Project information
CERIT Scientific Cloud
(CERIT-SC)
- Project Identification
- CZ.02.1.01/0.0/0.0/16_013/0001802 (kod CEP: EF16_013/0001802)
- Project Period
- 5/2017 - 6/2021
- Investor / Pogramme / Project type
-
Ministry of Education, Youth and Sports of the CR
- Operational Programme Research, Development and Education
- Priority axis 1: Strengthening capacities for high-quality research
- MU Faculty or unit
-
Institute of Computer Science
- Mgr. Aleš Křenek, Ph.D.
- doc. Ing. RNDr. Barbora Bühnová, Ph.D.
- doc. RNDr. Jiří Filipovič, Ph.D.
- doc. Mouzhi Ge, Ph.D.
- Mgr. Samuel Gorta
- Mgr. Jan Horáček
- Ing. Jana Hozzová, Ph.D.
- Mgr. Kristián Katanik
- Mgr. Vojtěch Krajňanský
- Mgr. Aleš Křenek, Ph.D.
- RNDr. Martin Macák, Ph.D.
- Mgr. David Myška
- RNDr. Petra Němcová
- Mgr. et Mgr. Jaroslav Oľha
- Mgr. Marek Pastierik
- RNDr. Tomáš Raček, Ph.D.
- RNDr. Tomáš Rebok, Ph.D.
- Bruno Rossi, PhD
- Bc. Maksym Skoryk
- RNDr. Terézia Slanináková
- Mgr. Radim Šašinka
- Mgr. Matúš Štovčik
- Muhammad Usman, Ph.D.
- Mgr. Vladimír Višňovský
- Project Website
- https://www.cerit-sc.cz/en
Centre CERIT-SC (CERIT Scientific Cloud) is a national centre operating a computing and data storage experimental infrastructure for research and development in the area of flexible e-infrastructures and large in-silico experiments, performed in close collaboration with other scientific disciplines. Its top-level mission can be phrased as “Speeding up the time from ideas to publications (and products) in all research disciplines”. The centre is built on three pillars: hardware resources of sufficient scale to ensure competitiveness, excellent research in specific areas of computer science (i.e. know-how to use the hardware resources efficiently), and long-term collaboration with the user communities (being true research partners of the users, not just providers of “precanned” technical solutions). This project aims at strengthening the first and the second pillar; the third one is currently being funded by other means.
Specifically, significant part of project budget is investment to hardware, pushing the centre’s equipment to the leading edge of available technology. This is complemented with the in-house research programme, with the goal to increase the efficient usage of the current and procured infrastructure.
The research programme will consist of two integrated subprogrammes aimed at big data analysis and high performance computing. Their approach to efficient use of infrastructure is complementary. While the Big Data subprogramme approaches it more top-down, concentrating on data processing methods and software architectures at a higher level, the High Performance Computing subprogramme concentrates on optimization at a lower level, from bottom-up. The Big Data research subprogramme will focus on the research in efficient big data analysis, with special focus on the careful selection of the best-fit data analysis technique to each specific problem setup. The High Performance Computing research subprogramme will focus on software parallelization, acceleration and optimization, including automated frameworks.
Publications
Total number of publications: 39
2020
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The Suitability of Graph Databases for Big Data Analysis: A Benchmark
Proceedings of the 5th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS, year: 2020
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Towards Process Mining Utilization in Insider Threat Detection from Audit Logs
2020 Seventh International Conference on Social Networks Analysis, Management and Security (SNAMS), year: 2020
2019
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A GPU acceleration of 3-D Fourier reconstruction in cryo-EM
The International Journal of High Performance Computing Applications, year: 2019, volume: 33, edition: 5, DOI
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A Research Roadmap of Big Data Clustering Algorithms for Future Internet of Things
International Journal of Organizational and Collective Intelligence, year: 2019, volume: 9, edition: 2, DOI
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Big Data - overview, basic concepts and practical use in research
Year: 2019, type:
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Big Data Platform for Smart Grids Power Consumption Anomaly Detection
Proceedings of the 2019 Federated Conference on Computer Science and Information Systems, year: 2019
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Exploiting historical data: pruning autotuning spaces and estimating the number of tuning steps
Lecture Notes in Computer Science, year: 2019
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Quality Management for Big 3D Data Analytics: A Case Study of Protein Data Bank
Proceedings of the 4th International Conference on Internet of Things, Big Data and Security - Volume 1, year: 2019
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Scaling Big Data Applications in Smart City with Coresets
Proceedings of the 8th International Conference on Data Science, Technology and Applications - Volume 1, year: 2019
2018
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A Large-Scale Study on Source Code Reviewer Recommendation
44th Euromicro Conference on Software Engineering and Advanced Applications (SEAA) 2018, year: 2018