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Profil

HELBECQUE Guillaume

Main Referenced Co-authors
BOUVRY, Pascal  (6)
MELAB, Nouredine (6)
GMYS, Jan (5)
CARNEIRO PESSOA, Tiago  (4)
CARNEIRO, Tiago (1)
Main Referenced Keywords
Chapel (6); Productivity-awareness (4); Distributed programming (3); Branch-and-Bound (2); AMD (1);
Main Referenced Disciplines
Computer science (7)

Publications (total 7)

The most downloaded
75 downloads
HELBECQUE, G., GMYS, J., CARNEIRO PESSOA, T., MELAB, N., & BOUVRY, P. (2022). A performance-oriented comparative study of the Chapel high-productivity language to conventional programming environments. In PMAM '22: Proceedings of the Thirteenth International Workshop on Programming Models and Applications for Multicores and Manycores (pp. 21-29). New York, United States: Association for Computing Machinery. doi:10.1145/3528425.3529104 https://hdl.handle.net/10993/55211

The most cited

4 citations (Scopus®)

HELBECQUE, G., GMYS, J., CARNEIRO PESSOA, T., MELAB, N., & BOUVRY, P. (2022). A performance-oriented comparative study of the Chapel high-productivity language to conventional programming environments. In PMAM '22: Proceedings of the Thirteenth International Workshop on Programming Models and Applications for Multicores and Manycores (pp. 21-29). New York, United States: Association for Computing Machinery. doi:10.1145/3528425.3529104 https://hdl.handle.net/10993/55211

The most significant

HELBECQUE, G. (2025). PGAS-based Parallel Branch-and-Bound for Ultra-Scale GPU-powered Supercomputers [Doctoral thesis, Unilu - Université du Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/63730

HELBECQUE, G., CARNEIRO, T., MELAB, N., GMYS, J., & BOUVRY, P. (2024). PGAS Data Structure for Unbalanced Tree-Based Algorithms at Scale. In Computational Science – ICCS 2024 (pp. 103–111). Springer Cham. doi:10.1007/978-3-031-63759-9_13
Peer reviewed

HELBECQUE, G., GMYS, J., MELAB, N., CARNEIRO PESSOA, T., & BOUVRY, P. (19 July 2023). Parallel distributed productivity-aware tree-search using Chapel. Concurrency and Computation: Practice and Experience, 35 (27). doi:10.1002/cpe.7874
Peer Reviewed verified by ORBi


HELBECQUE, G. (2025). PGAS-based Parallel Branch-and-Bound for Ultra-Scale GPU-powered Supercomputers [Doctoral thesis, Unilu - Université du Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/63730

HELBECQUE, G., CARNEIRO, T., MELAB, N., GMYS, J., & BOUVRY, P. (2024). PGAS Data Structure for Unbalanced Tree-Based Algorithms at Scale. In Computational Science – ICCS 2024 (pp. 103–111). Springer Cham. doi:10.1007/978-3-031-63759-9_13
Peer reviewed

HELBECQUE, G., KRISHNASAMY, E., MELAB, N., & BOUVRY, P. (2024). GPU-Accelerated Tree-Search in Chapel Versus CUDA and HIP. In 2024 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW) (pp. 872-879). Institute of Electrical and Electronics Engineers Inc. doi:10.1109/IPDPSW63119.2024.00156
Peer reviewed

HELBECQUE, G., GMYS, J., MELAB, N., CARNEIRO PESSOA, T., & BOUVRY, P. (19 July 2023). Parallel distributed productivity-aware tree-search using Chapel. Concurrency and Computation: Practice and Experience, 35 (27). doi:10.1002/cpe.7874
Peer Reviewed verified by ORBi

HELBECQUE, G., GMYS, J., CARNEIRO PESSOA, T., MELAB, N., & BOUVRY, P. (02 June 2023). Towards a Scalable Load Balancing for Productivity-Aware Tree-Search [Paper presentation]. The 10th Annual Chapel Implementers and Users Workshop.
Peer reviewed

HELBECQUE, G., GMYS, J., MELAB, N., CARNEIRO PESSOA, T., & BOUVRY, P. (03 May 2023). Productivity-aware Parallel Distributed Tree-Search for Exact Optimization [Paper presentation]. International Conference on Optimization and Learning, Malaga, Spain.
Peer reviewed

HELBECQUE, G., GMYS, J., CARNEIRO PESSOA, T., MELAB, N., & BOUVRY, P. (2022). A performance-oriented comparative study of the Chapel high-productivity language to conventional programming environments. In PMAM '22: Proceedings of the Thirteenth International Workshop on Programming Models and Applications for Multicores and Manycores (pp. 21-29). New York, United States: Association for Computing Machinery. doi:10.1145/3528425.3529104
Peer reviewed

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