peer Stritzinger (NFV-SDN, 2021)

Compression and Speed-up of Convolutional Neural Networks Through Dimensionality Reduction for Efficient Inference on Embedded Multiprocessor. - Lucas Fernández Brillet; Nicolas Leclaire; Stéphane Mancini; Marina Nicolas; Sébastien Cleyet-Merle; Jean-Paul Henriques; Claude Delnondedieu (J. Signal Process. Syst., 2022)