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Number of documents

20

CV HAL de Jan GMYS


Journal articles10 documents

  • Jan Gmys, Tiago Carneiro, Nouredine Melab, El-Ghazali Talbi, Daniel Tuyttens. A comparative study of high-productivity high-performance programming languages for parallel metaheuristics. Swarm and Evolutionary Computation, Elsevier, 2020, 57, ⟨10.1016/j.swevo.2020.100720⟩. ⟨hal-02879767⟩
  • Jan Gmys, Mohand Mezmaz, Nouredine Melab, Daniel Tuyttens. A computationally efficient Branch-and-Bound algorithm for the permutation flow-shop scheduling problem. European Journal of Operational Research, Elsevier, 2020, 284 (3), pp.814-833. ⟨10.1016/j.ejor.2020.01.039⟩. ⟨hal-02421229⟩
  • Nouredine Melab, Jan Gmys, Peter Korošec, Imen Chakroun. Synergy between parallel computing, optimization and simulation. Journal of computational science, Elsevier, 2020, 44, pp.101168. ⟨10.1016/j.jocs.2020.101168⟩. ⟨hal-02919422⟩
  • Guillaume Briffoteaux, Maxime Gobert, Romain Ragonnet, Jan Gmys, Mohand Mezmaz, et al.. Parallel Surrogate-assisted Optimization: Batched Bayesian Neural Network-assisted GA versus q-EGO. Swarm and Evolutionary Computation, Elsevier, 2020, pp.100717. ⟨10.1016/j.swevo.2020.100717⟩. ⟨hal-02767541⟩
  • Tiago Carneiro, Jan Gmys, Nouredine Melab, Daniel Tuyttens. Towards ultra-scale Branch-and-Bound using a high-productivity language. Future Generation Computer Systems, Elsevier, 2020, SI: On The Road to Exascale II: Advances on High Performance Computing and Simulations, 105, pp.196-209. ⟨10.1016/j.future.2019.11.011⟩. ⟨hal-02371238⟩
  • Nouredine Melab, Jan Gmys, Mohand Mezmaz, Daniel Tuyttens. Multi-core versus Many-core Computing for Many-task Branch-and-Bound applied to Big Optimization Problems. Future Generation Computer Systems, Elsevier, 2018, 82, pp.20. ⟨10.1016/j.future.2016.12.039⟩. ⟨hal-01419079⟩
  • Tiago Carneiro Pessoa, Jan Gmys, Francisco Heron de Carvalho Junior, Nouredine Melab, Daniel Tuyttens. GPU-accelerated backtracking using CUDA dynamic parallelism. Concurrency and Computation: Practice and Experience, Wiley, 2018, 30 (9), ⟨10.1002/cpe.4374⟩. ⟨hal-01919514⟩
  • Jan Gmys, Mohand Mezmaz, Nouredine Melab, Daniel Tuyttens. IVM-based parallel branch-and-bound using hierarchical work stealing on multi-GPU systems. Concurrency and Computation: Practice and Experience, Wiley, 2017, 29 (9), ⟨10.1002/cpe.4019⟩. ⟨hal-01419072⟩
  • Jan Gmys, Rudi Leroy, Mohand Mezmaz, Nouredine Melab, Daniel Tuyttens. Work Stealing with Private Integer-Vector-Matrix Data Structure for Multi-core Branch-and-Bound Algorithms. Concurrency and Computation: Practice and Experience, Wiley, 2016, ⟨10.1002/cpe.3771⟩. ⟨hal-01248336⟩
  • Jan Gmys, Mohand Mezmaz, Nouredine Melab, Daniel Tuyttens. A GPU-based Branch-and-Bound algorithm using Integer-Vector-Matrix data structure. Parallel Computing, Elsevier, 2016, Parallel Computing, 59, pp.119-139. ⟨10.1016/j.parco.2016.01.008⟩. ⟨hal-01389471⟩

Conference papers7 documents

  • Maxime Gobert, Jan Gmys, Nouredine Melab, Daniel Tuyttens. Adaptive Space Partitioning for Parallel Bayesian Optimization. HPCS 2020 - The 18th International Conference on High Performance Computing & Simulation, Mar 2021, Barcelona / Virtual, Spain. ⟨hal-03121209⟩
  • Johann Dreo, Arnaud Liefooghe, Sébastien Verel, Marc Schoenauer, Juan Merelo, et al.. Paradiseo: From a Modular Framework for Evolutionary Computation to the Automated Design of Metaheuristics: 22 Years of Paradiseo. GECCO 2021 - Genetic and Evolutionary Computation Conference, ACM Sigevo, Jul 2021, Lille / Virtual, France. ⟨pasteur-03220556⟩
  • Maxime Gobert, Jan Gmys, Nouredine Melab, Daniel Tuyttens. Towards Adaptive Space Partitioning for Large-scale Parallel Bayesian Optimization. OLA'2020 - International Conference on Optimization and Learning, Feb 2020, Cadix, Spain. ⟨hal-02898960⟩
  • Maxime Gobert, Jan Gmys, Jean-François Toubeau, Francois Vallee, Nouredine Melab, et al.. Surrogate-Assisted Optimization for Multi-stage Optimal Scheduling of Virtual Power Plants. PaCOS 2019 - International Workshop on the Synergy of Parallel Computing, Optimization and Simulation (part of HPCS 2019), Jul 2019, Dublin, Ireland. ⟨hal-02178314⟩
  • Tiago Carneiro, Jan Gmys, Nouredine Melab, Francisco Heron de Carvalho Junior, Pedro Pedrosa Rebouças Filho, et al.. Dynamic Configuration of CUDA Runtime Variables for CDP-based Divide-and-Conquer Algorithms. VECPAR 2018 - 13th International Meeting on High Performance Computing for Computational Science, Sep 2018, São Pedro, Brazil. ⟨hal-01919532⟩
  • Tiago Carneiro Pessoa, Jan Gmys, Nouredine Melab, de Carvalho Junior Francisco Heron, Daniel Tuyttens. A GPU-Based Backtracking Algorithm for Permutation Combinatorial Problems. 16th International Conference, ICA3PP 2016, Dec 2016, Granada, Spain. pp.15, ⟨10.1007/978-3-319-49583-5_24⟩. ⟨hal-01419073⟩
  • Jan Gmys, Mohand Mezmaz, N Melab, D Tuyttens. IVM-based Work Stealing for Parallel Branch-and-Bound on GPU. 11th Intl. Conf. on Parallel Processing and Applied Mathematics, Sep 2015, Krakov, Poland. ⟨hal-01248329⟩

Book sections1 document

  • Nouredine Melab, Jan Gmys, Mohand Mezmaz, Daniel Tuyttens. Many-core Branch-and-Bound for GPU accelerators and MIC coprocessors. T. Bartz-Beielstein; B. Filipic; P. Korosec; E-G. Talbi. High-Performance Simulation-Based Optimization, 833, Springer, pp.16, 2019, Studies in Computational Intelligence, ISBN 978-3-030-18763-7. ⟨hal-01924766⟩

Preprints, Working Papers, ...1 document

  • Jan Gmys. Solving large permutation flow-shop scheduling problems on GPU-accelerated supercomputers. 2020. ⟨hal-03079700⟩

Theses1 document

  • Jan Gmys. Heterogeneous cluster computing for many-task exact optimization - Application to permutation problems. Distributed, Parallel, and Cluster Computing [cs.DC]. Université de Mons (UMONS); Université de Lille, 2017. English. ⟨tel-01652000⟩