The ultimate goal of REGALE is to pave the way of next generation HPC applications to exascale systems. To accomplish this, we define an open architecture, build a prototype system and incorporate in this system appropriate sophistication in order to equip supercomputing systems with the mechanisms and policies for effective resource utilization and execution of complex applications. The REGALE architecture and prototype will be co-designed considering both state-of-the-art and next generation HPC applications, maximizing in this way its applicability.

CAPE (European Open Compute Architecture for Powerful Edge) aims to redefine the landscape of edge-cloud computing infrastructures by developing the EdgeMicroDataCenters (EMDC's) and eHPS as a 'new unit of computing' for data-dense edge environments. The project designs and showcase an innovative, open hardware platform that is dynamically composable via CXL to answer the end user needs. EMDC and eHPS provides an open high density platform for heterogeneous computing units (XPU), RISC-V architectures all based on industry-standard form factor, COM-HPC that is supported by a robust ecosystem of Original Equipment Manufacturers (OEMs) within Europe, ensuring wide accessibility and adoption. To allow end users to be digital sovereign e.g. manage the governance of data, AI models, applications deployed across an ‘edge-first’ edge to cloud continuum, CAPE will employ a cloud-agnostic overlay known as Infrastructure from Code (IfC). This innovative approach abstracts the complexities inherent in diverse cloud computing infrastructures and services, empowering software developers to deploy applications effortlessly across the edge-to-cloud continuum. This is achieved without necessitating extensive knowledge of the underlying cloud infrastructure, enabling deployments across on-premise and off-premise, public and private cloud environments with minimal complexity. CAPE's solution will be validated in 3 use cases: the management of intelligent electric energy microgrids, edge AI and satellite communications. All usecases will evaluate RISC-V (EPI) and CXL solutions. Each usecase will be evaluated on technical, economical and sustainability aspects and benchmarked against legacy hardware in local clouds against edge-optimized data centers.

EMPYREAN envisages a hyper-distributed computing paradigm, based on federations of collaborative and heterogeneous IoT devices and resources (e.g., on RISC-V) across different providers and networks. These federations, namely Associations, operate autonomously and interconnect seamlessly utilizing distributed, cognitive and dynamic AI-enabled decision-making, to balance computing tasks and data inside an Association as well as between Associations in a multi-agent manner and across central computing environments, optimizing resources and providing scalability, resiliency, energy efficiency and quality of service. An Association will constitute a trusted execution environment, while identity and data access management schemes will assure controlled access and confidentiality of data, utilizing Cluster 3 related outcomes from participating partners. EMPYREAN will also be empowered with automated tools and mechanisms for efficient data processing of AI-workloads and secure distributed edge storage. Developed technologies will also enable Associations-native application development and deployment, contributing to the entire application lifecycle and interoperability. EMPYREAN will provide open and standardized APIs, while utilizing and extending open-source platforms maintained by European companies from the consortium. EMPYREAN will demonstrate its advanced and innovative capabilities through three well-defined use cases that involve device- and data-rich applications in advanced manufacturing, smart agriculture and warehouse automation, involving AI-driven value extraction from high volume and dynamic IoT data generated by multiple sources (e.g., robots) at the edge of the network. Also, a South Korea based use case in smart factories will further showcase the benefits of the EMPYREAN’s technologies. EMPYREAN will develop its Association-based continuum through synergies with emerging IPCEI initiatives and EU bodies (e.g., GAIA-X, IDSA) by involved partners.

With exascale systems almost outside our door, we need now to turn our attention on how to make the most out of these large investments towards societal prosperity and economic growth. REGALE aspires to pave the way of next-generation HPC applications to exascale systems. To accomplish this we define an open architecture, build a prototype system and incorporate in this system appropriate sophistication in order to equip supercomputing systems with the mechanisms and policies for effective resource utilization and execution of complex applications. REGALE brings together leading supercomputing stakeholders, prestigeous academics, top European supercomputing centers and end users from five critical target sectors, covering the entire value chain in system software and applications for extreme scale technologies.

SEANERGYS creates an integrated European software solution that optimises the operation of supercomputers. In doing so, it addresses four different objectives: reducing the amount of energy used for real-world workload mixes as the primary objective, optimising resource utilisation, enhancing system throughput and reducing response time as secondary objectives. Since these objectives can conflict with each other, site-specific policies define the weights attached to each, and the SEANERGYS SW suite will tailor system operation towards the combined optimum. Possible scenarios include improving the throughput of HPC systems, generating more R&D results for a given energy budget, or produce a fixed set of R&D results with less energy, while striving to keep response times constant. The solution consists of a comprehensive monitoring infrastructure (CMI), an Artificial Intelligence data analytics system (AIDAS), and a dynamic scheduling and resource management system (DSRM). The CMI gathers data from hardware and software sensors, and correlates it with scheduler information to identify jobs that do not fully utilize allocated resources. Users receive automatic feedback on energy and resource use for each run, plus information on how to optimize these. The DAIS leverages AI models trained with a vast set of operational data of the participating HPC sites. It fingerprints resource usage patterns, predicts future job behaviour, and identifies complementary job profiles for potential co-scheduling. Finally, the DSRM utilizes these insights to develop scheduling policies that maximize resource utilization and energy efficiency, and supports jobs/applications with dynamic and adaptable resource profiles. The SEANERGYS solution will be ready for deployment up to Exascale level. To ensure production-quality, the project builds on results from European projects, the competency of well-established research groups and companies, and widely used open-source codes. These are input for an integrated software system that achieves the functionality, performance and stability needed by European HPC centres, defined by KPIs and acceptance criteria and processes established at the project start. An agile, professional software development method will leverage a modern DevOps framework and strive to provide end-to-end traceability by linking and tracking requirements, interface, functional and performance specifications, code design and development steps, and validation/verification throughout the development lifecycle. Validation/verification measures will include code reviews, automated SW quality analysis, unit and integration tests and a verification suite. The project will implement a staged testing and validation process, with functionality tests on single-nodes, scaling tests on mid-sized platforms, and finally acceptance tests on production supercomputers.