Projects

Heterogeneous and distributed systems are increasingly used today to speed up the solution of complex computational tasks and to solve previously unsolvable problems. Today's trend shows that of the 500 most powerful supercomputers in the world, 133 are already heterogeneous, meaning that in addition to traditional processors (CPUs), they are equipped with various accelerators, today's most popular graphics processing units (GPUs). It is expected that the future exascale supercomputers, i.e. computers that can perform more than 10^18 operations per second, will also be based on accelerators. Due to their large heterogeneity, the development of efficient and scalable algorithms and applications that achieve high utilisation of such systems is of utmost importance. The aim of this project is to develop new and improve existing computational methods and algorithms of numerical linear algebra that are able to exploit large heterogeneous systems while achieving very high performance. The main directions of the research are: increasing the scalability of the algorithms (increasing the problem size and the number of computational resources), reducing the communication overhead and exploiting the complex memory hierarchies of the heterogeneous systems, In addition, new models for optimising the parameters of algorithms with respect to the architecture of the underlying computer systems and problem size are being explored in order to reduce the overall execution time, the research results obtained will be used in solving large-scale, real-world computational problems in other scientific fields such as computational chemistry, materials physics and molecular medicine. The project will contribute to the efficient parallelisation and optimisation of algorithms for future heterogeneous and distributed systems and will strengthen research in high-performance computing at the Ruđer Bošković Institute and in the Republic of Croatia.

The mission of EuroCC 2 is to continue the establishment of a network of National Centres of Competence (NCC) in the most efficient way, while continuing to address the differences in the maturity of HPC deployment in Europe, for which improvement has already been noted. Therefore, in addition to high-level management to monitor progress in the NCCs’ development, the main task of the overall activity is to support national centres in setting up their individual operational frameworks, while accessing and making the most of the experience and expertise currently available at national and European level. To support this, EuroCC 2 will work closely with CASTIEL 2, which is tailored to the needs of the EuroCC (2) NCCs and this time will also involve the Centres of Excellence. The EuroCC activities—with 32 member and associated countries on board—is coordinated by the High-Performance Computing Center Stuttgart (HLRS). The project aims to elevate the participating countries to a common high level in the fields of HPC, HPDA and artificial intelligence (AI). The EuroCC project has established National Competence Centres (NCCs) in the participating countries, which will be responsible for surveying and documenting the core HPC, HPDA, and AI activities and competencies in their respective countries. Ultimately, the goal is to make HPC available to different users from science, industry, public administration, and society.

The objective of the EBSI-NE consortium is to support the development and adoption of the EBSI network at the European level by increasing the number of validator nodes in the production network and the provision of support services for all relevant EBSI stakeholders. These actions will increase the robustness and maturity of the production network of EBSI, enabling the development of the prioritized EBSI cross-border use cases. The consortium is made of 24 organizations from 14 European countries including government agencies, public institutions and academia which have an extensive experience related to Distributed Ledger Technologies and past EBSI ecosystem initiatives, including the deployment of pre-production nodes. Furthermore, all consortium members that will operate an EBSI production node have received support from the European Blockchain Partnership representative of their respective countries. The establishment, deployment, and operation of the new nodes in a unified and coordinated way will enhance the performance, robustness, resilience, security, and sustainability of the production EBSI network by leveraging industry best practices and technical knowledge. Specifically, the project will result in 18 new validator nodes in the EBSI production network and 24 entities providing different support services to the EBSI ecosystem across regions. The activities included in this proposal include not only all the required tasks to deploy an EBSI production node but other voluntary actions proposed to increase performance, adoption and development of the EBSI network. This additional tasks include the integration of SIEM tools, development of tailored tests to improve robustness, creation of tools to facilitate adoption and node deployment in the future, development of framework to qualify EBSI nodes as trusted e-ledgers for eIDAS 2 as well as communication and dissemination activities to raise awareness and drive further development of EBSI.

The aim of the platform DAP is to create a democratic, trustworthy and efficient infrastructure for scholarly publishing to support the European Research Area, Open Research Europe and the Digital Europe Programme. This unique initiative brings together researchers from the Centre for Informatics and Computing at the Ruđer Bošković Institute (RBI) in Zagreb, Croatia, along with experts from NGI Trublo, Moon Code, and HashNET. The project is funded under the Horizon 2020 Programme. The DAP platform was developed in response to the many challenges researchers and academics face in scientific publishing. The goal of DAP is to give authors, researchers, and the public more control over academic knowledge and information, improve recognition of the efforts of all participants in the peer review process, and prevent breaches of research integrity. More Weight for Academic Voices Researchers around the world face numerous challenges in the traditional academic publishing process. These include lengthy and opaque peer review processes, high publication costs, and limited access to publication opportunities. These constraints often impede scientific progress and innovation and limit the dissemination of important research findings. The peer review process can take months or even years, with reviewers often exercising a disproportionate amount of control over the publication process. In addition, the high costs associated with traditional academic publishing can be prohibitive, especially for researchers with limited financial resources or those from developing countries. To address these challenges, the DAP platform has introduced a new solution. The goal of the DAP platform, which is based on blockchain technology and smart contracts, is to give authors, researchers, and the public greater control over academic knowledge and information while improving recognition of the efforts of all participants in the peer review process and preventing breaches of research integrity. The proposed architecture of DAP includes a decentralized set of rules and procedures, decentralized archiving of articles and reviews, on-demand anonymity and privacy, a decentralized open review process, and the possibility of direct publication.

The LimitX project represents a ground-breaking step in the field of computational Materials Science and aims to develop an innovative recommender system. Solving large and sparse numerical linear systems in materials science on massively parallel supercomputers is a complex endeavor that requires a delicate balance between accuracy and computational efficiency. Challenges include managing the scale and complexity of these systems, optimizing scalability on parallel architectures, and addressing real-world material complexities. Project goal The LimitX project represents a ground-breaking step in the field of computational Materials Science and aims to develop an innovative recommender system. This system aims to revolutionise the solution of large-scale sparse linear systems by accelerating and scaling the solutions of linear systems so that materials science research can be routinely performed on exascale clusters. At its core, this system relies on a two-pronged approach: first, the development of a spectral predictor system and, second, the use of an extensive database of matrices that encapsulate the essence of surrogate space in the field of materials science. The spectral predictor system is the heart of the recommendation system. It utilises deep learning techniques to predict spectral properties that are crucial for the efficient solution of linear systems. The extensive matrix dataset captures the diversity of spectral patterns that occur in material science calculations. The application of this recommender system promises to be transformative, as it enables simulations with hundreds of thousands of atoms, a feat previously unrealisable on current pre-exascale clusters. The linear scaling of DFT (density functional theory) codes such as BigDFT will enable researchers to simulate and analyse complex material systems with unprecedented accuracy and computational efficiency, opening up new horizons for scientific exploration in this field. Researchers working on the project: Davor Davidović

DNA methylation inhibitors are emerging as a promising approach in the treatment of serious diseases, including cancer, Alzheimer’s, and Parkinson’s. DNA methylation is an essential process that regulates gene expression, but abnormal methylation patterns can lead to the silencing of crucial genes involved in disease suppression. Inhibitors targeting this process aim to reverse these harmful epigenetic changes, reactivating suppressed genes and offering new therapeutic possibilities. By restoring normal gene function, DNA methylation inhibitors hold the potential to treat not only aggressive cancers but also complex neurodegenerative disorders, marking a significant step forward in personalized medicine. To continue research begun under the mentorship of Professor Željko Svedružić († April 20, 2023), a scientific team from the Center for Informatics and Computing (CIR) at the Ruđer Bošković Institute (RBI) and the University of Rijeka (UNRI) secured funding for the EHPC-BEN-2023B11-013 project on the LUMI supercomputer. This HPE Cray EX system, with 0.3091 Exaflops of power, is the third most powerful supercomputer in the world, located at the EuroHPC Center CSC in Finland. Through this EuroHPC project, the research team has been allocated a valuable 876.00 core hours, providing them with the resources needed for further exploration of the #DNA #methylation field. The research’s goal remains focused on finding new inhibitors of DNA methylation, and the results are expected to enable the development of efficient simulations of DNA structures within the millisecond timeframe. These advanced investigations not only contribute to understanding the fundamental mechanisms of DNA methylation but also open up possibilities for developing new therapeutic approaches. Scientists are particularly hopeful that their efforts will lead to the discovery of novel DNA methylation inhibitors, the application of which could have a significant impact on the treatment of serious diseases such as cancer, Alzheimer’s, Parkinson’s, and other complex pathologies. This research has the potential not only to expand our knowledge of molecular processes in the organism but also to lay the foundation for the development of targeted therapies that could revolutionize medical practice, all with a help of High-Performance Computing (HPC). CIR Scientist working on the project : Draško Tomić

When using industrial machines for additive manufacturing, heat and its dissipation to individual structural elements of the machine play one of the major roles. One of the aspects of the influence of heat is the heated working space inside the machine itself that is very important because most materials used in different industries require heated work chambers, passively or actively heated. The vision of this project is to establish and predict the impact of this heat on the structure and motion system of the machine using HPC infrastructure. The experiment is divided into 3 phases. In the first phase, a digital model of a new machine assembly will be constructed. Then, in the second phase, the first series of detailed simulations on HPC infrastructure of the heat influence and dissipation in the new machine will be performed. Finally, in the third phase, the physical machine will be assembled, based on the simulations performed in the previous step. Then, through an iterative process of HPC simulations and machine fine-tuning, the machine will be calibrated and tested. The result that can be obtained with this project allows complete control over the parameters that affect the dimensional stability of 3D printed products.

The aim of the National Competence Centers in the Framework of EuroHPC (EuroCC) project is to establish national HPC competence centers and contribute to the construction of the European HPC ecosystem. This will strengthen existing and develop new competencies in the field of high performance computing (HPC). At the same time, preconditions will be created for synergistic action on policy building, financing and resource management in three areas: HPC, analysis of large data sets on HPC resources (High Performance Data Analytics, HPDA) and artificial intelligence technology (Artificial Intelligence, AI). ). ABOUT THE PROJECT The EuroCC project will bring together the necessary expertise to establish a network of national Competence Centers for High Performance Computing in 33 Member States of the European High Performance Computing Joint Undertaking (EuroHPC JU) to provide users with a portfolio of services tailored to the relevant national needs of industry, academia and the public. administration. The High Performance Computing Competence Centers will be central hubs for coordinating national initiatives, making it easier for national users to access European HPC competencies and opportunities in different industrial sectors and industries. By establishing a network of national centers of competence for HPC, the project will contribute to the construction of the European HPC ecosystem and the implementation of the HPC initiative of the European Commission.

The development of Industrial 3D printing platforms is transforming manufacturing through Cloud-HPC integration, enabling advanced production technologies. The 3D Clothing Production by Additive Manufacturing (3D CPAM) experiment introduces a flexible and fully programmable production process but faces efficiency challenges due to the time required to produce a single item, such as a jacket. To address this, 3D CPAM optimizes the design-to-manufacturing process by combining modern 3D printing with HPC/Cloud services to reduce production time. This approach overcomes size and time constraints, leveraging a Digital Factory Concept for faster, more efficient garment production. The project aims to streamline the supply chain, reducing steps and lowering costs.

TETRAMAX is a Horizon 2020 innovation action and provides an implementation of the European Smart Anything Everywhere (SAE) initiative in the domain of customized and low-energy computing for cyber physical systems and the internet of things. The total budget of the TETRAMAX project is 7M€ and is coordinated by RWTH Aachen University, with 23 partners, covering almost all EU countries. The project partially builds on experiences with the TETRACOM project during 2013-2016. TETRAMAX was launched in Sep 2017 and will run for four years. TETRAMAX and "HeartStep" experiment The first call has already closed some time ago, but the withdrawal of another experiment has made room for ‘HeartStep’ to step in and receive financial support of €42.005. HeartStep is a TTX between Ruđer Bošković Institute / Centre for informatics and computing, a Croatian research institute and SAVING trgovina in storitve d.o.o a company in Slovenia. Together they are working on the improvement of a smart body gadget monitoring the heart, which saves time in the diagnosis of heart patients and is already used in many clinics in Slovenia and the rest of the EU.

EOSC-hub unites multiple service providers into a single Hub, offering European researchers easy access to a wide range of resources for data-driven research. It enhances access to services for scientific discovery and collaboration across disciplines and regions, involving providers from the EGI Federation, EUDAT CDI, INDIGO-DataCloud, and other major European research infrastructures to deliver a unified catalogue of data, services, and software. The project aims to simplify access to a broad range of products, resources, and services through an integrated service catalogue, eliminating fragmentation in service provisioning by ensuring interoperability of compute, storage, data, and software platforms. It seeks to expand e-infrastructure capacity, improve service quality, and widen access to researchers, educators, and businesses, while growing the user base. Additionally, the project will establish a knowledge hub and enhance the innovation potential of research e-infrastructures.