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., 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 |