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ORCIDJaroslav Olha
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2020 – today
- 2024
[c5]David Procházka, Terézia Slanináková, Jozef Cernanský, Jaroslav Olha
, Matej Antol, Vlastislav Dohnal:
Scaling Learned Metric Index to 100M Datasets. SISAP 2024: 266-273- 2023
- [j7]David Strelák, David Myska, Filip Petrovic, Jan Polák, Jaroslav Olha, Jiri Filipovic:
Umpalumpa: a framework for efficient execution of complex image processing workloads on heterogeneous nodes. Computing 105(11): 2389-2417 (2023) - [j6]Terézia Slanináková, Matej Antol, Jaroslav Olha, Vlastislav Dohnal, Susana Ladra, Miguel A. Martínez-Prieto:
Reproducible experiments with Learned Metric Index Framework. Inf. Syst. 118: 102255 (2023) - [c4]Terézia Slanináková, David Procházka, Matej Antol, Jaroslav Olha, Vlastislav Dohnal:
SISAP 2023 Indexing Challenge - Learned Metric Index. SISAP 2023: 282-290 - 2022
- [j5]Dalibor Trapl, Martin Krupicka, Vladimír Visnovský, Jana Hozzová, Jaroslav Olha, Ales Krenek, Vojtech Spiwok:
Property Map Collective Variable as a Useful Tool for a Force Field Correction. J. Chem. Inf. Model. 62(3): 567-576 (2022) - [j4]Jiri Filipovic, Jana Hozzová, Amin Nezarat, Jaroslav Olha, Filip Petrovic:
Using hardware performance counters to speed up autotuning convergence on GPUs. J. Parallel Distributed Comput. 160: 16-35 (2022) - [c3]Jaroslav Olha, Terézia Slanináková, Martin Gendiar, Matej Antol, Vlastislav Dohnal:
Learned Indexing in Proteins: Substituting Complex Distance Calculations with Embedding and Clustering Techniques. SISAP 2022: 274-282 - [i5]Jaroslav Olha, Terézia Slanináková, Martin Gendiar, Matej Antol, Vlastislav Dohnal:
Learned Indexing in Proteins: Substituting Complex Distance Calculations with Embedding and Clustering Techniques. CoRR abs/2208.08910 (2022) - 2021
- [j3]Matej Antol, Jaroslav Olha, Terézia Slanináková, Vlastislav Dohnal:
Learned Metric Index - Proposition of learned indexing for unstructured data. Inf. Syst. 100: 101774 (2021) - [c2]Terézia Slanináková, Matej Antol, Jaroslav Olha, Vojtech Kana, Vlastislav Dohnal:
Data-Driven Learned Metric Index: An Unsupervised Approach. SISAP 2021: 81-94 - [i4]Jiri Filipovic, Jana Hozzová, Amin Nezarat, Jaroslav Olha, Filip Petrovic:
Using hardware performance counters to speed up autotuning convergence on GPUs. CoRR abs/2102.05297 (2021) - [i3]Jiri Filipovic, Jana Hozzová, Amin Nezarat, Jaroslav Olha, Filip Petrovic:
Searching CUDA code autotuning spaces with hardware performance counters: data from benchmarks running on various GPU architectures. CoRR abs/2102.05299 (2021) - 2020
- [j2]Jaroslav Olha, Jana Hozzová, Jan Fousek, Jiri Filipovic:
Exploiting historical data: Pruning autotuning spaces and estimating the number of tuning steps. Concurr. Comput. Pract. Exp. 32(21) (2020) - [j1]Filip Petrovic, David Strelák, Jana Hozzová, Jaroslav Olha, Richard Trembecký, Siegfried Benkner, Jiri Filipovic:
A benchmark set of highly-efficient CUDA and OpenCL kernels and its dynamic autotuning with Kernel Tuning Toolkit. Future Gener. Comput. Syst. 108: 161-177 (2020)
2010 – 2019
- 2019
- [c1]Jaroslav Olha, Jana Hozzová, Jan Fousek, Jiri Filipovic:
Exploiting Historical Data: Pruning Autotuning Spaces and Estimating the Number of Tuning Steps. Euro-Par Workshops 2019: 295-307 - [i2]Filip Petrovic, David Strelák, Jana Hozzová, Jaroslav Olha, Richard Trembecký, Siegfried Benkner, Jiri Filipovic:
A Benchmark Set of Highly-efficient CUDA and OpenCL Kernels and its Dynamic Autotuning with Kernel Tuning Toolkit. CoRR abs/1910.08498 (2019) - 2018
- [i1]Jana Pazúriková, Jaroslav Olha, Ales Krenek, Vojtech Spiwok:
Acceleration of Mean Square Distance Calculations with Floating Close Structure in Metadynamics Simulations. CoRR abs/1801.02362 (2018)
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