Masaryk University

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    2024

    1. PROCHÁZKA, David, Terézia SLANINÁKOVÁ, Jaroslav OĽHA, Adrián ROŠINEC, Katarína GREŠOVÁ, Miriama JÁNOŠOVÁ, Jakub ČILLÍK, Jana PORUBSKÁ, Radka SVOBODOVÁ, Vlastislav DOHNAL and Matej ANTOL. AlphaFind: Discover structure similarity across the entire known proteome. bioRxiv, 2024.

    2023

    1. SLANINÁKOVÁ, Terézia, Matej ANTOL, Jaroslav OĽHA, Vlastislav DOHNAL, Susana LADRA and Miguel A. MARTÍNEZ-PRIETO. Reproducible experiments with Learned Metric Index Framework. Information systems. Elsevier, vol. 118, No 1, p. 102255-102270. ISSN 0306-4379. doi:10.1016/j.is.2023.102255. 2023.
    2. SLANINÁKOVÁ, Terézia, David PROCHÁZKA, Matej ANTOL, Jaroslav OĽHA and Vlastislav DOHNAL. SISAP 2023 Indexing Challenge – Learned Metric Index. In Pedreira, O., Estivill-Castro, V. Similarity Search and Applications. SISAP 2023. Lecture Notes in Computer Science, vol 14289. Cham: Springer. p. 282-290. ISBN 978-3-031-46993-0. doi:10.1007/978-3-031-46994-7_24. 2023.
    3. STŘELÁK, David, David MYŠKA, Filip PETROVIČ, Jan POLÁK, Jaroslav OĽHA and Jiří FILIPOVIČ. Umpalumpa: a framework for efficient execution of complex image processing workloads on heterogeneous nodes. Computing. Springer, vol. 105, No 11, p. 2389-2417. ISSN 0010-485X. doi:10.1007/s00607-023-01190-w. 2023.

    2022

    1. OĽHA, Jaroslav, Terézia SLANINÁKOVÁ, Martin GENDIAR, Matej ANTOL and Vlastislav DOHNAL. Learned Indexing in Proteins: Extended Work on Substituting Complex Distance Calculations with Embedding and Clustering Techniques. arXiv. doi:10.48550/ARXIV.2208.08910. 2022.
    2. OĽHA, Jaroslav, Terézia SLANINÁKOVÁ, Martin GENDIAR, Matej ANTOL and Vlastislav DOHNAL. Learned Indexing in Proteins: Substituting Complex Distance Calculations with Embedding and Clustering Techniques. In Tomáš Skopal, Fabrizio Falchi, Jakub Lokoč, Maria Luisa Sapino, Ilaria Bartolini, Marco Patella. Similarity Search and Applications, 15th International Conference, SISAP 2022, Bologna, Italy, October 5–7, 2022, Proceedings. 1st ed. Cham: Springer Cham. p. 274-282. ISBN 978-3-031-17848-1. doi:10.1007/978-3-031-17849-8_22. 2022.
    3. TRAPL, Dalibor, MArtin KRUPIČKA, Vladimír VIŠŇOVSKÝ, Jana HOZZOVÁ, Jaroslav OĽHA, Aleš KŘENEK and Vojtěch SPIWOK. Property Map Collective Variable as a Useful Tool for a Force Field Correction. Journal of Chemical Information and Modeling. American Chemical Society, vol. 62, No 3, p. 567-576. ISSN 1549-9596. doi:10.1021/acs.jcim.1c00651. 2022.
    4. FILIPOVIČ, Jiří, Jana HOZZOVÁ, Amin NEZARAT, Jaroslav OĽHA and Filip PETROVIČ. Using hardware performance counters to speed up autotuning convergence on GPUs. Journal of Parallel and Distributed Computing. Elsevier, vol. 160, February, p. 16-35. ISSN 0743-7315. doi:10.1016/j.jpdc.2021.10.003. 2022.

    2021

    1. VIŠŇOVSKÝ, Vladimír, Viktória SPIŠAKOVÁ, Jana HOZZOVÁ, Jaroslav OĽHA, Dalibor TRAPL, Vojtěch SPIWOK, Lukáš HEJTMÁNEK and Aleš KŘENEK. Complex simulation workflows in containerized high-performance environment. In Armenia S., Geril P. Proc. ESM 2021. Brusel: EUROSIS. p. 42-45. ISBN 978-94-92859-18-1. 2021.
    2. SLANINÁKOVÁ, Terézia, Matej ANTOL, Jaroslav OĽHA and Vlastislav DOHNAL. Data-driven Learned Metric Index: an Unsupervised Approach. In 14th International Conference on Similarity Search and Applications (SISAP 2021). Cham: Springer. p. 81-94. ISBN 978-3-030-89656-0. doi:10.1007/978-3-030-89657-7_7. 2021.
    3. ANTOL, Matej, Jaroslav OĽHA, Terézia SLANINÁKOVÁ and Vlastislav DOHNAL. Learned metric index - proposition of learned indexing for unstructured data. Information Systems. Elsevier, vol. 100, No 101774, p. 1-12. ISSN 0306-4379. doi:10.1016/j.is.2021.101774. 2021.
    4. HOZZOVÁ, Jana, Jiří FILIPOVIČ, Amin NEZARAT, Jaroslav OĽHA and Filip PETROVIČ. Searching CUDA code autotuning spaces with hardware performance counters: data from benchmarks running on various GPU architectures. Data in Brief. Elsevier, vol. 39, December, p. 1-12. ISSN 2352-3409. doi:10.1016/j.dib.2021.107631. 2021.

    2020

    1. PETROVIČ, Filip, David STŘELÁK, Jana HOZZOVÁ, Jaroslav OĽHA, Richard TREMBECKÝ, Siegfried BENKNER and Jiří FILIPOVIČ. A benchmark set of highly-efficient CUDA and OpenCL kernels and its dynamic autotuning with Kernel Tuning Toolkit. Future Generation Computer Systems. Elsevier, vol. 108, July, p. 161-177. ISSN 0167-739X. doi:10.1016/j.future.2020.02.069. 2020.
    2. OĽHA, Jaroslav, Jana HOZZOVÁ, Jan FOUSEK and Jiří FILIPOVIČ. Exploiting historical data: Pruning autotuning spaces and estimating the number of tuning steps. CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE. HOBOKEN: WILEY, vol. 32, No 21, p. 1-15. ISSN 1532-0626. doi:10.1002/cpe.5962. 2020.
    3. KŘENEK, Aleš, Jana HOZZOVÁ, Jaroslav OĽHA, Dalibor TRAPL and Vojtěch SPIWOK. Exploring Protein Folding Space with Neural Network Guided Simulations. In Alexandre Nketsa. MODELLING AND SIMULATION 2020. Brusel: EUROSIS-ETI. p. 305-309. ISBN 978-94-92859-12-9. 2020.

    2019

    1. OĽHA, Jaroslav, Jana HOZZOVÁ, Jan FOUSEK and Jiří FILIPOVIČ. Exploiting historical data: pruning autotuning spaces and estimating the number of tuning steps. In Ulrich Schwardmann, Christian Boehme, Dora B. Heras, Valeria Cardellini, Emmanuel Jeannot, Antonio Salis, Claudio Schifanella, Ravi Reddy Manumachu, Dieter Schwamborn, Laura Ricci, Oh Sangyoon, Thomas Gruber, Laura Antonelli, Stephen L. Scott. Lecture Notes in Computer Science. Cham, Switzerland: Springer, Cham. p. 295-307. ISBN 978-3-030-48339-5. doi:10.1007/978-3-030-48340-1_23. 2019.

    2018

    1. PAZÚRIKOVÁ, Jana, Jaroslav OĽHA, Aleš KŘENEK and Vojtěch SPIWOK. Acceleration of Mean Square Distance Calculations with Floating Close Structure in Metadynamics Simulations. arXiv. 22 pp. arXiv:1801.02362. 2018.
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