Research activity

Conception d'algorithmes parallèles pour les architectures généralistes (CPU multicoeurs SIMD, DSP, GPU), les systèmes embarqués et les systèmes manycores. Customisation de processeur "softcore", étude des formats de calcul flottant en demi-précision F16 pour le traitement d'images et la vision par ordinateur. optimisation de codes HPC. Etiquetage et Analyse en Composantes Connexes.

3 PhD students (Supervision / Co-supervision)

• HENNEQUIN Arthur : real time tracking for the CERN LHCb experiment, .
• PETRETO Andrea : realtime spatio-temporal processing for spectral camera.
• ROMERA Thomas : .

2 PhD graduated 2019

2009-2019 Publications

• 2019
  • A. Hennequin, I. Masliah, L. Lacassagne : “Designing efficient SIMD algorithms for direct Connected Component Labeling”, WPMVP'19 - 5^th Workshop on Programming Models for SIMD/Vector Processing, Washington, USA, pp. 4:1-4:8, (ACM) (2019)
• 2018
  • O. Haggui, C. Tadonki, L. Lacassagne, F. Sayadi, O. Bouraoui : “Harris corner detection on a NUMA manycore”, Future Generation Computer Systems, vol. 88, pp. 442-452, (Elsevier) (2018)
  • L. Cabaret, L. Lacassagne, D. Etiemble : “Parallel Light Speed Labeling: an efficient connected component algorithm for labeling and analysis on multi-core processors”, Journal of Real-Time Image Processing, vol. 15 (1), pp. 173-196, (Springer Verlag) (2018)
  • A. Hennequin, L. Lacassagne, L. Cabaret, Q. Meunier : “A new Direct Connected Component Labeling and Analysis Algorithms for GPUs”, 2018 Conference on Design and Architectures for Signal and Image Processing (DASIP), Porto, Portugal (2018)
  • A. Petreto, A. Hennequin, Th. Koehler, Th. Romera, Y. Fargeix, B. Gaillard, M. Bouyer, Q. Meunier, L. Lacassagne : “Comparaison de la consommation énergétique et du temps d’exécution d’un algorithme de traitement d’images optimisé sur des architectures SIMD et GPU”, GdR SOC2, Paris, France (2018)
  • A. Petreto, A. Hennequin, Th. Koehler, Th. Romera, Y. Fargeix, B. Gaillard, M. Bouyer, Q. Meunier, L. Lacassagne : “Comparaison de la consommation énergétique et du temps d’exécution d’un algorithme de traitement d’images optimisé sur des architectures SIMD et GPU”, Conférence d’informatique en Parallélisme, Architecture et Système (COMPAS 2018), Toulouse, France (2018)
  • A. Petreto, A. Hennequin, Th. Koehler, Th. Romera, Y. Fargeix, B. Gaillard, M. Bouyer, Q. Meunier, L. Lacassagne : “Energy and Execution Time Comparison of Optical Flow Algorithms on SIMD and GPU Architectures”, Conference on Design and Architectures for Signal and Image Processing (Dasip 2018), Porto, Portugal (2018)
  • N. Rambaux, D. Galayko, G. Guignan, J. Vaubaillon, L. Lacassagne, Ph. Keckhut, A. Levasseur‑Regourd, A. Hauchecorne, M. Birlan, G. Augarde, S. Barnier, S. Ben Kemmoum, A. Bigot, P. Boisse, M. Capderou, A. Chu, F. Colas, F. DESHOURS, Y. Fargeix, A. Hennequin, Th. Koehler, M. Lumbroso, J.‑F. Mariscal, D. Portela‑Moreira, J. Raffard, J.‑L. Rault, Th. Romera, C. Tob, B. Zanda : “METEORIX: a cubesat mission dedicated to the detection of meteors”, COSPAR 2018, 42^nd Assembly, Pasadena, USA (2018)
  • F. Lemaitre, B. Couturier, L. Lacassagne : “Small SIMD Matrices for CERN High Throughput Computing”, WPMVP 2018 Workshop on Programming Models for SIMD/Vector Processing, Vienna, Austria, (ACM Press) (2018)
  • D. Mercadier, P.‑�. Dagand, L. Lacassagne, G. Muller : “Usuba, Optimizing & Trustworthy Bitslicing Compiler”, WPMVP’18 - Workshop on Programming Models for SIMD/Vector Processing, Vienna, Austria (2018)
• 2017
  • F. Lemaitre, B. Couturier, L. Lacassagne : “Cholesky Factorization on SIMD multi-core architectures”, Journal of Systems Architecture, (Elsevier) (2017)
  • M. Gouiffès, A. Romero Mier y Téran, L. Lacassagne : “Color enhanced local binary patterns in covariance matrices descriptors (ELBCM)”, Journal of Visual Communication and Image Representation, vol. 49, pp. 447-458, (Elsevier) (2017)
  • C. CARRASCAL‑MANZANARES, A. Imperiale, G. Rougeron, V. Bergeaud, L. Lacassagne : “A fast implementation of a spectral finite elements method on CPU and GPU applied to ultrasound propagation”, International Conference on Parallel Computing, vol. 32, Parallel Computing is Everywhere, Bologna, Italy, pp. 339-348, (IOS Press), (ISBN: 978-1-61499-843-3) (2017)
  • L. Cabaret, L. Lacassagne, D. Etiemble : “Distanceless Label Propagation: an Efficient Direct Connected Component Labeling Algorithm for GPUs”, IPTA2017 - International Conference on Image Processing Theory, Tools and Applications, Montreal, Canada (2017)
  • C. Tadonki, O. Haggui, L. Lacassagne : “Harris Corner Detection on a NUMA Manycore”, n°E-424 (2017)
• 2016
  • Ah. Ben Abdallah, M. Gouiffès, L. Lacassagne : “A Modular System for Global and Local Abnormal Event Detection and Categorization in Videos”, Machine Vision and Applications, vol. 27 (4), Machine Vision and Applications, pp. 463-481, (Springer Verlag) (2016)
  • L. Lacassagne, L. Cabaret, D. Etiemble, F. Hebbache, A. Petreto : “A new SIMD iterative connected component labeling algorithm”, Principles and Practice of Parallel Programming / WVMVP, Barcelone, Spain (2016)
  • F. Lemaitre, L. Lacassagne : “Batched Cholesky Factorization for tiny matrices”, Design and Architectures for Signal and Image Processing (DASIP), Rennes, France, pp. 1-8 (2016)
• 2015
  • L. Lacassagne, L. Cabaret, D. Etiemble : “Parallel light speed labeling: An efficient connected component labeling algorithm for multi-core processors”, IEEE International Conference on Image Processing (ICIP), Quebec, Canada, pp. 3486-3489, (IEEE) (2015)
• 2009
  • L. Lacassagne, A. Manzanera, J. Denoulet, A. Mérigot : “High performance motion detection: some trends toward new embedded architectures for vision systems”, Journal of Real Time Image Processing, vol. 4 (2), Springer (Ed.), pp. 127-146, (ISBN: 1861-8200) (2009)