Co-located with EuroPar 2025 (August 25-26, 2025, Dresden, Germany)
Paper Submission Deadline: May 5, 2025
Graphs and GraphSys
The use, interoperability, and analytical exploitation of graph data are essential for modern digital economies. Today, thousands of computational methods 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, 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, analyze, and enable processing knowledge about real and digital worlds to generate actionable insights through item representation and interconnectedness. For societally relevant problems, graphs further technological innovations to meet the needs of the worldwide data economy. Digital graphs could be key to pursuing 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. Every professional, scientific, and economic domain could leverage graph data to deliver higher value with unique analysis and insights, but only if graph processing becomes easy-to-use, fast, scalable, and sustainable.
GraphSys is a venue for specialists from academia and industry to discuss the state of the art of graph processing systems, from architecture to algorithms, and from performance to sustainability. Contributions focusing on graph representation of data, graph representation and processing at scale, graph processing frameworks and architectures, parallel and distributed graph processing algorithms and applications, performance and sustainability studies, and machine learning on graphs, are especially welcome. We also invite contributions covering surveys and comparative analyses. This broad mix of topics revolving around graph processing is meant to stir discussion and lead to new collaborations and research directions in the field.
Workshop format
GraphSys-2025 will be a full-day (in-person only) workshop, running a single track (i..e, no parallel sessions). We plan to feature one keynote, 6-10 paper presentations, 1-2 invited presentation(s), and one panel. We will invite submissions of full papers (12 pages), as well as work-in-progress, experience, and position papers (6 pages). We will run a thorough revision process to select the papers featured in the proceedings.