Associate professor

Department of Distributed and Dependable Systems
Faculty of Mathematics and Physics
Charles University

Malostranské náměstí 25
118 00 Praha 1
Czech Republic

E-mail: krulis@d3s.mff.cuni.cz
Phone: +420 951 554 193

Teaching

Software Projects

Publications

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
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
D. Bednárek, M. Kruliš, P. Malý, J. Yaghob, F. Zavoral, J. Pokorný:
‪Combining Distributed Computing and Massively Parallel Devices to Accelerate Stream Data Processing‬, in DBKDA, 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