Jan Gmys
Orcid: 0000-0001-9635-4396
According to our database1,
Jan Gmys
authored at least 28 papers
between 2015 and 2024.
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Bibliography
2024
Observations in applying Bayesian versus evolutionary approaches and their hybrids in parallel time-constrained optimization.
Eng. Appl. Artif. Intell., 2024
Proceedings of the Computational Science - ICCS 2024, 2024
2023
Concurr. Comput. Pract. Exp., 2023
2022
Exactly Solving Hard Permutation Flowshop Scheduling Problems on Peta-Scale GPU-Accelerated Supercomputers.
INFORMS J. Comput., 2022
Batch Acquisition for Parallel Bayesian Optimization - Application to Hydro-Energy Storage Systems Scheduling.
Algorithms, 2022
Proceedings of the Fifteenth International Symposium on Combinatorial Search, 2022
A performance-oriented comparative study of the Chapel high-productivity language to conventional programming environments.
Proceedings of the PMAM@PPoPP 2022: Proceedings of the Thirteenth International Workshop on Programming Models and Applications for Multicores and Manycores, Virtual Event / Seoul, Republic of Korea, April 2, 2022
Parallel Bayesian Optimization for Optimal Scheduling of Underground Pumped Hydro-Energy Storage Systems.
Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2022
Proceedings of the Workshop Proceedings of the 51st International Conference on Parallel Processing, 2022
2021
Paradiseo: from a modular framework for evolutionary computation to the automated design of metaheuristics: 22 years of Paradiseo.
Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021
2020
Proceedings of the High-Performance Simulation-Based Optimization, 2020
A comparative study of high-productivity high-performance programming languages for parallel metaheuristics.
Swarm Evol. Comput., 2020
Parallel surrogate-assisted optimization: Batched Bayesian Neural Network-assisted GA versus q-EGO.
Swarm Evol. Comput., 2020
J. Comput. Sci., 2020
Future Gener. Comput. Syst., 2020
A computationally efficient Branch-and-Bound algorithm for the permutation flow-shop scheduling problem.
Eur. J. Oper. Res., 2020
Solving large permutation flow-shop scheduling problems on GPU-accelerated supercomputers.
CoRR, 2020
2019
Surrogate-Assisted Optimization for Multi-stage Optimal Scheduling of Virtual Power Plants.
Proceedings of the 17th International Conference on High Performance Computing & Simulation, 2019
2018
Multi-core <i>versus</i> many-core computing for many-task Branch-and-Bound applied to big optimization problems.
Future Gener. Comput. Syst., 2018
Concurr. Comput. Pract. Exp., 2018
Dynamic Configuration of CUDA Runtime Variables for CDP-Based Divide-and-Conquer Algorithms.
Proceedings of the High Performance Computing for Computational Science - VECPAR 2018, 2018
Optimal Solving of Permutation-based Optimization Problems on Heterogeneous CPU/GPU Clusters.
Proceedings of the 2018 International Conference on High Performance Computing & Simulation, 2018
2017
Heterogeneous cluster computing for many-task exact optimization - Application to permutation problems. (Optimisation massivement multi-tâche sur grappes de calcul hétérogènes - Application aux problèmes de permutation).
PhD thesis, 2017
IVM-based parallel branch-and-bound using hierarchical work stealing on multi-GPU systems.
Concurr. Comput. Pract. Exp., 2017
2016
Parallel Comput., 2016
Work stealing with private integer-vector-matrix data structure for multi-core branch-and-bound algorithms.
Concurr. Comput. Pract. Exp., 2016
Proceedings of the Algorithms and Architectures for Parallel Processing, 2016
2015
Proceedings of the Parallel Processing and Applied Mathematics, 2015