Projects of the Parallel and distributed information processing department VEGA – Scientific Grant Agency of SR and SAS
GAV – Grant Agency for Science
COPERNICUS – European Communities
ASFEU – Agency of SR for EU Structural Funds
SRDA – Agency for research&development support
MAD – Inter-academic agreement

Actual and recent projects:

Imaging data and services for aquatic science (iMagine)
Cloudové služby pre spracovanie obrazových údajov pre vedy o vode
Program: Horizon Europe
Project leader: Ing. Tran Viet, PhD.
ID: 101058625
Duration: 1.9.2022 - 31.8.2025
Annotation
EOSC Beyond: advancing innovation and collaboration for research
EOSC Beyond: pokrok v inováciách a spolupráci v oblasti výskumu
Program: Horizon Europe
Project leader: Ing. Tran Viet, PhD.
ID: 101131875
Duration: 1.4.2024 - 31.3.2027
Annotation
Integrated Technological and Information Platformfor wildfire Management (SILVANUS)
Integrovaná technologická a informačná platforma pre manažment lesných požiarov
Program: Horizon 2020
Project leader: Ing. Balogh Zoltán, PhD.
ID: H2020-101037247
Duration: 1.10.2021 - 31.3.2025
Annotation
Artificial Intelligence for the European Open Science Cloud (AI4EOSC)
Umelá inteligencia pre EOSC
Program: Horizon Europe
Project leader: Ing. Tran Viet, PhD.
ID: 101058593
Duration: 1.9.2022 - 31.8.2025
Web page: https://ai4eosc.eu/
Annotation
leveraging the European compute infrastructures for data-intensive research guided by FAIR principles (EuroScienceGateway)
využitie európskych výpočtových infraštruktúr pre výskum náročný na údaje riadený zásadami FAIR
Program: Horizon Europe
Project leader: Ing. Tran Viet, PhD.
ID: 101057388
Duration: 1.9.2022 - 31.8.2025
Annotation
Secure Interactive Environments for SensiTive data Analytics (SIESTA)
Zabezpečené interaktívne prostredia pre analýzu citlivých údajov
Program: Horizon Europe
Project leader: Ing. Tran Viet, PhD.
ID: 101131957
Duration: 1.1.2024 - 31.12.2026
Annotation
Semantic distributed computing continuum for extreme data processing
Sémantické distribuované výpočtové kontinuum pre spracovanie extrémnych dát
Program: VEGA
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: 2/0131/23
Duration: 1.1.2023 - 31.12.2025
Artificial Intelligence for Personalised Oncology: from Single-Sample Assessment to Real-time Monitoring of Solid Tumours (AIPOLOGY)
Umelá inteligencia pre precíznu onkológiu: od analýzy jednotlivých vzoriek po real-time monitorovanie progresie nádorových ochorení.
Program: SRDA
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: APVV-21-0448
Duration: 1.7.2022 - 30.6.2025
Annotation

Finished projects:

3D Visualization of Spatial Data
3D vizualizácia priestorových údajov
Program: Inter-governmental agreement
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: 53s07
Duration: 1.1.2006 - 30.11.2007
Web page: http://ups.savba.sk/3dspatial/
Annotation
Seamless Communication for Crisis Management (SeCriCom)
Bezproblémová komunikácia pre krízový manažment
Program: FP7
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: FP7-218123
Duration: 1.9.2008 - 30.4.2012
Web page: http://en.wikipedia.org/wiki/Secricom
Annotation
Data Fusion for Flood Analysis and Decision Support (ANFAS)
Datová fúzia pre analýzu povodní a podporu rozhodovania
Program: FP5
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: IST-1999-11676
Duration: 1.1.2000 - 28.2.2003
Web page: https://cordis.europa.eu/project/rcn/53064/factsheet/en
Annotation
EGI Advanced Computing for EOSC (EGI-ACE)
EGI pokročilé počítanie pre EOSC
Program: Horizon 2020
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: H2020-101017567
Duration: 1.1.2021 - 30.6.2023
Web page: https://www.egi.eu/projects/egi-ace/
Annotation
EGI: Integrated Sustainable Pan-European Infrastructure for Researchers in Europe (EGI-InSPIRE)
EGI: Integrovaná udržateľná pan-európska infraštruktúra pre vedu v Európe
Program: FP7
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: FP7-261323
Duration: 1.5.2010 - 31.12.2014
Web page: www.egi.eu
Annotation
European Open Science Cloud - Expanding Capacities by building Capabilities (EOSC-Synergy)
Európsky cloud pre otvorenú vedu – rozšírenie kapacít budovaním infraštruktúrneho potenciálu
Program: Horizon 2020
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: 857647
Duration: 1.9.2019 - 31.10.2022
Annotation
Data Fusion Grid Infrastructure
Gridová infraštruktúra pre údajovú fúziu
Program: INTAS
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: 06-1000024-9154
Duration: 1.1.2007 - 31.12.2008
Hybrid Medical Complex Systems (SK-RO)
Hybrid Medical Complex Systems
Program: Inter-governmental agreement
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID:
Duration: 1.1.2011 - 31.12.2012
Annotation
Integrating and managing services for the European Open Science Cloud (EOSC-hub)
Integrovanie a manažment služieb pre európsky cloud pre otvorenú vedu
Program: Horizon 2020
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: 777536
Duration: 1.1.2018 - 31.3.2021
Annotation
Interactive European Grid (int.eu.grid)
Interaktívny Európsky Grid
Program: FP6
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: FP6-31857
Duration: 1.5.2006 - 30.4.2008
Web page: grid.ifca.inican.es/int.eu.grid
Annotation
Mediterranean Grid of Multi-Risk Data and Models (MEDIGRID)
Juhoeurópsky Grid multi-rizikových údajov a modelov
Program: FP6
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: 4044
Duration: 1.11.2004 - 31.10.2006
Annotation
Parallel Processing Tools: Integration and Result Dissemination (KIT)
Nástroje pre paralené spracovanie informácií: Integrácia a ďalšie rozšírenie výsledkov
Program: CIP-ICT
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: 977100-PPTIRD
Duration: 17.7.1998 - 16.7.1999
Web page: https://cordis.europa.eu/project/id/977100
Annotation
High Performance Computing Tools for Industry, EU Copernicus (HPCTI)
Nástroje pre vysokovýkonné počítanie v priemysle, EU Copernicus
Program: CIP-ICT
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: CP-93-5383
Duration: 1.10.1994 - 30.9.1996
Web page: http://ups.savba.sk/parcom/sephp/sephp.html
Annotation
Designing and Enabling E-infrastructures for intensive Processing in a Hybrid DataCloud (DEEP-HybridDataCloud)
Návrh a sprístupnenie e-infraštruktúr pre intenzívne spracovanie v hybridnom dátovom cloude
Program: Horizon 2020
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: 777435
Duration: 1.11.2017 - 30.4.2020
Web page: http://deep-hybrid-datacloud.eu/
Annotation
Development of machine learning models for high-performance computing
Návrh modelov strojového učenia pre vysoko-výkonné počítanie.
Program: Inter-academic agreement
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID:
Duration: 1.4.2020 - 31.12.2022
Annotation
Development of software tools for analysis and synthesis of schedulers for cloud computing
Návrh softvérových nástrojov pre analýzu a syntézu plánovačov pre počítanie v cloude
Program: Inter-academic agreement
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID:
Duration: 6.4.2017 - 31.12.2019
Annotation
A Platform for Organisationally Mobile Public Employees (Pellucid)
Platforma pre zamestnancov verejnej správy migrujúcich medzi organizáciami
Program: FP5
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: IST-2001-34519
Duration: 1.3.2002 - 31.12.2004
Web page: http://agents.ui.sav.sk/index.php?n=Main.Projects https://cordis.europa.eu/project/rcn/61524/factsheet/en
Annotation
COMMunity-based Interoperability Utility for SMEs (Commius)
Podpora Interoperability pre MSP založená na ISU
Program: FP7
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: FP7-213876
Duration: 1.2.2008 - 31.1.2011
Web page: www.commius.eu
Annotation
Advanced Data Mining and Integration Research for Europe (ADMIRE)
Pokročilé dolovanie a integrácia dát pre Európu
Program: FP7
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: FP7-215024
Duration: 1.3.2008 - 28.2.2011
PROviding Computing solutions for ExaScale challengeS (PROCESS)
Poskytovanie výpočtových riešení pre výzvy v oblasti ExaScale
Program: Horizon 2020
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: 777533
Duration: 1.11.2017 - 30.10.2020
Web page: http://www.process-project.eu/
Annotation
Flood Forecasting Computed on Grid Infrastructures
Predpoved povodní pomocou počítania na gridových infraštruktúrach
Program: NATO
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: 981032
Duration: 1.1.2004 - 31.12.2006
Annotation
Programming environment for adaptive development of high performance parallel software on heterogeneous platforms (MAD with s ISS NASU, Kyiv)
Programming environment for adaptive development of high performance parallel software on heterogeneous platforms
Program: Inter-academic agreement
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID:
Duration: 1.1.2011 - 31.12.2013
RAilway Network of Excelence
-
Program: European Science Foundation (ESF)
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: SORO/JPD 3-094/2005/NP1-033, 13120200104
Duration: 3.1.2007 - 31.12.2007
Dissemination and Exploitation GRids in Earth sciencE (DEGREE)
Rozšírenie a využitie gridov vo vede o Zemi
Program: FP6
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: FP6-034619
Duration: 1.6.2006 - 31.5.2008
Web page: www.eu-degree.eu
Annotation
European Urban Simulation for Asymmetric Scenarios (EUSAS)
Simulácia správania pre asymetrické scenáre v urbanizáciách
Program: EDA
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: A-0938-RT-GC
Duration: 1.3.2010 - 31.8.2012
Social Network of Machines (SOON)
Sociálna sieť strojov
Program: ERANET
Project leader: Ing. Balogh Zoltán, PhD.
ID:
Duration: 1.3.2019 - 30.4.2022
Annotation
Software Engineering for Parallel Processing, EU Copernicus (SEPP)
Softvérové inžinierstvo v paralelnom spracovaní informácií, EU Copernicus
Program: CIP-ICT
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: CIPA - CT93-0251
Duration: 1.2.1994 - 31.3.1997
Web page: http://ups.savba.sk/parcom/sephp/sephp.html https://cordis.europa.eu/project/id/CIPA930251
Enabling Grids for E-scienE III (EGEE-III)
Sprístupnenie Gridu pre e-vedu III
Program: FP7
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: FP7-222667
Duration: 1.5.2008 - 30.4.2010
Web page: www.eu-egee.org
Enabling Grids for E-Science in Europe (EGEE)
Sprístupnenie Gridu pre e-vedu v Európe
Program: FP6
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: 508833
Duration: 1.4.2004 - 31.3.2006
Web page: www.eu-egee.org
Annotation
Enabling Grids for E-sciencE II (EGEE II)
Sprístupnenie Gridu pre e-vedu v Európe II
Program: FP6
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: RI-031688
Duration: 1.4.2006 - 31.3.2008
Web page: www.eu-egee.sk
Annotation
Stimulation of European Industry through High Performance Computing, EU Copernicus Network (SEIHPC)
Stimulácia európskeho priemyslu pomocou vysokovýkonného počítania , EU Copernicus sieťový projekt
Program: CIP-ICT
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: COP-94-00774
Duration: 1.4.1995 - 31.3.1997
Web page: https://cordis.europa.eu/project/id/CP94-774
Annotation
Emergency Responder Data Interoperability Network (REDIRNET)
Systém pre dátovú interoperabilitu záchranných zložiek
Program: FP7
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: FP7 - 607768
Duration: 1.3.2014 - 31.8.2016
Annotation
Virtual Enterprises by Networked Interoperability Services (VENIS)
Virtuálne podniky zosieťované navzájom prepojenými službami
Program: FP7
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: FP7 – 284984
Duration: 1.9.2011 - 31.8.2015
Annotation
DevelOpment of GRID Environment for InteRaCtive ApplicationS (CROSSGRID)
Vývoj Grid prostredia pre interaktívne aplikácie
Program: FP5
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: IST-2001-32243
Duration: 1.3.2002 - 30.4.2005
Web page: https://cordis.europa.eu/project/rcn/63588/factsheet/en
Engaging the EGI Community towards an Open Science Commons (EGI-Engage)
Zapojenie EGI spoločenstva smerom k otvorenej vede
Program: Horizon 2020
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: 654142
Duration: 1.3.2015 - 31.8.2017
Web page: https://www.egi.eu/about/projects/
Annotation
Knowledge-based Workflow System for Grid Applications (K-WfGrid)
Znalostná konštrukcia toku práce v Gridových aplikáciách
Program: FP6
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: FP6-511385
Duration: 1.9.2004 - 28.2.2007
Web page: www.kwfgrid.net
Annotation
Rapid Operational Analytics for flood Response (ROAR-PP-H2020)
- (ROAR-PP-H2020)
Program: SRDA
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: PP-H2020-18-0017
Duration: 28.8.2018 - 31.12.2018
Experimentation platform for the successsful adoption of disruptive technologies in public services (XPERT-PP-H2020)
- (XPERT-PP-H2020)
Program: SRDA
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: PP-H2020-18-0012
Duration: 28.8.2018 - 31.12.2018
Adaptive Interoperability Framework for Private and Public Sector (AIIA)
Adaptívna platforma na podporu interoperability v súkromnom a verejnom sektore
Program: SRDA
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: APVV-0216-07
Duration: 1.9.2008 - 31.12.2010
Web page: http://aiia.ui.sav.sk/
Annotation
(INTAP)
Aplikačná platforma pre interaktívne gridové aplikácie
Program: SRDA
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: RPEU-0029-06
Duration: 15.2.2007 - 31.8.2008
Seamless Communication for Crisis Management
Bezproblémová komunikácia pre krízový manažment (SeCriCom-APVV)
Program: SRDA
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: DO7RP-0007-08
Duration: 1.9.2008 - 31.12.2009
Seamless Communication for Crisis Management
Bezproblémová komunikácia pre krízový manažment (SeCriCom-MVTS)
Program:
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID:
Duration: 1.9.2008 - 31.12.2009
Centre for the Research of Risks of Water Distribution in a Large City (CVR)
Centrum výskumu rizík zásobovania vodou velkého mesta
Program: EU Structural Funds Research Development
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: ITMS 26240220082
Duration: 1.7.2012 - 30.6.2015
Cloud Computing for Big Data Analytics (Clan)
Cloudové Počítanie Pre Analýzu Veľkých Dát
Program: SRDA
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: APVV-0809-11
Duration: 1.7.2012 - 31.12.2015
Web page: clan.ui.sav.sk
Efficient tools and mechanisms for grid computing
Efektívne nástroje a mechanizmy pre gridové čítanie
Program: VEGA
Project leader: Ing. Tran Viet, PhD.
ID: 2/6103/6
Duration: 1.1.2006 - 1.12.2008
Annotation
FaceControl – komplexné komunikačné zariadenie pre inovatívne riadenie výrobných a podporných procesov v priemysle (FACECONTROL)
FaceControl – komplexné komunikačné zariadenie pre inovatívne riadenie výrobných a podporných procesov v priemysle
Program:
Project leader: Ing. Forgáč Radoslav, PhD.
ID: 313012P897
Duration: 1.3.2019 - 31.10.2020
Web page: https://www.ui.sav.sk/w/wp-content/uploads/FACECONTROL_web.pdf
Intelligent methods for large scale information processing
Inteligentné metódy pre spracovanie rozsiahlych informačných zdrojov
Program: VEGA
Project leader: Doc. RNDr. Laclavík Michal, PhD.
ID: 2/0184/10
Duration: 1.1.2010 - 31.12.2012
Annotation
Intelligent Cloud Workflow Management for Dynamic Metric- Optimized Application Deployment (ICONTROL)
Inteligentné riadenie tokov práce v cloude pre dynamické a metrikami optimalizované nasadzovanie aplikácií
Program: SRDA
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: APVV-20-0571
Duration: 1.7.2021 - 31.12.2023
Annotation
Intelligent technologies for knowlege oriented organizations
Inteligentné technológie pre znalostne orientované organizácie
Program: VEGA
Project leader: Doc. RNDr. Laclavík Michal, PhD.
ID: VEGA 2/7098/27
Duration: 1.1.2007 - 31.12.2009
Web page: http://ikt.ui.sav.sk/vega/
Annotation
Cognitive traveling in digital space of the Web and digital libraries supported by personalized services and social networks (TraDiCe)
Kognitívne cestovanie po digitálnom svete webu a knižníc s podporou personalizovaných služieb a sociálnych sietí
Program: SRDA
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: APVV-0208-10
Duration: 1.5.2011 - 31.10.2014
Competence Center for SMART Technologies for Electronics and Informatics Systems and Services (KC-INTELINSYS)
Kompetenčné centrum inteligentných technológií pre elektronizáciu a informatizáciu systémov a služieb
Program: EU Structural Funds Research Development
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: ITMS 26240220072
Duration: 1.9.2011 - 30.6.2015
Methods and algorithms for the semantic processing of Big Data in distributed computing environment
Metódy a algoritmy pre sémantické spracovanie veľkých dát v distribuovanom výpočtovom prostredí
Program: VEGA
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: 2/0167/16
Duration: 1.1.2016 - 31.12.2019
Annotation
(GRID-TOOLS)
Nástroje pre prípravu, efektívne vykonávanie a vizualizáciu aplikácií a správu dát v prostredí Gridu
Program: SRDA
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: RPEU-0024-06
Duration: 15.2.2007 - 31.8.2008
-
Nástroje pre získanie, organizovanie a udržovanie znalostí v prostredí heterogénnych informačných zdrojov
Program:
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID:
Duration: 1.9.2004 - 31.3.2008
New Methods and Approaches for Distributed Scalable Computing
Nové metódy a prístupy pre distribuované škálované počítanie
Program: VEGA
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: 2/0125/20
Duration: 1.1.2020 - 31.12.2022
Annotation
Optimization of recycling production lines by application of nonconventional control methods. (OptiMAT)
Optimalizácia recyklačných výrobných liniek aplikovaním nekonvenčných metód riadenia
Program: SRDA
Project leader: Ing. Balogh Zoltán, PhD.
ID: VMSP-016-09
Duration: 1.9.2009 - 31.8.2011
Center of Excellence for SMART Technologies, Systems and Services
Podpora budovania Centra exelentnosti pre SMART technológie, systémy a služby
Program: EU Structural Funds Research Development
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: 26240120005
Duration: 1.5.2009 - 30.4.2011
Center of Excellence for SMART Technologies, Systems and Services II
Podpora dobudovania Centra exelentnosti pre SMART technológie, systémy a služby - II
Program: EU Structural Funds Research Development
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: 26240120029
Duration: 1.1.2010 - 31.1.2014
COMMunity-based Interoperability Utility for SMEs
Podpora Interoperability pre MSP založená na ISU (Commius-APVV)
Program: SRDA
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: DO7RP-0005-08
Duration: 1.2.2008 - 31.12.2009
COMMunity-based Interoperability Utility for SMEs
Podpora Interoperability pre MSP založená na ISU (Commius-MVTS)
Program:
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID:
Duration: 1.2.2008 - 31.12.2009
Advanced Data Mining and Integration Research for Europe
Pokročilé dolovanie a integrácia dát pre Európu (ADMIRE-APVV)
Program: SRDA
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: DO7RP-0006-08
Duration: 1.3.2008 - 31.12.2009
Advanced Data Mining and Integration Research for Europe
Pokročilé dolovanie a integrácia dát pre Európu (ADMIRE-MVTS)
Program:
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: FP7-215024
Duration: 1.3.2008 - 31.12.2009
Data Mining Meteo (DMM)
Predpovedné a detekčné metódy význačných a nebezpečných javov založené na dolovaní meteorologických dát
Program: SRDA
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: VMSP-P-0048-09
Duration: 1.9.2009 - 31.8.2011
Industry research in the area of effective work with large data in user oriented applications (RECLER)
Priemyselný výskum v oblasti efektívnej práce s rozsiahlymi dátami v používateľsky orientovaných aplikáciách
Program: EU Structural Funds Research Development
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: ITMS 26240220029
Duration: 1.5.2010 - 30.4.2012
Web page: http://www.anasoft.com/sk/pages/Priemyselny-vyskum.shtml
Semantic composition of Web and Grid Services (SEMCO-WS)
Sémantická kompozícia webových a gridových služieb
Program: SRDA
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: APVV-0391-06
Duration: 1.2.2007 - 31.12.2009
Service-based distributed computing and data management
Servisne-orientované distribuované počítanie a dátový manažment
Program: VEGA
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: 2/0211/09
Duration: 1.1.2009 - 31.12.2011
Annotation
Slovak infrastructure for high performance computing (SIVVP)
Slovenská infraštruktúra pre vysokovýkonné počítanie
Program: EU Structural Funds Research Development
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: ITMS 26230120002
Duration: 15.1.2010 - 31.12.2015
Enabling Grids for E-scienE III
Sprístupnenie Gridu pre e-vedu III (EGEE-III-MVTS)
Program:
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID:
Duration: 1.5.2008 - 31.12.2009
Sports Video And Statictics Automation System (SVASAS)
Systém pre automatizáciu videa a štatistík v športe
Program:
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: NFP313020U867
Duration: 1.6.2020 - 31.5.2021
Urgent Computing for Exascale Data (U-COMP)
Urgentné počítanie pre Exascale dáta
Program: SRDA
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: APVV-17-0619
Duration: 1.8.2018 - 31.12.2020
Annotation
Virtual and constructive modelling, training and simulaion of crowd behaviour in urban environment (Riot)
Virtuálne a konštruktívne modelovanie, tréning a simulácia správania davu v mestskom prostredí
Program: SRDA
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: APVV-0233-10
Duration: 1.5.2011 - 31.10.2014
Selected methods, approaches and tools for distributed computing.
Vybrané metody, prístupy a nástroje pre distribuované spracovanie informácií.
Program: VEGA
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: 2/0054/12
Duration: 1.1.2012 - 31.12.2015
Annotation
(CRISIS)
Výskum a vývoj nových informačných technológií na predvídanie a riešenie krízových situácií a bezpečnosť obyvateľstva
Program: EU Structural Funds Research Development
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: ITMS 26240220060
Duration: 3.1.2011 - 31.12.2013
(RAPORT)
Výskum a vývoj znalostného systému na podporu riadenia toku práce v organizáciách s administratívnymi typmi procesov
Program: SRDA
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: APVT-51-024604
Duration: 1.2.2005 - 31.12.2007
Research on the application of artificial intelligence tools in the analysis and classification of hyperspectral sensing data (HYSPED)
Výskum aplikácie prostriedkov umelej inteligencie pri analýzach a klasifikácií dát hyperspektrálneho snímkovania
Program:
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: NFP313011BWC9
Duration: 1.2.2022 - 31.12.2023
(RPKOM)
Výskum technológií pre riadenie podnikových procesov v heterogénnych distribuovaných systémoch v reálnom čase s podporou multimodálnej komunikácie
Program: EU Structural Funds Research Development
Project leader: doc. Ing. Hluchý Ladislav, CSc.
ID: ITMS 26240220064
Duration: 3.1.2011 - 30.6.2014
PFO-CAD CP93: 7896 - Copernicus program - Geometric Modeling for CIM-oriented Virtual Reality
PFO-CAD CP93: 7896 - Copernicus program - Geometric Modeling for CIM-oriented Virtual Reality
Program: Other
Project leader: Ing. Sebestyénová Jolana, PhD.
ID: CP93: 7896
Duration: 1.2.1994 - 30.4.1995
Web page: http://cordis.europa.eu/project/rcn/30200_en.html
Annotation

Actual and recent projects (annotations):

Imaging data and services for aquatic science (iMagine)
Cloudové služby pre spracovanie obrazových údajov pre vedy o vode
Annotation: iMagine provides a portfolio of free at the point of use image datasets, high-performance image analysis tools empowered with Artificial Intelligence (AI), and Best Practice documents for scientific image analysis. These services and materials enable better and more efficientprocessing and analysis of imaging data in marine and freshwater research, accelerating our scientific insights about processes and measures relevant for healthy oceans, seas, coastal and inland waters. By building on the computing platform of the European Open Science Cloud (EOSC) the project delivers a generic framework for AI model development, training, and deployment, which can be adopted by researchers for refining their AI-based applications for water pollution mitigation, biodiversity and ecosystem studies, climate change analysis and beach monitoring, but also for developing and optimising other AI-based applications in this field. The iMagine compute layer consists of providers from the pan-European EGI federation infrastructure, collectively offering over 132,000 GPU-hours, 6,000,000 CPU-hours and 1500 TB-month for image hosting and processing. The iMagine AI framework offers neural networks, parallel post-processing of very large data, and analysis of massive online data streams in distributed environments. 13 RIs will share over 9 million images and 8 AI-powered applications through the framework. Having representatives so many RIs and IT experts, developing a portfolio of eye-catching image processing services together will also give rise to Best Practices. The synergies between aquatic use caseswill lead to common solutions in data management, quality control, performance, integration, provenance, and FAIRness, contributing to harmonisation across RIs and providing input for the iMagine Best Practice guidelines. The project results will be integrated into and will bring important contributions from RIs and e-infrastructures to EOSC and AI4EU.
EOSC Beyond: advancing innovation and collaboration for research
EOSC Beyond: pokrok v inováciách a spolupráci v oblasti výskumu
Annotation: EOSC Beyond overall objective is to advance Open Science and innovation in research in the context of the European Open Science Cloud (EOSC) by providing new EOSC Core capabilities allowing scientific applications to find, compose and access multiple Open Science resources and offer them as integrated capabilities to researchers. To do so, EOSC Beyond supports a new concept of EOSC: a federated and integrated network of Nodes operated at different levels, national, regional, international and thematic, to serve the specific scientific missions of their stakeholders. Further specific objectives of the project are to accelerate ‘time to product’ of new scientific applications with software adapters, enable Open Science with machine composability and dynamic deployment of shared resources, support innovation in EOSC with a testing and integration environment, and align the EOSC Core architecture and specifications to integrate with European dataspaces. The project extends the state of the art of the EOSC Core and adopts a co-design methodology, including requirements elicitation, software development and validation in collaboration with different use cases from EOSC national and regional initiatives (e-Infra CZ, Czechia, NFDI, Germany, and NI4OS, South East Europe region), thematic research infrastructures from Social Sciences and Humanities (CESSDA), Life Sciences (CNB-CSIC and Instruct-ERIC), Environmental Science (ENES and LifeWatch), and Health and Food (METROFood-RI). EOSC Beyond builds on the capacities of prospective EOSC Nodes and partners with multi-annual experience in developing solutions for large-scale federated digital infrastructures and aligns with the technical architecture and requirements of data spaces from different business sectors. Ultimately, EOSC Beyond supports Open Science in modern, data-intensive, and multidisciplinary research, facilitating resource discovery, access, and reuse across scientific communities, organisations, and countries.
Integrated Technological and Information Platformfor wildfire Management (SILVANUS)
Integrovaná technologická a informačná platforma pre manažment lesných požiarov
Annotation: SILVANUS envisages to deliver an environmentally sustainable and climate resilient forest management platform through innovative capabilities to prevent and combat against the ignition and spread of forest fires. The platform will cater to the demands of efficientresource utilisation and provide protection against threats of wildfires encountered globally. The project will establish synergies between (i) environmental; (ii) technology and (iii) social science experts for enhancing the ability of regional and nationalauthorities to monitor forest resources, evaluate biodiversity, generate more accurate fire risk indicators and promote safety regulations among citizens through awareness campaigns. The novelty of SILVANUS lies in the development and integration ofadvanced semantic technologies to systematically formalise the knowledge of forest administration and resource utilisation. Additionally, the platform will integrate a big-data processing framework capable of analysing heterogeneous data sourcesincluding earth observation resources, climate models and weather data, continuous on-board computation of multi-spectral video streams. Also, the project integrates a series of sensor and actuator technologies using innovative wireless communicationinfrastructure through the coordination of aerial vehicles and ground robots. The technological platform will be complemented with the integration of resilience models, and the results of environmental and ecological studies carried out for the assessment of fire risk indicators based on continuous surveys of forest regions. The surveys are designed to take into consideration the expertise and experience of frontline fire fighter organisations who collectively provide support for 47,504x104 sq. meters of forest area within Europe and across international communities. The project innovation will be validated through 11 pilot demonstrations across Europe and internationally using a two sprint cycle.
Artificial Intelligence for the European Open Science Cloud (AI4EOSC)
Umelá inteligencia pre EOSC
Annotation: The AI4EOSC (Artificial Intelligence for the European Open Science Cloud) delivers an enhanced set of advanced services for the development of Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL) models and applications in the European Open Science Cloud (EOSC). These services are bundled together into a comprehensive platform providing advanced features such as distributed, federated and split learning; novel provenance metadata for AI/ML/DL models; event-driven data processing services or provisioning of AI/ML/DL services based on serverless computing. The project builds on top of the DEEP-Hybrid-DataCloud outcomes and the EOSC compute platform and services in order to provide this specialized compute platform. Moreover, AI4EOSC offers customization components in order to provide tailor made deployments of the platform, adapting to the evolving user needs. The main outcomes of the AI4EOSC project will be a measurable increase of the number of advanced, high level, customizable services available through the EOSC portal, serving as a catalyst for researchers, facilitating the collaboration, easing access to high-end pan-European resources and reducing the time to results; paired with concrete contributions to the EOSC exploitation perspective, creating a new channel to support the build-up of the EOSC Artificial Intelligence and Machine Learning community of practice.
leveraging the European compute infrastructures for data-intensive research guided by FAIR principles (EuroScienceGateway)
využitie európskych výpočtových infraštruktúr pre výskum náročný na údaje riadený zásadami FAIR
Annotation: In the past decade, many scientific domains have been transformed into data-driven disciplines relying on the exchange and integration of internationally distributed data. Exploiting this data is still a laborious and largely manual task, prone to losses and errors, and increasingly specialised beyond most users technical capabilities. FAIR practices are encouraged but their adoption curve is steep. The needs for compute and data resources, tools, and application platforms are often domain-specific. Many scientists struggle to navigate this intricate ecosystem. Generally, researchers do not possess the computing skills to effectively use the HPC or Cloud platforms they need. Thus, new approaches are needed to enable all researchers, with widely ranging digital skills, to efficiently use the diverse computational infrastructures available across Europe, for asynchronous and for interactive applications.EuroScienceGateway will leverage a distributed computing network across 13 European countries, accessible via 6 national, user-friendly web portals, facilitating access to compute and storage infrastructures across Europe as well as to data, tools, workflows and services that can be customized to suit researchers\' needs. At the heart of the proposal workflows will integrate with the EOSC-Core. Adoption, development and implementation of technologies to interoperate across services, will allow researchers to produce high-quality FAIR data, available to all in EOSC. Communities across disciplines - Life Sciences, Climate and Biodiversity, Astrophysics, Materials science - will demonstrate the bridge from EOSC\'s technical services to scientific analysis. EuroScienceGateway will deliver a robust, scalable, seamlessly integrated open infrastructure for data-driven research, contributing an innovative and customizable service for EOSC that enables operational open and FAIR data and data processing, empowering European researchers to embrace the new digital age of science.
Secure Interactive Environments for SensiTive data Analytics (SIESTA)
Zabezpečené interaktívne prostredia pre analýzu citlivých údajov
Annotation: The FAIR principles provide a framework for enabling proper access and reusability of scientific data, and implementing them is a key goal of the European Open Science Cloud (EOSC). However, providing access to sensitive or confidential data while preserving privacy/confidentiality and usability for researchers is still an open question. Existing solutions like safe rooms, safe pods, or data safe havens are often challenging for the development of reproducible research and seem counter-intuitive when dealing with open science and FAIR principles. The SIESTA project aims to provide a set of tools, services, and methodologies for the effective sharing of sensitive data in the EOSC, following a cloud-based model and approach. SIESTA will provide user-friendly tools with the aim of fostering the uptake of sensitive data sharing and processing in the EOSC. The project will deliver trusted cloud-based environments for the management and sharing of sensitive data that are built in a reproducible way, together with a set of services and tools to ease the secure sharing of sensitive data in the EOSC through state-of-the-art anonymization techniques. The overall objective is to enhance the EOSC Exchange services by delivering a set of cloud-based trusted environments for the analysis of sensitive data in the EOSC demonstrating the feasibility of the FAIR principles over them.
Artificial Intelligence for Personalised Oncology: from Single-Sample Assessment to Real-time Monitoring of Solid Tumours (AIPOLOGY)
Umelá inteligencia pre precíznu onkológiu: od analýzy jednotlivých vzoriek po real-time monitorovanie progresie nádorových ochorení.
Annotation: The methodologies that oncologists use to decide on a patient\'s treatment are ever changing. It seems to us that 21st century cancer medicine is much about analysing big data and using mathematical modelling to extract information that can help predict how tumours will evolve and react to potential therapies. The sad fact is, however, that despite ever increasing knowledge on cancer we still lack the proper tools to translate this knowledge to an impactful “bedside” practice that would overcome the limitation from cancer heterogeneity and allow real-time monitoring of disease progression. Here, we propose the AIpology project that aims at the development of novel artificial intelligence strategies to identify molecular traits (individual mutations, mutation signatures and genomic scars) in heterogeneous cancer genomes for which therapeutic targets exist. Based on target clonal mapping and ordering, the system will then outline possible courses of treatment and will intelligently adapt as more data from real time monitoring approaches (such as liquid biopsy) will become available. The system will help us to track each target at the finer time scale than it is possible today and predict future (i.e how the tumour will evolve after being treated with a specific drug) and past (i.e. how long the tumour existed prior to detection) cancer evolutionary trajectories from existing data. Finally, we will understand better why certain cancers become (chemo)therapy-resistant and derive clinically relevant recommendations when they do.

Finished projects (annotations):

3D Visualization of Spatial Data
3D vizualizácia priestorových údajov
Annotation: The project 3D Visualization of Spatial Data is loosely related to the Medigrid project, which goal was to create a system of web services for running the simulations of environmental disasters; and to the project of simulation of forest fires in Slovakia. The goal of the project is to utilise the data and outcomes of simulations obtained in the forementioned projects for creation of three-dimensional models of natural disasters (floods, forest fires, soil erosion, and landslides). An agreed upon requirement was the models shall be capable of being displayed both on an ordinary PC and in the Virutal Reality devices (e.g., CAVE).
Seamless Communication for Crisis Management (SeCriCom)
Bezproblémová komunikácia pre krízový manažment
Annotation: Project\'s aim was to create Seamless Communication for Crisis Management for EU safety. Thirteen partners from eight EU countries had united their capacities in order to produce a competetive solution for secure communication and collaboration of emergency responders with advanced functions.
Data Fusion for Flood Analysis and Decision Support (ANFAS)
Datová fúzia pre analýzu povodní a podporu rozhodovania
Annotation: ANFAS project aims at developing a Support Decision System for flood prevention and protection, integrating the most advanced techniques of data processing and management. Tools based on Computer Vision and Scientific Computing will enable to create a model of the scene and to perform flood simulation. Close involvement of end-users and industrial partners may lead to the realisation of an Integrated Information System close to a prototype. Pilot applications will be carried out on the Vah river in Slovaka, the Loire in France, the Poyang lake and the Three Gorges reservoir in China.
EGI Advanced Computing for EOSC (EGI-ACE)
EGI pokročilé počítanie pre EOSC
Annotation: The mission of the EGI-ACE project of EGI is to implement the Compute Platform of theEuropean Open Science Cloud, by delivering a secure federation of Cloud computeand storage facilities in collaboration with providers of the EGI Federation, commercialproviders, data providers and international research infrastructures of pan-Europeanrelevance.
EGI: Integrated Sustainable Pan-European Infrastructure for Researchers in Europe (EGI-InSPIRE)
EGI: Integrovaná udržateľná pan-európska infraštruktúra pre vedu v Európe
Annotation: Scientific research is no longer conducted within national boundaries and is becoming increasing dependent on the large-scale analysis of data, generated from instruments or computer simulations housed in trans-national facilities, by using e-Infrastructure (distributed computing and storage resources linked by high-performance networks).The 48 month EGI-InSPIRE project will continue the transition to a sustainable pan-European e-Infrastructure started in EGEE-III. It will sustain support for Grids of high-performance and high-throughput computing resources, while seeking to integrate new Distributed Computing Infrastructures (DCIs), i.e. Clouds, SuperComputing, Desktop Grids, etc., as they are required by the European user community. It will establish a central coordinating organisation, EGI.eu, and support the staff throughout Europe necessary to integrate and interoperate individual national grid infrastructures. EGI.eu will provide a coordinating hub for European DCIs, working to bring existing technologies into a single integrated persistent production infrastructure for researchers within the European Research Area.EGI-InSPIRE will collect requirements and provide user-support for the current and new (e.g. ESFRI) users. Support will also be given for the current heavy users as they move their critical services and tools from a central support model to ones driven by their own individual communities. The project will define, verify and integrate within the Unified Middleware Distribution, the middleware from external providers needed to access the e-Infrastructure. The operational tools will be extended by the project to support a national operational deployment model, include new DCI technologies in the production infrastructure and the associated accounting information to help define EGI’s future revenue model.
European Open Science Cloud - Expanding Capacities by building Capabilities (EOSC-Synergy)
Európsky cloud pre otvorenú vedu – rozšírenie kapacít budovaním infraštruktúrneho potenciálu
Annotation: EOSC-synergy extends the EOSC coordination to nine participating countries by harmonizing policies and federating relevant national research e-Infrastructures, scientific data and thematic services, bridging the gap between national initiatives and EOSC.The project introduces new capabilities by opening national thematic services to European access, thus expanding the EOSC offer in the Environment, Climate Change, Earth Observation and Life Sciences. This will be supported by an expansion of the capacity through the federation of compute, storage and data resources aligned with the EOSC and FAIR policies and practices.EOSC-synergy builds on the expertise of leading research organizations, infrastructure providers, NRENs and user communities from Spain, Portugal, Germany, Poland, Czech Republic, Slovakia, Netherlands, United Kingdom and France, all already committed to the EOSC vision and already involved in related activities at national and international level. Furthermore, we will expand EOSC’s global reach by integrating infrastructure and data providers beyond Europe, fostering international collaboration and open new resources to European researchers.The project will push the EOSC state-of-the-art in software and services life-cycle through a quality-driven approach to services integration that will promote the convergence and alignment towards EOSC standards and best practices.This will be complemented by the expansion of the EOSC training and education capabilities through the introduction of an on-line platform aimed at boosting the development of EOSC skills and competences.EOSC-synergy complements on-going activities in EOSC-hub and other related projects liaising national bodies and infrastructures with other upcoming governance, data and national coordination projects.
Hybrid Medical Complex Systems (SK-RO)
Hybrid Medical Complex Systems
Annotation: APVV COST SK-RO-0014-10
Integrating and managing services for the European Open Science Cloud (EOSC-hub)
Integrovanie a manažment služieb pre európsky cloud pre otvorenú vedu
Annotation: The EOSC-hub project creates the integration and management system of the future European Open Science Cloud that delivers a catalogue of services, software and data from the EGI Federation, EUDAT CDI, INDIGO-DataCloud and major research e-infrastructures. This integration and management system (the Hub) builds on mature processes, policies and tools from the leading European federated e-Infrastructures to cover the whole life-cycle of services, from planning to delivery. The Hub aggregates services from local, regional and national e-Infrastructures in Europe, Africa, Asia, Canada and South America. The Hub acts as a single contact point for researchers and innovators to discover, access, use and reuse a broad spectrum of resources for advanced data-driven research. Through the virtual access mechanism, more scientific communities and users have access to services supporting their scientific discovery and collaboration across disciplinary and geographical boundaries. The project also improves skills and knowledge among researchers and service operators by delivering specialised trainings and by establishing competence centres to co-create solutions with the users. In the area of engagement with the private sector, the project creates a Joint Digital Innovation Hub that stimulates an ecosystem of industry/SMEs, service providers and researchers to support business pilots, market take-up and commercial boost strategies. EOSC-hub builds on existing technology already at TRL 8 and addresses the need for interoperability by promoting the adoption of open standards and protocols. By mobilizing e-Infrastructures comprising more than 300 data centres worldwide and 18 pan-European infrastructures, this project is a ground-breaking milestone for the implementation of the European Open Science Cloud.
Interactive European Grid (int.eu.grid)
Interaktívny Európsky Grid
Annotation: no description
Mediterranean Grid of Multi-Risk Data and Models (MEDIGRID)
Juhoeurópsky Grid multi-rizikových údajov a modelov
Annotation: no description
Parallel Processing Tools: Integration and Result Dissemination (KIT)
Nástroje pre paralené spracovanie informácií: Integrácia a ďalšie rozšírenie výsledkov
Annotation: Program: FP4-INCO, KIT - INCO-Esprit Keep in Touch
High Performance Computing Tools for Industry, EU Copernicus (HPCTI)
Nástroje pre vysokovýkonné počítanie v priemysle, EU Copernicus
Annotation: Program:IC-PECO/COPERNICUS.The aim of the HPCTI project is to develop a toolset for the development of parallel application programs for distributed memory multiprocessors, including networks of distributed workstations. The project focuses on the following key research issues in parallel systems engineering: visual programming, simulation, mapping and load-balancing, monitoring, visualisation and quality issues. The project will be conducted within an encompassing task framework of which the SEPP project ( Software Engineering for Parallel Processing ) forms a part. SEPP will primarly address the specification and the development of a graphical CASE environment to support the lifecycle of generic, distributed-memory multiprocessor systems. HPCTI will address the integration of the tools on an agreed hardware/software platform.
Designing and Enabling E-infrastructures for intensive Processing in a Hybrid DataCloud (DEEP-HybridDataCloud)
Návrh a sprístupnenie e-infraštruktúr pre intenzívne spracovanie v hybridnom dátovom cloude
Annotation: The key concept proposed in the DEEP Hybrid DataCloud project is the need to support intensive computing techniques that require specialized HPC hardware, like GPUs or low latency interconnects, to explore very large datasets. A Hybrid Cloud approach enables the access to such resources that are not easily reachable by the researchers at the scale needed in the current EU e-infrastructure. We also propose to deploy under the common label of “DEEP as a Service” a set of building blocks that enable the easy development of applications requiring these techniques: deep learning using neural networks, parallel post-processing of very large data, and analysis of massive online data streams. Three pilot applications exploiting very large datasets in Biology, Physics and Network Security are proposed, and further pilots for dissemination into other areas like Medicine, Earth Observation, Astrophysics, and Citizen Science will be supported in a testbed with significant HPC resources, including latest generation GPUs, to evaluate the performance and scalability of the solutions. A DevOps approach will be implemented to provide the chain to ensure the quality of the software and services released, that will also be offered to the developers of research applications. The project will evolve to TRL8 existing services and technologies at TRL6+, including relevant contributions to the EOSC by the INDIGO-DataCloud H2020 project, that the project will enrich with new functionalities already available as prototypes, notably the support for GPUs and low latency interconnects. These services will be deployed in the project testbed, offered to the research communities linked to the project through pilot applications, and integrated under the EOSC framework, where they can be further scaled up in the future.
Development of machine learning models for high-performance computing
Návrh modelov strojového učenia pre vysoko-výkonné počítanie.
Annotation: Nowadays, Machine learning (ML) is important and relevant trend in the development of modern computer science. ML is not new concept it was part of the field of artificial intelligence for a long time. The main idea focuses on building algorithms that can learn on their own, but recent advances in computing systems and the availability of big data create impressive progress from checkers solving program to self-moved cars and programs that recognize single face from thousands of photos. One of the applications of ML is to improve the efficiency of computations by tuning parameters of environment. Here we deal with complex computational program as with black box, which dynamic depends on parameters. In this project we propose to investigate process of auto tuning of parallel program on heterogeneous multiprocessor system. This problem is important and has some features, that makes it hard for solving. First of all, data and environment can influence performance of program in crucial way. Also, in some setups algorithm can control scheduling making strategy time-dependant.Secondly, an important feature is the presence of competing users. It is necessary to ensure fair and equal access to resources. Because each user is a rational agent and seeks to increase his or her share of the resource at the expense of others, an unbalanced distribution algorithm can shift the system to an inefficient equilibrium. This is problem of game theory. There are notable connections of ML methods with game theory. For example we can mention GANs (generative Adversarial Nets) corresponding to a two-player game, SVM (support vector machine) connected with zero-sum two-player game, and others. This project proposes the following approaches to address the problem. The first is model-free reinforcement machine learning, which is trying to find the best possible control strategy. Secondly, it is the application of the game-theoretic approach, in which the formalized user behavior is involved in the system. Each user has their own learning algorithm and is a rational agent who wants to get some of the computing resource and maximize its utility function. The project continues previous collaboration between institutes in the design of adaptive programming methods for high-performance computing in heterogeneous multiprocessor environments.Project objectives:The purpose of the project is to analyze and synthesize new machine learning algorithms in concurrent high-performance computing. Existing machine learning algorithms are usually heuristic solutions, the quality of which depends on the data and training parameters. One of the promising areas of better understanding of the work is the application of game-theoretical approaches to modeling the learning process of competing algorithms. The results of the game analysis will help to describe the optimal behavior of users at the point of equilibrium and to calculate the characteristics of schedulers and translation algorithms.
Development of software tools for analysis and synthesis of schedulers for cloud computing
Návrh softvérových nástrojov pre analýzu a syntézu plánovačov pre počítanie v cloude
Annotation: Modern scientific problems require significant computing resources, so the problem of resources optimization in multiprocessor environments is very important. We will focus on cloud systems as one of the most recent and promising fields of high-performance computing. Cloud computing systems operate in complex heterogeneous environments. It is common to have a single physical server with many simultaneous programs from different users competing for computing and network resources. In most cases, especially for public cloud, the user is unable to control the distribution of resources.The allocation algorithms may contain defects and inefficiency and this can lead to a significant increase in processing time, that is why cloud computing require efficient algorithms providing flexible and stable allocation of resources. The problem is in unfair and uneven access to resources, caused by heterogeneity of users and their tasks where each user is rational agent that tries to increase its share of resources. This could bring the system to the inefficient equilibrium., so a key element of cloud systems are efficient algorithms for load distribution – schedulers and brokers, providing services to users.The idea of this project is to apply game-theoretic approach to the problem of scheduling and allocation of computing resources in dynamic heterogeneous environment with many competitive users and provide software tools based on game-theoretic construction.Another idea of the project is an optimization approach that respects the requirements of end-users. This task will be modelled as a multi-criteria optimization problem. Each objective of the optimization will be associated with a weight. The weight will express the priority of the optimization objective. This way of the optimization will enable the end-users to adjust it to their needs. The problem will be sorted out in a general way so the solution will support various cloud providers.The project continues the previous cooperation of our Institute in constructing adaptive methods for programming high-performance computing on heterogeneous multiprocessor systems.
A Platform for Organisationally Mobile Public Employees (Pellucid)
Platforma pre zamestnancov verejnej správy migrujúcich medzi organizáciami
Annotation: Project will design, develop and validate a flexible software platform for an important kind of knowledge management: to assist organisationally mobile workers at middle and higher levels of public sector organisation.
COMMunity-based Interoperability Utility for SMEs (Commius)
Podpora Interoperability pre MSP založená na ISU
Annotation: Commius aims to deliver an adaptable and customisable software prototype, providing SMEs with zero-cost of entry into interoperability using the ideas behind the Interoperability Service Utility.
PROviding Computing solutions for ExaScale challengeS (PROCESS)
Poskytovanie výpočtových riešení pre výzvy v oblasti ExaScale
Annotation: The PROCESS demonstrators will pave the way towards exascale data services that will accelerate innovation and maximise the benefits of these emerging data solutions. The main tangible outputs of PROCESS are five very large data service prototypes, implemented using a mature, modular, generalizable open source solution for user friendly exascale data. The services will be thoroughly validated in real-world settings, both in scientific research and in industry pilot deployments. To achieve these ambitious objectives, the project consortium brings together the key players in the new data-driven ecosystem: top-level HPC and big data centres, communities – such as Square Kilometre Array (SKA) project – with unique data challenges that the current solutions are unable to meet and experienced e-Infrastructure solution providers with an extensive track record of rapid application development. In addition to providing the service prototypes that can cope with very large data, PROCESS addresses the work programme goals by using the tools and services with heterogeneous use cases, including medical informatics, airline revenue management and open data for global disaster risk reduction. This diversity of user communities ensures that in addition to supporting communities that push the envelope, the solutions will also ease the learning curve for broadest possible range of user communities. In addition, the chosen open source strategy maximises the potential for uptake and reuse, together with mature software engineering practices that minimise the efforts needed to set up and maintain services based on the PROCESS software releases.
Flood Forecasting Computed on Grid Infrastructures
Predpoved povodní pomocou počítania na gridových infraštruktúrach
Annotation: no description
Dissemination and Exploitation GRids in Earth sciencE (DEGREE)
Rozšírenie a využitie gridov vo vede o Zemi
Annotation: DEGREE is a Specific Support Action (SSA) project which aims to promote GRID throughout a large and diverse Earth Science (ES) community, in order to increase the awareness and uptake of GRID technology and infrastructure by EU Earth Science Industry and Research communities.
Social Network of Machines (SOON)
Sociálna sieť strojov
Annotation: This project proposes to investigate the impact of the use of autonomous social agents to optimise manufacturing process in the framework of Industry 4.0. Social means that cyber-physical entities will act autonomously in order to optimize an industrial process following behaviour models inspired by human social networks. Currently, in Industry 4.0, smart entities do exist. However, intelligence is localised and intelligent heterogeneous entities cannot communicate together even inside the same shop-floor. Our motivation comes from the observation that, if we want to create a real Internet of Everything that brings together processes, data, things, and people, all these entities have to be connected and follow a shared, easy to understand paradigm.In this project, we propose a holistic multi-agent paradigm that encompasses machines and humans. The presence of human operators is therefore crucial both to teach to and to learn from software agents, via deep learning and data mining algorithms. Agents will take decisions merging and analysing big and heterogeneous data produced by sensors (vibration, temperature, etc.), automation and information systems (such as enterprise resource planning and manufacturing execution system), and humans in real-time.The design and evaluation of the SOON system will be performed through predictive maintenance scenarios in collaboration with three different industrial companies (in Slovakia, Spain and Switzerland). Such collaboration will enable the project consortium to assess the concrete improvement on specific industrial processes. As application scenario, the project will focus on the predictive maintenance tasks. We believe that the arrival of Industry 4.0 revolution combined with recent improvements in machine learning, and the application of autonomous multi-agent architecture can finally bring disruptive innovation in industrial process optimization and modelling.
Enabling Grids for E-Science in Europe (EGEE)
Sprístupnenie Gridu pre e-vedu v Európe
Annotation: no description
Enabling Grids for E-sciencE II (EGEE II)
Sprístupnenie Gridu pre e-vedu v Európe II
Annotation: The EGEE project brings together experts from over 27 countries with the common aim of building on recent advances in Grid technology and developing a service Grid infrastructure which is available to scientists 24 hours-a-day.The project aims to provide researchers in academia and industry with access to major computing resources, independent of their geographic location. The EGEE project will also focus on attracting a wide range of new users to the Grid.
Stimulation of European Industry through High Performance Computing, EU Copernicus Network (SEIHPC)
Stimulácia európskeho priemyslu pomocou vysokovýkonného počítania , EU Copernicus sieťový projekt
Annotation: Program: IC-PECO/COPERNICUSThe objective of this concerted action is the provision of a mechanism whereby high performance computing (HPC) skills, tools and experience can be transferred across Europe and the emerging economies of Eastern Europe and the NIS.Technology transfer takes place between the steering group, who have HPC skills and experience, and new members through one-to-one contact and workshops. Experiences in the one-to-one contacts, as well as presentations of relevance to HPC, will be discussed at the workshops, which will be held in January 1996 in Portugal and in September 1996 in Hungary.European links:The network will provide a tightly coupled outlet for the major developments made in HPC by the steering group members in the two Copernicus projects Software Engineering for Parallel Processing (SEPP) and High Performance Computing Tools for Industry (HPCTI).INFORMATION DISSEMINATION ACTIVITIES AND EXPLOITATIONThe major activities in this concerted action arevisits of new members to members of the steering group a reporting mechanism to assess the impact of HPC two major workshops.
Emergency Responder Data Interoperability Network (REDIRNET)
Systém pre dátovú interoperabilitu záchranných zložiek
Annotation: Over the past 5 years the majority of the REDIRNET consortia have participated in Projects SECRICOM and FREESIC;this has involved partners engaging significantly with a wide range of public safety officers across the EU. A benefit of thisengagement has been the recognition that in addition to agency interoperability of communications a pressing need existsfor agency interoperability of additional IT systems such as databases, sensor systems and cameras. REDIRNET providesa framework for addressing this need with detailed mapping of user preferences and related legal requirements usinginnovative technologies.The consortium is aware that frequently it is non-technical issues that hinder agency interoperability regardless of the qualityof technical solutions. Consequently user engagement across a range of agencies EU-wide will be ongoing throughout theduration of REDIRNET. This will lead to the first of two elements of the REDIRNET framework - a quality repository of useridentified interoperability issues and proposals for their resolutionThe second element of REDIRNET will be technology. REDIRNET will provide a decentralized framework for interoperabilityfor first responders’ systems based on a public meta-data gateway controlled by the agencies themselves via a REDIRNETsocio-professional web. Agencies will be able link up to partner agencies of their choice and operational need; they will alsobe able to manage the scope of such interoperability. To help set up these link-up arrangements REDIRNET will be enhancedwith semantic web methods in accordance with the vocabulary and processes of the user community. Inter-operatingagencies will need only to develop one gateway (to REDIRNET) leading to a cost effective solution; agent technologies willalso be developed to facilitate the integration of user systems into REDIRNET.
Virtual Enterprises by Networked Interoperability Services (VENIS)
Virtuálne podniky zosieťované navzájom prepojenými službami
Annotation: The VENIS project is aimed at bridging the gap of interoperability between Large and Medium-Small-MicroEnterprises, according to the “Virtual Organisation” paradigm:- a distributed and secure repository to share the information contained in the file systems, databases, ERPs,CRMs, and other legacy applications of the enterprises, connecting the IT Infrastructures from Large to Microenterprises;- a set of lightweight web services for the smart integration of the information exchanged in joint works, based onlegacy email systems and boosted by semantic annotations and search;- a distributed processes engine mechanism, able to link and execute the enterprises business processes, toassist the work in joint businesses and to create novel synergies in products supply chains.Latest documents and multimedia, meeting planning, joint work flow and milestones, etc. will be then easilyavailable to all the persons involved both from Large to Micro enterprises, while leaving almost unchanged thealready existing legacy procedures.The Consortium, composed by 7 Partners skilled in international collaboration, is well balanced in expertisebetween technology developers and final users. The VENIS results will be disseminated on the Web and inInternational Conferences, thanks to the creation of a VENIS Community of users,Boosted by VENIS, the involved Enterprises expect to improve their competitive edge in joint projects, byexploiting the project results in their joint business and towards external market, bringing an estimated 15-20%increase of business during the 3 years following the end of the project.
Engaging the EGI Community towards an Open Science Commons (EGI-Engage)
Zapojenie EGI spoločenstva smerom k otvorenej vede
Annotation: EGI-Engage will accelerate advancements within the European Grid Infrastructure (EGI) in strategy, policy, business and technical innovation, user engagement towards researchers within the long-tail of science, domain-specific research communities, Research Infrastructures (RIs) within the ESFRI roadmap, as well as SMEs and industry at large.Accelerated Computing in Cloud is being the IISAS role in this project, i.e. integrating GPGPU accelerators into the computing infrastructure EGI.
Knowledge-based Workflow System for Grid Applications (K-WfGrid)
Znalostná konštrukcia toku práce v Gridových aplikáciách
Annotation: Project K-Wf_Grid addresses the need for a better infrastructure for the future Grid environment. In order to address the complexity in using and controlling the next generation Grid, the K-Wf_Grid consortium will adopt the approaches envisioned by semantic Web and Grid communities in a novel, generic infrastructure, to assist its users in composing powerful Grid workflows by means of a rule-based expert system.
Adaptive Interoperability Framework for Private and Public Sector (AIIA)
Adaptívna platforma na podporu interoperability v súkromnom a verejnom sektore
Annotation: Existing interoperability solutions are suitable only for large enterprises and lack of cheap, easy to integrate and easy to customize solutions. We believe such solution need to be build above existing ICT infrastructure (email, web) available in most of enterprises and organizations. We propose to build interoperability solution on top of email communication. Email communication is used in most of enterprises on daily bases to acomplish interoperability tasks manualy. We believe that such approach for interoperability can have significant impact by not forcing users to change working tool (they can stay with email), by delivering interoperability solution above existing ICT and by providing tool which can be easily customize for concrete application.AIIA can be used also in eGovernment, by solving interoperability problem among different governmental offices. This is especially true in countries as Slovakia, where public bodies have basic ICT infrastructure as email and web but lack of interoperability solutions and thus people need to act as interoperability layer by bringing stamped papers from one office to another.
Efficient tools and mechanisms for grid computing
Efektívne nástroje a mechanizmy pre gridové čítanie
Annotation: Computational Grids are facing a rapid development in the recent time. Although the main domain of their use is in the fields of science and research, computing capacity providing by grids also attracts commercial organizations from industry, finance or medicine. However, there are many areas in grid computing that need to be improved in order to use grid efficiently: security, workflow, data management. The aim of this project is to analyze and propose improvement of the basic features and to create tools for efficient use of grid computing
Intelligent methods for large scale information processing
Inteligentné metódy pre spracovanie rozsiahlych informačných zdrojov
Annotation: At present the amount of information available in digital form is increasing steadily. However, increasing volumeresults in so-called information overload – i.e. much information is available which we are unable to sort, integrateor retrieve adequately. The largest group of digital data is that created by humans, such as text, documents,pictures, videos. The onset of web 2.0 applications and of electronization of banking or travel transactions resultsin generating huge amount of data. However, data generated in the above manner contain much information,primarily about links among real world and digital objects, but this valuable information is hard to find in the hugevolumes of available data. The project handles research and development of such methods which would makethis partially possible. Simultaneously, the project is aimed at analysis, creation and verification of suchinformation processing methods and algorithms which are able to process, manage, retrieve and accessinformation large scale.
Intelligent Cloud Workflow Management for Dynamic Metric- Optimized Application Deployment (ICONTROL)
Inteligentné riadenie tokov práce v cloude pre dynamické a metrikami optimalizované nasadzovanie aplikácií
Annotation: ICONTROL is a platform for dynamic and intelligent function-based workflow application deployment and run-timeredeployment in hybrid edge cloud computing environments.ICONTROL will automatically construct and deploy complex workflow-based cloud applications in an end-to-endmanner. ICONTROL will use semantic information on available cloud-based application functionalities toautomatically generate complex workflows of functions, which will be executed across edge and cloud resources. Itwill help users to automate function selection, configuration and deployment, dealing with run-time failure orperformance issues through automated redeployment. To remove obstacles for non-cloud expert users to usecomplex function-based workflow applications, ICONTROL will support a separation of tasks among 3 categories ofspecialists. Cloud application developers will develop application and backend functions, semantically annotate anddescribe them. AI-powering algorithms will assist domain application experts to create application workflows usingfunctionalities provided by the cloud application developers, with semi-automated workflow construction techniquesby leveraging semantic descriptions. Application users will be able to usetheir application workflows to instantiate, deploy and run their applications using the automation capabilities of theproposed system in complex hybrid edge and cloud environments, not burdened by complexities related toworkflows selection, application deployment, fault resolution, resource elasticity provision, to name just a few.ICONTROL will significantly improve composability and adaptability of workflow-based applications spanning theentire edge-cloud continuum (from remote wireless IoT sensors, through personal devices, to large computingcenters), by creating a semantically-enriched, platform-agnostic, and secured FaaS workflow development andexecution platform, with automatic infrastructure resource management and provisioning.
Intelligent technologies for knowlege oriented organizations
Inteligentné technológie pre znalostne orientované organizácie
Annotation: An important aspect in building knowledge economy is an ability of organizations to assess their knowledge capital. Technologies and knowledge are becoming a key factor in productivity growth. This is the reason why companies support knowledge management projects in their organizations and strive to use their knowledge management to the largest possible extent. The objective of the project is to support companies heading towards the knowledge economy by extending existing and creating new models, algorithms, technologies and tools that can help organizations in their transition to a knowledge oriented corporation. Such transition should be preceded by an analysis and processing of information resources in organizations including documents, electronic communication and databases in an effect to manage and create availability and sharing of relevant information and knowledge. The project focuses in particular on the areas of knowledge modeling, service oriented architectures, distributed knowledge bases, semantic annotation, knowledge mining, case based reasoning and statistical methods. Special attention is devoted to processing of information resources in the Slovak language, where techniques based on neural networks and ontologies will be used.
Methods and algorithms for the semantic processing of Big Data in distributed computing environment
Metódy a algoritmy pre sémantické spracovanie veľkých dát v distribuovanom výpočtovom prostredí
Annotation: The research proposed in this project follows up on the successes achived in 7th FP projects in which most of the research team has participated: ADMIRE: Advanced Data Mining and Integration Research for Europe (2008-2011), Commius : Community-based Interoperability Utility for SMEs (2008-2011), VENIS: Virtual Enterprises by Networked Interoperability Services (2011-2015) and EGI-InSPIRE: Integrated Sustainable Pan-European Infrastructure for Researchers in Europe (2010-2014). Several case studies from these projects have created the motivation for research in the area of semantic processing of Big Data in a virtual computational environment. A big challenge in the proposed project will be to study new methods, approaches and algorithms. The proposal also builds on two previous VEGA projects: Selected methods, approaches and tools for distributed computing (2012-2015) and New methods and approaches on information processing and knowledge bases (2013-2015).
New Methods and Approaches for Distributed Scalable Computing
Nové metódy a prístupy pre distribuované škálované počítanie
Annotation: Nowadays, there is a growing number of heterogeneous data from distributed sources, which brings great challenges to extract valuable knowledge from them. Current solutions are computationally-intensive modeling and simulations in a variety of science, industry and commercial areas through machine learning, neural networks, and deep learning. Due to the extremely multi-faceted dynamic data it is highly necessary to design novel methodologies, robust methods and approaches for scalable analytics in conjunction with scalable data collection, processing and management. High-performance platforms also need to be upgraded with the latest cloud technology knowledge for flexible management of large-scale systems. The project will also include research and development of appropriate tools and services for distributed and scalable information processing with the support for high-performance platforms. The proposed project builds on the results achieved in the VEGA 2/0167/16 project and in the four H2020 projects.
Service-based distributed computing and data management
Servisne-orientované distribuované počítanie a dátový manažment
Annotation: Service-oriented architectures and software services as their basic building blocks are currently one of the most prominent research paradigms of distributed information systems. There is a need for novel approaches which are able to deal with and utilize the knowledge which will be available in the pervasive world of future service-oriented environment. In this environment the convergence between existing grid technologies, web services, semantic technologies and emerging service oriented architectures will enable enhanced provision of computing, data, information and knowledge capabilities. The project aims at surveying the following selected topics: exploitation of semantics in service oriented environment, use of services in Grid, use of services in data management and visualization of service oriented scientific computation in Grid. The project also aims at verifying the researched approaches on selected applications such as utilization of the service oriented Grid systems in image processing.
Urgent Computing for Exascale Data (U-COMP)
Urgentné počítanie pre Exascale dáta
Annotation: Current challenges of the European research area in computer science place emphasis on integration of research infrastructures, move to e-services, open access to data and reusability of services, data and research results. Furthermore, European infrastructures now move toward processing of Big Data and even exascale data, using novel modes of HPC such as urgent computing. The ability to use exascale systems to provide urgent decision making support critically depends on the ability of the supercomputing centers to provide urgent computing as a new use mode. We strongly believe that urgent computing must be a service provided by the future European computing centers. This will have the dual benefits of immediate delivery of societal benefits of the best performing (at any given time) systems, combined with their ability to optimize the design of the future operational centers with urgent computing capability. These challenges are best tackled by merging web services as the premier e-service paradigm, semantic web technologies for ease of data discovery and cloud computing as a flexible deployment platform. We would like to help to further our understanding of the e-service composition and orchestration challenges when done on a massive scale, and to allow the operators and users of e-services to truly enter the era of Cloud Computing by providing methodology, architecture, tools and standards which will make it easier, safer, and also less expensive to adopt true Cloud Computing and distributed service-oriented applications en masse. Thus we have chosen four research domains which we want to target in this proposal:• composition and orchestration of e-service processes with support of urgent computing;• use of semantic web technologies in describing the services and domain components of the processes;• interoperability of cloud environments and HPC resources and their compatibility with urgent computing;• scalable and distributed aggregation and analysis of data
Selected methods, approaches and tools for distributed computing.
Vybrané metody, prístupy a nástroje pre distribuované spracovanie informácií.
Annotation: Distributed processing of information currently represents an important research area in the European Research Area, which is a part of the European research programs. The proposed project focuses on original solutions in 4 research objectives.1. Research in methods, approaches and algorithms for distributed information and data mining in multidimensional data.2. Innovative architectures and approaches for coordinated information gathering from heterogeneous sources and management of distributed resources using agents.3. New methods and techniques for management of distributed data and metadata in state-of-the-art service-oriented environments.4. Research on parallel and distributed computing, with emphasis on porting applications to the Cloud environment, as well as solving interoperability between different Clouds.
PFO-CAD CP93: 7896 - Copernicus program - Geometric Modeling for CIM-oriented Virtual Reality
PFO-CAD CP93: 7896 - Copernicus program - Geometric Modeling for CIM-oriented Virtual Reality
Annotation: Geometric Modeling for CIM-oriented Virtual Reality - PFO-CAD CP93: 7896
Leader from the Institute of Control Theory and Robotics SAS was Doc. RNDr. Jaroslav Fogel, CSc.;
J. Sebestyénová put info on the project into system ELVYS; co-researchers of the project from ICTR SAS (since 2004 part of Institute of Informatics SAS) were: J. Fogel, P. Kurdel, K. Dobrovodský, J. Sebestyénová
CSG Modelling is part of almost all CAD-systems for the modelling of solid state matter. Numerous theoretical investigations and implementations have been carried out. Besides its advantages CGS models need still to be modified into envelope representations for many applications. Parametrizing and real time capabilities are getting lost by this process.
European links: The project will run in strict conjunction with CP93-9554 DODECAS
The Modelling will be made capable of real time by focussing on a subset of CSG Models. Generic storage in databases will be established by using appropriate canonization of representations. Deductive retrieval of variants will be eased substantially.
Title of the task solved by colective from our Institute: Fast matching algorithm for protein graphs