GraphSys'23
2023-04-13 08:00 - 17:00 UTC
GraphSys’23

The First Workshop on Serverless, Extreme-Scale, and Sustainable Graph Processing Systems Co-located with ICPE 2023.

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Graphs and GraphSys
The use, interoperability, and analytical exploitation of graph data are essential for modern digital economies. Today, thousands of computational methods (algorithms) and findable, accessible, interoperable, and reusable (FAIR) graph datasets exist. However, current computational capabilities lag when faced with the complex workflows involved in graph processing, the extreme scale of existing graph datasets, and the need to consider sustainability metrics in graph-processing operations. Needs are emerging for graph-processing platforms to provide multilingual information processing and reasoning based on the massive graph representation of extreme data in the form of general graphs, knowledge graphs, and property graphs. Because graph workloads and graph datasets are strongly irregular, and involve one or several big data “Vs” (e.g., volume, velocity, variability, vicissitude), the community needs to reconsider traditional approaches in performance analysis and modeling, system architectures and techniques, serverless and “as a service” operation, real-world and simulation-driven experimentation, etc., and provide new tools and instruments to address emerging challenges in graph processing.
Graphs or linked data are crucial to innovation, competition, and prosperity and establish a strategic investment in technical processing and ecosystem enablers. Graphs are universal abstractions that capture, combine, model, analyse, and process knowledge about real and digital worlds into actionable insights through item representation and interconnectedness. For societally relevant problems, graphs are extreme data that require further technological innovations to meet the needs of the European data economy. Digital graphs help pursue the United Nations Sustainable Development Goals (UN SDG) by enabling better value chains, products, and services for more profitable or green investments in the financial sector and deriving trustworthy insight for creating sustainable communities. All science, engineering, industry, economy, and society-at-large domains can leverage graph data for unique analysis and insight, but only if graph processing becomes easy-to-use, fast, scalable, and sustainable.
To facilitate the exchange of ideas and expertise in the broad field of high-performance large-scale graph processing, we organize GraphSys, the first workshop of Serverless, Extreme-Scale, and Sustainable Graph Processing Systems. GraphSys is a cross-disciplinary meeting venue focusing on the state-of-the-art and the emerging (future) graph processing systems. We invite experts and trainees in the field, across academia, industry, governance, and society, to share experience and expertise leading to a shared body of knowledge, to formulate together a vision for the field, and to engage with the topics to foster new approaches, techniques, and solutions.
Workshop format
GraphSys-2023 will be a full-day workshop with a single session (no parallel sessions). We welcome the wide community of graph processing systems, and plan to feature invited talks and presentations of papers from within and beyond the GraphMassivizer project. We also plan a panel to introduce and discuss the goals of the GraphMassivizer project and how it can contribute to the strengthening of graph processing research and community.
For more details on submissions and topics of interest, please check the call for papers.
Credits & acknowledgements
The GraphSys workshop is technically sponsored by the Graph-Massivizer project (Grant number 101093202, https://graph-massivizer.eu) funded by the Horizon Europe research and innovation program of the European Union for the period 2023-2026, which studies and aims to develop a high-performance, scalable, gender-neutral, secure, and sustainable platform for massive graph processing, and by and the Horizon 2020 DataCloud project (Grant number 101016835, https://datacloudproject.eu/)
In time, we aim to align GraphSys with the Standard Performance Evaluation Corporation (SPEC)’s Research Group (RG), and, in particular, the RG Cloud Group that is taking a broad approach, relevant for both academia and industry, to cloud benchmarking, quantitative evaluation, and experimental analysis.

Join us on April 15, 2023, 9-17 in Coimbra!

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DATA WEEK 23
2023-06-13 09:00 - 2023-06-15 18:00 | Quality Hotel Luleå, Storgatan 17, Luleå, 971 28, Sweden
Data Week 2023 is the spring gathering of the European Big Data and Data Driven AI research and innovation communities. In Data Week, the participants share knowledge and results, discuss topics of common interest, find synergies, build new collaborations and identify new challenges and recommendations. Data Week also links the communities and their results to the European policies and market needs and brings European initiatives and activities closer to local communities.
Data Week 2023 is co-organised by Big Data Value Association and the EUHubs4Data project in collaboration with the Research Institutes of Sweden (RISE). The main event of the Data Week 2023 will take place in Luleå, Sweden between 13 – 15 June 2023 with the central theme “Data Meets Infrastructure at the Edge!”

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Join us on June 13 -15, 2023, in Luleå, Sweden

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Data Science International Summer School 4th Edition
2023-07-20 - 2023-07-28 | Training Center of the Bucharest University of Economic Studies in Predeal, Romania
July 20 – 28, 2023
Predeal, Romania
Organized by Bucharest University of Economic Studies, in collaboration with the GATE Institute at Sofia University “St. Kliment Ohridski” and the projects DataCloud, enRichMyData, Graph-Massivizer, UPCAST, and InterTwino.

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Goal:
The goal of the summer school is to familiarize students with relevant state of the art topics in data science. The program will cover fundamentals of data science and focus on the following key data science topics:
Data analytics and statisticsMachine learningTime series and graph dataConversational AIData pipelines (data enrichment pipelines, machine learning pipelines)Data sharingThe program will consist of a combination of lecture-style talks introducing various data science paradigms and methods, and hands-on sessions.
The summer school aims to have a practical orientation, with Python and Jupyter Notebooks being used to exemplify many of the topics covered at the summer school.
At the end of the summer school, the students are expected to have an understanding of key paradigms used in data science and be able to practically apply them in data science projects.
Prerequisites:
Familiarity with computer programming and basic knowledge about Python, interest in working with data, enthusiasm, and willingness to learn new things!
Basic knowledge of linear algebra, probability theory, and knowledge representation would be useful, though not strictly necessary.

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Join us on July 20-28, 2023, in Predeal, Romania

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Unleashing the Power of Graph-Massivizer: Transforming Data Analysis
2023-11-29 14:00 - 15:30
Join us for the upcoming HiPEAC webinar

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This webinar will present the potential of the Graph-Massivizer project funded by Horizon Europe to boost the impact of extreme and sustainable graph processing for mitigating existing urgent societal challenges.
Current graph processing platforms do not support diverse workloads, models, languages, and algebraic frameworks. Existing specialized platforms are difficult to use by non-experts and suffer from limited portability and interoperability, leading to redundant efforts and inefficient resource and energy consumption due to vendor and platform lock-in. While synthetic data emerged as an invaluable resource overshadowing actual data for developing robust artificial intelligence analytics, graph generation remains a challenge due to extreme dimensionality and complexity. On the European scale, this practice is unsustainable and, thus, threatens the possibility of creating a climate-neutral and sustainable economy based on graph data. Making graph processing sustainable is essential but needs credible evidence. The grand vision of the Graph-Massivizer project is a technological solution, coupled with field experiments and experience-sharing, for a high-performance and sustainable graph processing of extreme data.
What can you expect
●A general overview of graph processing: why it is important and challenges.●Understanding of the Graph-Massivizer project (approach, expected results, timeline), going deeper into some specific works that could be of interest to the HIPEAC community, such as graph-processing over the computing continuum and sustainability aspects.●Showcase of one of the Graph-Massivizer use cases implementing the concept of a Green Data Center Digital Twin and some discussions around the benefits of Graph-Massivizer based on the work carried out in the other pilots (financial, automotive and foresight for environment protection)
Proposed agenda

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Session

14:00

Introduction: Objectives and overview of the webinar (Nuria de Lama, IDC)

14:05

Graph-Massivizer: a game changer in graph-processing of extreme data (Dr. Radu Prodan, Klagenfurt University, Graph-Massivizer Project Coordinator)

14:20

Unveiling A Scalable and Sustainable Serverless Graph Processing System Dr. Reza Farahani, Klagenfurt University)

14:30

Energy awareness and sustainability of massive graph processing (CINECA)

14:40

Bringing technology into Practice:
Use Case: Data Center Digital Twin for Sustainable Exascale Computing (Martin Molan, University of Bologna)

15:00

Panel discussion/Q&A session including representatives of several use cases

15:30

Closing of the webinar & next steps

REGISTER HERE

Dubrovnik Meeting: let’s share what we have learned so far!
2024-06-17 - 2024-06-21
Graph-Massivizer’s partners will soon gather at the Center for Advanced Academic Studies of the University of Zagreb to engage in crucial discussions.
The meeting will focus on assessing the project’s progress and strategizing the next steps towards finalizing the use cases and launching the integrated version of the platform.
The event will take place in Dubrovnik, thanks to the colleagues from the Jožef Stefan Institute who have decided to host the graph massivizers in the city. Dubrovnik is a true jewel of the Adriatic and has been part of the UNESCO cultural heritage since 1979.

Data Science International Summer School
2024-07-20 - 2024-07-28 | Predeal, Romania
Organized by Bucharest University of Economic Studies in collaboration with the GATE Institute at Sofia University “St. Kliment Ohridski” and the projects enRichMyData , Graph-Massivizer , UPCAST , INTEND , and InterTwino , The goal of this 5th edition of the Summer School is to familiarize participants with relevant state of the art topics in data science and artificial intelligence (AI). The program will cover fundamentals of data science and AI and focus on the following key topics: • Data analytics and statistics • Machine learning and deep learning • Large Language Models and Conversational AI • Causal AI • Time series and graph data • Data sharing • Data and AI pipelines The location where the course will be held is the beautiful town of Predeal, located in the Transylvania region in Romania, famous for its mountain landscapes and natural and historical attractions. Register here and see you in Predeal!

Graph-Massivizer at SEMANTICS 2024
2024-09-17 - 2024-09-19 | AMSTERDAM, Netherlands
20th International Conference on Semantic Systems
We are pleased to announce that Graph-Massivizer will be featured at the Semantics Conference.
We will be presenting our project outcomes through presentations and posters.
More information will be coming soon on our social media channels. Stay tuned and follow us!
Info on the Conference available here

Graph-Massivizer at EBDVF 2024
2024-10-02 - 2024-10-04 | BUDAPEST, Hungary
Graph-Massivizer’s partners will soon participate at the European Big Data Value Forum!
The European Big Data Value Forum is BDVA’s flagship event, bringing together the entire European data-driven AI research and innovation community to share knowledge, collaborate, and celebrate achievements.
This year’s event will take place from October 2nd to 4th, 2024, in Budapest, Hungary.
Graph-Massivizer will be present in network with Data Nexus Cluster and DATA 01-04 Alliance.
Get ready for some exciting Sessions featuring Graph-Massivizer! Stay in the loop and find out where you can catch us at the event!
More info HERE

Graph-Massivizer at ADRF 2024
2024-11-04 - 2024-11-05 | Eindhoven, Netherlands
The partners of Graph-Massivizer are scheduled to participate in the ADRF – AI, Data, Robotic Forum – taking place in Eindhoven, Netherlands this upcoming November.
We anticipate the opportunity to engage with you during the event.
More information can be found here

Graph-Massivizer at Gaia-X Summit 2024
2024-11-14 - 2024-11-15 | Helsinki, Finland
Empowering Global Data Spaces, Shaping Tomorrow’s Cloud Infrastructure
You may find the program here:
HERE
Get ready for another exciting event!
Stay tuned for more updates – coming your way soon!

Dagstuhl Seminar - Holistic Graph-Processing Systems: Enabling Real-World Scale and Societal Impact
2025-04-21 - 2025-04-25
In today’s digital landscape, complexity grows with increasing data volume and degree of interconnection. A suitable data abstraction is crucial for comprehending and navigating this dense network of connections.
Graph-Massivizers is taking on this challenge and playing a key role in coordinating the Seminar.
The Dagstuhl Seminar will provide a unique opportunity for encounters between these distinct communities, each addressing graph processing at scale. We aim to bring together three essential communities: distributed, parallel, and cluster computing, machine learning for, on, and with graphs, and social and information networks. We facilitate therefore a better understanding of each community’s challenges regarding graph processing, and promote a synergic relationship to shape holistic, actionable knowledge of graph processing.
We are looking forward to meeting you there in 2025!
More information can be found here
