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
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
J. Pacovský, P. Hnětynka, M. Kruliš:
Generalization of Machine-Learning Adaptation in Ensemble-Based Self-adaptive Systems, in Proceedings of ECSA 2022 Tracks and Workshops, pp. 386-401, 2023
DOI: 10.1007/978-3-031-36889-9_26
T. Bureš, P. Hnětynka, M. Kruliš, F. Plášil, D. Khalyeyev, S. Hahner, S. Seifermann, M. Walter, R. Heinrich:
Generating adaptation rule-specific neural network, in International Journal on Software Tools for Technology Transfer 25, pp. 733–746, 2023
DOI: 10.1007/s10009-023-00725-y
M. Abdullah, M. Töpfer, T. Bureš, P. Hnětynka, M. Kruliš, F. Plášil:
Introducing Estimators—Abstraction for Easy ML Employment in Self-adaptive Architectures, in Proceedings of ECSA 2022 Tracks and Workshops, pp. 370-385, 2023
DOI: 10.1007/978-3-031-36889-9_25
M. Töpfer, M. Abdullah, T. Bureš, P. Hnětynka, M. Kruliš:
Machine-learning abstractions for component-based self-optimizing systems, in International Journal on Software Tools for Technology Transfer 25, pp. 717–731, 2023
DOI: 10.1007/s10009-023-00726-x
P. Hnětynka, M. Kruliš, M. Töpfer, T. Bureš:
Modeling Machine Learning Concerns in Collective Adaptive Systems:, in Proceedings of the 11th International Conference on Model-Based Software and Systems Engineering, Lisbon, Portugal, pp. 55-62, 2023
ISBN: 978-989-758-633-0, DOI: 10.5220/0011693300003402
M. Töpfer, F. Plášil, T. Bureš, P. Hnětynka, M. Kruliš, D. Weyns:
Online ML Self-adaptation in Face of Traps, accepted for publication in Proceedings of ACSOS 2023,Toronto, Canada
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
T. Bureš, P. Hnětynka, M. Kruliš, F. Plášil, D. Khalyeyev, S. Hahner, S. Seifermann, M. Walter, R. Heinrich:
Attuning Adaptation Rules via a Rule-Specific Neural Network, in Proceedings of ISOLA 2022, Rhodes, Greece, pp. 215-230, 2022
DOI: 10.1007/978-3-031-19759-8_14
M. Töpfer, M. Abdullah, T. Bureš, P. Hnětynka, M. Kruliš:
Ensemble-Based Modeling Abstractions for Modern Self-optimizing Systems, in Proceedings of ISOLA 2022, Rhodes, Greece, pp. 318-334, 2022
DOI: 10.1007/978-3-031-19759-8_20
M. Töpfer, M. Abdullah, M. Kruliš, T. Bureš, P. Hnětynka:
ML-DEECo: a Machine-Learning-Enabled Framework for Self-organizing Components, in Proceedings of ACSOS 2022, Virtual event, 2022
DOI: 10.1109/ACSOSC56246.2022.00033
M. Kruliš, T. Bureš, P. Hnětynka:
Simdex: a simulator of a real self-adaptive job-dispatching system backend, in Proceedings of the 17th Symposium on Software Engineering for Adaptive and Self-Managing Systems, pp. 167–173, 2022
ISBN: 978-1-4503-9305-8, DOI: 10.1145/3524844.3528078
T. Bureš, P. Hnětynka, M. Kruliš, J. Pacovský:
Towards Model-driven Fuzzification of Adaptive Systems Specification:, in Proceedings of the 10th International Conference on Model-Driven Engineering and Software Development, pp. 336-343, 2022
ISBN: 978-989-758-550-0, DOI: 10.5220/0010910800003119
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
D. Bednárek, M. Kruliš, J. Yaghob:
Letting future programmers experience performance-related tasks, in Journal of Parallel and Distributed Computing 155, pp. 74-86, 2021
DOI: 10.1016/j.jpdc.2021.04.014
M. Kruliš, M. Kratochvíl:
Detailed Analysis and Optimization of CUDA K-means Algorithm, in 49th International Conference on Parallel Processing - ICPP, pp. 1–11, 2020
ISBN: 978-1-4503-8816-0, DOI: 10.1145/3404397.3404426
D. Honzátko, M. Kruliš:
Accelerating block-matching and 3D filtering method for image denoising on GPUs, in Journal of Real-Time Image Processing 16(6), pp. 2273-2287, 2019
DOI: 10.1007/s11554-017-0737-9
E. Buzek, M. Kruliš:
An Entertaining Approach to Parallel Programming Education, in 2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), pp. 340-346, 2018
DOI: 10.1109/IPDPSW.2018.00065
D. Bednárek, M. Kruliš, J. Yaghob, F. Zavoral:
Player Performance Evaluation in Team-Based First-Person Shooter eSport, in Data Management Technologies and Applications, pp. 154-175, 2018
ISBN: 978-3-319-94809-6, DOI: 10.1007/978-3-319-94809-6_8
D. Bednárek, M. Kruliš, J. Yaghob, F. Zavoral:
‪Data preprocessing of esport game records‬, in DATA, 2017
M. Kruliš, H. Osipyan, S. Marchand-Maillet:
‪Employing GPU architectures for permutation-based indexing‬, in Multimedia Tools and Applications 76(6), pp. 11859-11887, 2017
D. Bednárek, M. Brabec, M. Kruliš:
Improving Matrix-Based Dynamic Programming on Massively Parallel Accelerators, in Information Systems 64, pp. 175-193, 2017
DOI: 10.1016/j.is.2016.06.001
I. Zelinka, M. Kruliš, M. Běhálek, T. Luu, J. Pokorný:
On Interdisciplinary Intersection of Unconventional Algorithms and Big Data Processing in Real World Problems: A Real World Example Based on Ho Chi Minh City Traffic, in Handbook of Research on Holistic Optimization Techniques in the Hospitality, Tourism, and Travel Industry, pp. 326-347, 2017
ISBN: 978-1-5225-1054-3
D. Bednárek, M. Kruliš, J. Yaghob, F. Zavoral:
‪Creating Distributed Execution Plans with BobolangNG‬, in International Conference on Algorithms and Architectures for Parallel Processing, 2016
M. Kruliš, J. Lokoč, T. Skopal:
Efficient extraction of clustering-based feature signatures using GPU architectures, in Multimedia Tools and Applications 75(13), pp. 8071-8103, 2016
DOI: 10.1007/s11042-015-2726-y
H. Osipyan, M. Kruliš, S. Marchand-Maillet:
A Survey of CUDA-based Multidimensional Scaling on GPU Architecture, in 2015 Imperial College Computing Student Workshop (ICCSW 2015), pp. 37–45, 2015
ISBN: 978-3-95977-000-2, DOI: 10.4230/OASIcs.ICCSW.2015.37
J. Pokorný, P. Škoda, I. Zelinka, D. Bednárek, F. Zavoral, M. Kruliš, P. Šaloun:
Big Data Movement: A Challenge in Data Processing, in , 2015
P. Galuščáková, M. Kruliš, J. Lokoč, D. Novák, P. Pecina:
‪CUNI at TRECVID 2015 Video Hyperlinking Task‬, in , 2015
M. Kruliš, D. Bednárek, M. Brabec:
Improving Parallel Processing of Matrix-Based Similarity Measures on Modern GPUs, in Similarity Search and Applications, 2015
Z. Falt, M. Kruliš, D. Bednárek, J. Yaghob, F. Zavoral:
Locality Aware Task Scheduling in Parallel Data Stream Processing, in Intelligent Distributed Computing VIII, pp. 331-342, 2015
ISBN: 978-3-319-10422-5, DOI: 10.1007/978-3-319-10422-5_35
M. Kruliš, H. Osipyan, S. Marchand-Maillet:
Permutation based indexing for high dimensional data on GPU architectures, in 2015 13th International Workshop on Content-Based Multimedia Indexing (CBMI), pp. 1-6, 2015
DOI: 10.1109/CBMI.2015.7153619
Z. Falt, M. Kruliš, D. Bednárek, J. Yaghob, F. Zavoral:
‪Towards Efficient Locality Aware Parallel Data Stream Processing, in Journal of Unversal Computer Science, pp. 816-841, 2015
M. Kruliš, D. Bednárek, Z. Falt, J. Yaghob, F. Zavoral:
Towards Semi-automated Parallelization of Data Stream Processing, in 9th International Symposium on Intelligent Distributed Computing (IDC), 2015
Z. Falt, D. Bednárek, M. Kruliš, J. Yaghob, F. Zavoral:
Bobolang: a language for parallel streaming applications, in Proceedings of the 23rd international symposium on High-performance parallel and distributed computing, pp. 311–314, 2014
ISBN: 978-1-4503-2749-7, DOI: 10.1145/2600212.2600711
J. Yaghob, D. Bednárek, M. Kruliš, F. Zavoral:
Column-Oriented Data Store for Astrophysical Data, in 2014 25th International Workshop on Database and Expert Systems Applications, pp. 258-262, 2014
DOI: 10.1109/DEXA.2014.60
M. Kruliš, D. Bednárek, J. Yaghob, F. Zavoral:
Employing Similarity Methods for Stellar Spectra Classification in Astroinformatics, in Similarity Search and Applications, 2014
M. Kruliš, S. Kirchhoff, J. Yaghob:
Perils of Combining Parallel Distance Computations with Metric and Ptolemaic Indexing in kNN Queries, in Similarity Search and Applications, pp. 127-138, 2014
ISBN: 978-3-319-11988-5, DOI: 10.1007/978-3-319-11988-5_12
M. Kruliš, J. Lokoč, T. Skopal:
Efficient Extraction of Feature Signatures Using Multi-GPU Architecture, in Advances in Multimedia Modeling, pp. 446-456, 2013
ISBN: 978-3-642-35728-2, DOI: 10.1007/978-3-642-35728-2_43
J. Galgonek, M. Kruliš, D. Hoksza:
On the Parallelization of the SProt Measure and the TM-Score Algorithm, in Euro-Par 2012: Parallel Processing Workshops, pp. 238-247, 2013
ISBN: 978-3-642-36949-0, DOI: 10.1007/978-3-642-36949-0_27
M. Kruliš, T. Skopal, J. Lokoč, C. Beecks:
Combining CPU and GPU architectures for fast similarity search, in Distributed and Parallel Databases 30(3), pp. 179-207, 2012
DOI: 10.1007/s10619-012-7092-4
M. Kruliš, Z. Falt, D. Bednárek, J. Yaghob:
‪Task scheduling in hybrid CPU-GPU systems‬, in ITAT, 2012
M. Kruliš, J. Lokoč, C. Beecks, T. Skopal, T. Seidl:
Processing the signature quadratic form distance on many-core GPU architectures, in Proceedings of the 20th ACM international conference on Information and knowledge management, pp. 2373–2376, 2011
ISBN: 978-1-4503-0717-8, DOI: 10.1145/2063576.2063970