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Gmys Jan


Main Referenced Co-authors
Melab, Nouredine (19)
Tuyttens, Daniel  (19)
Mezmaz, Mohand  (10)
Pessoa, Tiago Carneiro (6)
Gobert, Maxime  (4)
Main Referenced Keywords
Bayesian Optimization (1); Efficient Global Optimization (1); Evolutionary Algorithm (1); Massively Parallel Computing (1); Simulation (1);
Main Referenced Disciplines
Mathematics (19)
Computer science (2)
Electrical & electronics engineering (2)

Publications (total 20)

The most downloaded
22 downloads
Melab, N., Gmys, J., Mezmaz, M., & Tuyttens, D. (16 June 2019). Many-core Branch-and-Bound for GPU accelerators and MIC coprocessors. Studies in Computational Intelligence, 833, 275-291. https://hdl.handle.net/20.500.12907/12367
The most cited
41 citations (Scopus®)
Gmys, J., Mezmaz, M., Melab, N., & Tuyttens, D. (2020). A computationally efficient Branch-and-Bound algorithm for the permutation flow-shop scheduling problem. European Journal of Operational Research. https://hdl.handle.net/20.500.12907/17711

Gmys, J., Pessoa, T. C., Melab, N., Talbi, E.-G., & Tuyttens, D. (2020). A comparative study of high-productivity high-performance programming languages for parallel metaheuristics. Swarm and Evolutionary Computation.
Peer Reviewed verified by ORBi

Briffoteaux, G., Gobert, M., Ragonnet, R., Gmys, J., Mezmaz, M., Melab, N., & Tuyttens, D. (2020). Parallel Surrogate-assisted Optimization: Batched Bayesian Neural Network-assisted GA versus q-EGO. Swarm and Evolutionary Computation.
Peer Reviewed verified by ORBi

Gobert, M., Gmys, J., Melab, N., & Tuyttens, D. (2020). Towards Adaptive Space Partitioning for Large-scale Parallel Bayesian Optimization. Paper presented at International Conference on Optimization and Learning OLA'2020 17-19 February, Cadiz, Spain.

Gmys, J., Pessoa, T. C., Melab, N., Talbi, E.-G., & Tuyttens, D. (2020). Comparison of high-productivity languages for parallel metaheuristics. Paper presented at International Conference on Optimization and Learning OLA'2020 17-19 February, Cadiz, Spain.

Gmys, J., Mezmaz, M., Melab, N., & Tuyttens, D. (2020). A computationally efficient Branch-and-Bound algorithm for the permutation flow-shop scheduling problem. European Journal of Operational Research.
Peer Reviewed verified by ORBi

Pessoa, T. C., Gmys, J., Melab, N., & Tuyttens, D. (15 November 2019). Towards ultra-scale Branch-and-Bound using a high-productivity language. Future Generation Computer Systems, 105, 196-209. doi:10.1016/j.future.2019.11.011
Peer Reviewed verified by ORBi

Gobert, M., Gmys, J., Toubeau, J.-F., Vallée, F., Melab, N., & Tuyttens, D. (2019). Surrogate-Assisted Optimization for Multi-Stage Optimal Scheduling of Virtual Power Plants. Paper presented at International Conference on High Performance Computing & Simulation, Dublin, Ireland.

Melab, N., Gmys, J., Mezmaz, M., & Tuyttens, D. (16 June 2019). Many-core Branch-and-Bound for GPU accelerators and MIC coprocessors. Studies in Computational Intelligence, 833, 275-291.
Peer reviewed

Pessoa, T. C., Gmys, J., Melab, N., de Carvalho Junior, F. H., Pedrosa Rebouças Filho, P., & Tuyttens, D. (01 June 2019). Dynamic Configuration of CUDA Runtime Variables for CDP-based Divide-and-Conquer Algorithms. Lecture Notes in Computer Science, 11333, 16-30.
Peer reviewed

Gmys, J. (2018). Optimal Solving of Permutation-based Optimization Problems on Heterogeneous CPU/GPU Clusters. Paper presented at International Conference on High Performance Computing & Simulation, Orléans, France.

Filipic, B., Depolli, M., Zupancic, J., Gmys, J., Gobert, M., Melab, N., & Tuyttens, D. (2018). ECG simulator tuning: A parallel multiobjective optimization approach. Paper presented at OLA International Workshop on Optimization and Learning: Challenges and Applications, Alicante, Spain.

Gmys, J., Mezmaz, M., Melab, N., & Tuyttens, D. (2018). Exactly solving permutation-based optimization problems on heterogeneous CPU/GPU clusters. Paper presented at OLA International Workshop on Optimization and Learning: Challenges and Applications, Alicante, Spain.

Pessoa, T. C., Gmys, J., de Carvalho Junior, F. H., Melab, N., & Tuyttens, D. (2017). GPU-accelerated backtracking using CUDA Dynamic Parallelism. Concurrency and Computation: Practice and Experience, 1-19. doi:10.1002/cpe.4374
Peer Reviewed verified by ORBi

Melab, N., Gmys, J., Mezmaz, M., & Tuyttens, D. (03 January 2017). Multi-core versus many-core computing for many-task Branch-and-Bound applied to big optimization problems. Future Generation Computer Systems, 82, 472-481.
Peer Reviewed verified by ORBi

Pessoa, T. C., Gmys, J., Melab, N., de Carvalho Junior, F. H., & Tuyttens, D. (15 December 2016). A GPU-based Backtracking Algorithm for Permutation Combinatorial Problems. Lecture Notes in Computer Science, 10048, 310-324.
Peer reviewed

Gmys, J., Mezmaz, M., Melab, N., & Tuyttens, D. (10 May 2016). IVM-Based parallel branch-and-bound using hierarchical work stealing on multi-GPU systems. Concurrency and Computation: Practice and Experience, 29 (9). doi:10.1002/cpe.4019
Peer Reviewed verified by ORBi

Gmys, J., Mezmaz, M., Melab, N., & Tuyttens, D. (27 January 2016). A GPU-based Branch-and Bound algorithm using Integer-Vector-Matrix data structure. Parallel Computing, 59, 119-139. doi:10.1016/j.parco.2016.01.008
Peer Reviewed verified by ORBi

Gmys, J., Leroy, R., Mezmaz, M., Melab, N., & Tuyttens, D. (21 January 2016). Work stealing with private integer-vector-matrix data structure for multi-core branch-and-bound algorithms. Concurrency and Computation: Practice and Experience, 28 (18), 4463-4484. doi:10.1002/cpe.3771
Peer Reviewed verified by ORBi

Gmys, J., Mezmaz, M., Melab, N., & Tuyttens, D. (20 January 2016). IVM-based Work Stealing for Parallel Branch-and-Bound on GPU. Lecture Notes in Computer Science, 9573, 548-558.
Peer reviewed

Gmys, J., Mezmaz, M., Melab, N., & Tuyttens, D. (2015). Towards a GPU-based branch-and-bound algorithm using an integer-vector-matrix data structure. Paper presented at ORBEL 29 - Belgian Conference on Operational Research, Antwerp, Belgium.

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