1. Primary Research Team & Capabilities
URL:
Institute of Informatics, Slovak Academy of Sciences
Department of Parallel and Distributed Computing
Research and Development Areas:
Large-scale HPC, Grid and MapReduce applications
Intelligent and Knowledge oriented Technologies
Experience from IST:
3 project in FP5: ANFAS, CrosGRID, Pellucid
6 project in FP6: EGEE II, K-Wf Grid, DEGREE (coordinator), EGEE, int.eu.grid, MEDIGRID
7 projects in FP7: Commius, Admire, Secricom, EGEE III EGI-InSPIRE, Venis
4 projects in H2020: EGI-Engage, EOSC-hub DEEP-HybridDataCloud, PROCESS
Several National Projects (SPVV, VEGA, APVT)
Intelligent Knowledge Technology Group focus:
Information Processing (Large Scale)
Graph Processing
Information Extraction and Retrieval
Semantic Web - Knowledge oriented Technologies
Parallel and Distributed Information Processing
Solutions:
SGDB: Simple Graph Database
gSemSearch: Graph based Semantic Search
Ontea: Pattern-based Semantic Annotation
ACoMA: KM tool in
EMBET: Recommendation System
Experts on MapReduce and IR (Nutch, Solr, Lucene)
Director & leader of PDC:
Dr. Ladislav Hluchý
PROCESS Kick-off meeting
20-21 November 2017

2. Research Topics
High performance and distributed computing and information processing
Big Data oriented technology
Data analytics, Data mining
Machine Learning
Semantic, Ontology, Taxonomy
Natural Language Processing
Knowledge base and modeling
Artificial Intelligence
Reasoning and Inference
Semantic search, graph and network
Information Retrieval
Mobile and IoT computing
Communication technologies
Multi-agent systems
Infrastructures
PROCESS Kick-off meeting
20-21 November 2017

3. Large scale Text and Graph data processing
Web Crawling
Apache Nutch + Plugins
Information Retrieval
Full-text search
Nutch, Lucene, Sorl
Natural Language Processing
Stanford Core NLP, Cognitive Computation Group, NLP Tools, GATE, Ontea
Large-scale Data Processing
Hadoop, Spark, Hive, Pig, S4, HBase
Graph processing and Querying
Simple Graph Database (SGDB), gSemSearch, Neo4j, Blueprints
Machine Learning
VW, Weka
PROCESS Kick-off meeting
20-21 November 2017

4. Related projects in FP7 and H2020

5. K-Wf Grid Project Semantic Service Oriented Architecture
Workflows of Web Services
PROCESS Kick-off meeting
20-21 November 2017

6. EGI-Inspire
EGI-Inspire: Integrated Sustainable Pan-European Infrastructure for Researchers in Europe, FP , ( )
Collaborative effort involving more than 50 institutions in over 40 countries
Provide sustain support for Grids of HPC/HTC, while seeking to integrate new Distributed Computing Infrastructures (DCIs), i.e. Clouds, SuperComputing, Desktop Grids
IISAS in EGI-Inspire
NGI for Slovakia
Federated Cloud
Service infrastructure
PROCESS Kick-off meeting
20-21 November 2017

7. ADMIRE (Advanced Data Mining and Integration Research for Europe)
7FP programme, ICT priority, 2008/03 – 2011/02, 6 institutions from EU
Accelerate access to and increase the benefits from data exploitation;
Deliver consistent and easy to use technology for extracting information and knowledge;
Cope with complexity, distribution, change and heterogeneity of services, data, and processes, through abstract view of data mining and integration; and
Provide power to users and developers of data mining and integration processes
IISAS’s role
Environmental data- specific methods for data integration
Tools applying knowledge management to data mining in SOA environment
Pilot application, user interface
PROCESS Kick-off meeting
20-21 November 2017

8. EGI-Engage project
EGI-Engage: Engaging the Research Community towards an Open Science Commons H ( )
Collaborative effort involving more than 70 institutions in over 30 countries
Expanding the capabilities of a European backbone of federated services for compute, storage, data, communication, knowledge and expertise
Complementing community-specific capabilities

9. EGI-Engage objectives
Ensure the continued coordination of the EGI Community in strategy and policy development, engagement, technical user support and operations of the federated infrastructure in Europe and worldwide.
Evolve the EGI Solutions, related business models and access policies for different target groups aiming at an increased sustainability of these outside of project funding
Offer and expand an e-Infrastructure Commons solution
Promote the adoption of the current EGI services and extend them with new capabilities through user co-development

10. EGI Federated Cloud Federated multi-national cloud system
Integrates community, private and public clouds into a scalable computing platform for research
Offers a federation pools IaaS, PaaS and SaaS services
Uses single authentication and authorization framework
IISAS actively participated into EGI Federated cloud activity with three different cloud sites

11. Accelerated Computing in EGI FedCloud
IISAS is the leader of Accelerated Computing activity in EGI-Engage
Provides accelerated computing capabilities to user communities in EGI Federated Cloud
IISAS-GPUCloud site
IISAS-Nebula
Coordinates development and user activities related to Accelerated computing
Manage Accelerated computing VO
Provide tutorials, user guides and training for using Accelerated computing
Cooperate with developers of EGI Federation Cloud to integrate Accelerated computing to the pool of Cloud services
Use Cases and Application Audience
Biodiversity and Ecosystem Research
Bioinformatics and Biomolecular simulations
Machine Learning (ML), Artificial Neural Networks (ANN) and Deep Learning (DL) applications
Life large-scale simulation packages with dynamic progress development

12. DEEP-Hybrid-DataCloud project
DEEP-Hybrid-DataCloud: Designing and Enabling E-infrastructures for intensive Processing in a Hybrid DataCloud ( ) H
Partners: CSIC (Spain), LIP (Portugal), INFN (Italy), PSNC (Poland), KIT (Germany), UPV (Spain), CESNET (Czech Republic), IISAS (Slovakia), ATOS (Spain), HMGU (Germany)
to support intensive computing techniques that require specialized HPC hardware, like GPUs or low latency interconnects, to explore very large datasets
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

13. DEEP-Hybrid-DataCloud architecture
Very large datasets
Deep learning framework
Hybrid Cloud
Specialized hardware and systems

14. IISAS roles in DEEP-Hybrid-DataCloud
WP leader for Accelerated and HPC Computing in Cloud
To develop on existing cloud middleware to provide bare-metal like performance
To provide access to accelerators (GPU, FPGA) via all software layers to applications
To create a seamless access to HPC resources from PaaS level

15. IISAS roles in DEEP-Hybrid-DataCloud
DEEP as a Service
To create basic building blocks for Deep learning and Big data analytics
To compose building blocks according to application requirements
To deploy and provide DEEP as a service
Use case
analysis of massive online event streams in order to generate alerts with hard realtime constraints.

16. PROviding Computing solutions for ExaScale challengeS
PROCESS
PROviding Computing solutions for ExaScale challengeS
Call: H2020-EINFRA e-Infrastructures
Topic: EINFRA Platform-driven e-infrastructure innovation

17. PROCESS Goals
PROCESS will deliver a comprehensive set of mature services prototypes and tools specially developed to enable extreme scale data processing in both scientific research and advanced industry settings.
PROCESS will provide services to three communities with exceptional requirements in terms of data processing
The PROCESS demonstrators will pave the way towards exascale data services that will accelerate innovation and maximise the benefits of the emerging “very large data” solutions. The main tangible outputs of PROCESS are five data services prototypes, implemented using a mature, modular, and generalizable open source solution for user friendly exascale data. The services are thoroughly validated in real-world settings: in scientific research, in industry pilot deployments, and in open data service pilot targeting also general public

18. PROCESS Partners Ludwig-Maximilians-Universität München - Germany
Universiteit van Amsterdam - Netherlands
Netherlands eScience Center - Netherlands
Haute Ecole Spécialisée de Suisse Occidentale - Switzerland
Lufthansa Systems GmbH & Co. KG - Germany
Inmark Europa SA - Spain
Ústav informatiky, Slovenská akadémia vied - Slovakia
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie - Poland

19. PROCESS UISAV Role
Leader of JRA1 – Design and Architecture. Responsibility for design, implementation and validation of a novel SoA architecture for exascale data management and processing.
Leader of JRA4 - Service Orchestration and User Interfaces. Responsible for the development and deployment of the service orchestration infrastructure as well as the user interface and collaboration tools.
One of principal designers of PROCESS data services
Active in JRA3 - Extreme Large Computing Service-oriented Infrastructure ,developing services for Big Data manipulation and processing
Active in JRA2, integrating data management with service orchestration
Will participate in dissemination and exploitation

20. PROCESS Architecture

21. EOSC-hub Integrating and managing services for the European Open Science Cloud
09 January, EOSC-hub Kickoff
Tiziana Ferrari/EOSC-hub Project Coordinator

22. EOSC-hub mobilises providers from 20 major digital infrastructures, EGI, EUDAT CDI and INDIGO-DataCloud jointly offering services, software and data for advanced data-driven research and innovation.
7/25/2019

23. 100 Partners, 76 beneficiaries (75 funded)
Project figures
100 Partners, 76 beneficiaries (75 funded)
3874 PMs, 108 FTEs, more than 150 technical and scientific staff involved
€33,331,18 of which the European Commission funds €30,000,000
€2,155,540 (~8 FTEs) are co-funded by the EGI Foundation and its participants + €1,221,094 (~5 FTEs) from EGI participants
36 months: Jan 2018 – Dec 2020 (18 month reporting period)
7/25/2019

24. Mission
The project will create the Hub a federated integration and management system for the future EOSC
Resources and Services
Federation “core” services
Federated operations
Processes and policies
7/25/2019

25. What does the Hub provide?
Contact point for researchers and innovators to discover, access, use and reuse a broad spectrum of resources for advanced data-driven research
Catalogue of resources and services
Humanities, Engineering, Medical and Health Sciences, Natural Sciences
Corpus of policies, processes and federation services (community-defined)
Principles of engagement and EOSC “core” services
Quality assurance reviews
Manage end-to-end service level management performance
Competence Centres and a Joint Digital Innovation Hub
Specialized Technical support, training
7/25/2019

26. The Hub and the Three Os Open Science Open Innovation
Resources and services for sharing, discovery access, use and reuse
Collaboration with OpenAIRE-Advance
Open Innovation
A open collaborative effort of service providers and user communities
Co-design of process with Competence Centres and a Joint Digital Innovation hub
Open to the world
Aggregates services from local, regional and national e-Infrastructures in Europe and other regions of the world
7/25/2019

27. From integration to utilization
Integrate production-ready services
Operate and Provide
Access and Consume
7/25/2019

28. Architecture
7/25/2019

29. Work packages
7/25/2019

30. Service Integration and Access Management
7/25/2019

31. Service Providers 1/2 e-Infra Humanities Engineering
EGI Federation
EUDAT CDI
Humanities
Language and literature (CLARIN)
Arts (DARIAH)
Engineering
Environmental engineering (sea vessels, LNEC)
Civil Engineering (Disaster Mitigation)
Medical and Health Sciences
Biological Sciences (ELIXIR)
Structural biology (WeNMR)
7/25/2019

32. Natural Sciences Service Providers 2/2 Physical Sciences
Astronomy (LOFAR)
Fusion (ITER)
High Energy Physics (CMS and VIRGO)
Space Science (EISCAT-3D)
Earth Science
EO Pillar
GEO
Climate Research (ENES)
Seismology (ORFEUS, EPOS)
Biological Sciences
Marine and freshwater biology (IFREMER)
Biodiversity conservation (LifeWatch)
Ecology (ICOS)
7/25/2019

33. EOSC Domains and the Hub: what model?
7/25/2019

34. IISAS roles in EOSC-Hub
Continues the research and development activities from EGI-Engage project:
To participate in Federated computing activities: Federated cloud, DNS as a service
To provide Accelerated computing capabilities to scientific communities
To provide training, guides and user supports related to Accelerated computing