HPCLAB is currently participating in four EC funded H2020 projects.
ACCORDION (H2020 RIA 2020-2023 contract N. 871793) aspires to support the enlargement of the edge resource & infrastructure pool so as to cover morgeographies and users, thus truly enabling ubiquitous and collaborative applications that will benefit from the edge computing offerings.
A system will be created, called ACCORDION system, that will address the needs of both NextGen application developers and local infrastructure owners, and will encompass frameworks for application development, establishment of an adaptive and robust cloud/edge infrastructure continuum, and the abstraction of widely heterogeneous pools.
MASTER (H2020-MSCA-RISE-2017 2018-2022 – contract N. 777695) is a EC funded under the H2020 Marie-Slodowska Curie actions as the RISE funding scheme. The objective is to form an international and inter-sectoral network of organisations working on a joint research programme to define new methods to build, manage and analyse multiple aspects semantic trajectories. We propose methods to analyze and infer knowledge from multiple aspects trajectories, considering as vital issues the privacy and big data dimensions.
HPC Lab is the coordinator of the project and its main role is in developing efficient methods for trajectories representation, management and analysis.
SoBigData++ (H2020 RI, 2020-2023 contract N. 871042) strives to deliver a distributed, Pan-European, multi-disciplinary research infrastructure for big social data analytics, coupled with the consolidation of a cross-disciplinary European research community, aimed at using social mining and big data to understand the complexity of our contemporary, globally-interconnected society. Becoming an advanced community, SoBigData++ will strengthen its tools and services to empower researchers and innovators through a platform for the design and execution of large-scale social mining experiments. It will be open to users with diverse background, accessible on project cloud (aligned with EOSC) and also exploiting supercomputing facilities.
The BigDataGrapes project (H2020 PPP RIA, 2018-2021 contract N. 780751) aims at building knowledge and methodologies to support companies in the grapevine industry when making important decisions by exploiting complex and heterogeneous data sources modelled using RDF.
HPC Lab is responsible for providing the consortium with an efficient and scalable platform supporting effective management and prediction methods to address the volume and the complexity of the data, with concise and fast data structures for indexing and searching huge RDF repositories, and with robust methodologies for the experimental assessment of the BigDataGrapes software stack.
TEACHING (H2020 RIA 2020 – 2022 contract N. 871385) addresses the challenge by integrating AI with fundamental concepts of security and dependability stemming from the AI-human-CPSoS interactions, as well as by considering their impact on the underlying computing system. TEACHING develops a human-aware CPSoS for autonomous safety-critical applications, based on a distributed, energy-efficient and dependable AI, leveraging edge computing platforms, and integrating specialized computing fabric for AI and in-silico support for intelligent cybersecurity.
HPCLab leads WP2 (Distributed Computing and Communication platform for CPSoS) and is responsible of the innovation coordination for the whole project.
HPCLAB is also involved in the National project OK-INSAID (Operational Knowledge from Insights and Analytics on Industrial Data, PON e FSC – Fabbrica Intelligente – n. ARS01_00917) funded by the Ministero dell’Istruzione, Università e Ricerca (MIUR).
Some of the projects recently concluded are listed below