J. Klepl, A. Šmelko, L. Rozsypal, M. Kruliš:
Abstractions for C++ code optimizations in parallel high-performance applications, in Parallel Computing 121, pp. 103096, 2024
DOI: https://doi.org/10.1016/j.parco.2024.103096
A. Šmelko, M. Kruliš, J. Klepl:
GPU-acceleration of neighborhood-based dimensionality reduction algorithm EmbedSOM, in 16th Workshop on General Purpose Processing Using GPU, pp. 13–18, 2024
ISBN: 979-8-4007-1817-5, DOI: 10.1145/3649411.3649414
A. Šmelko, M. Kratochvíl, E. Barillot, V. Noël:
Maboss for HPC environments: implementations of the continuous time Boolean model simulator for large CPU clusters and GPU accelerators, in BMC bioinformatics 25, 2024
DOI: 10.1186/s12859-024-05815-5
J. Klepl, A. Šmelko, L. Rozsypal, M. Kruliš:
Pure C++ Approach to Optimized Parallel Traversal of Regular Data Structures, in Proceedings of the 15th International Workshop on Programming Models and Applications for Multicores and Manycores, pp. 42–51, 2024
ISBN: 979-8-4007-0599-1, DOI: 10.1145/3649169.3649247
A. Šmelko, M. Kruliš, M. Kratochvíl, J. Klepl, J. Mayer, P. Šimůnek:
Astute Approach to Handling Memory Layouts of Regular Data Structures, in International Conference on Algorithms and Architectures for Parallel Processing, pp. 507–528, 2022
DOI: 10.1007/978-3-031-22677-9_27
A. Šmelko, M. Kratochvíl, M. Kruliš, T. Sieger:
GPU-Accelerated Mahalanobis-Average Hierarchical Clustering Analysis, in Euro-Par 2021: Parallel Processing, pp. 580-595, 2021
ISBN: 978-3-030-85665-6, DOI: 10.1007/978-3-030-85665-6_36