Search

The European Union (EU) initiative on the Digital Transformation of Health and Care (Digicare) aims to provide the conditions necessary for building a secure, flexible, and decentralized digital health infrastructure. Creating a European Health Research and Innovation Cloud (HRIC) within this environment should enable data sharing and analysis for health research across the EU, in compliance with data protection legislation while preserving the full trust of the participants. Such a HRIC should learn from and build on existing data infrastructures, integrate best practices, and focus on the concrete needs of the community in terms of technologies, governance, management, regulation, and ethics requirements. Here, we describe the vision and expected benefits of digital data sharing in health research activities and present a roadmap that fosters the opportunities while answering the challenges of implementing a HRIC. For this, we put forward five specific recommendations and action points to ensure that a European HRIC: i) is built on established standards and guidelines, providing cloud technologies through an open and decentralized infrastructure; ii) is developed and certified to the highest standards of interoperability and data security that can be trusted by all stakeholders; iii) is supported by a robust ethical and legal framework that is compliant with the EU General Data Protection Regulation (GDPR); iv) establishes a proper environment for the training of new generations of data and medical scientists; and v) stimulates research and innovation in transnational collaborations through public and private initiatives and partnerships funded by the EU through Horizon 2020 and Horizon Europe. [ABSTRACT FROM AUTHOR]

The paper provides an overview of an experimental, Grid-like computing environment, Polder, and its components. Polder offers high-performance computing and interactive simulation facilities to computational science. It was successfully implemented on a wide-area cluster system, the Distributed ASCI Supercomputer. An important issue is an efficient management of resources, in particular multi-level scheduling and migration of tasks that use PVM or sockets. The system can be applied to interactive simulation, where a cluster is used for high-performance computations, while a dedicated immersive interactive environment (CAVE) offers visualization and user interaction. Design considerations for the construction of dynamic exploration environments using such a system are discussed, in particular the use of intelligent agents for coordination. A case study of simulatedabdominal vascular reconstruction is subsequently presented: the results of computed tomography or magnetic resonance imaging of a patient are displayed in CAVE, and a surgeon can evaluate the possible treatments by performing the surgeries virtually and analysing the resulting blood flow which is simulated using the lattice-Boltzmann method. Copyright © 2002 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Debuggers play an important role in developing parallel applications. They are used to control the state of many processes, to present distributed information in a concise and clear way, to observe the execution behavior, and to detect and locate programming errors. More sophisticated debugging systems also try to improve understanding of global execution behavior and intricate details of a program. In this paper we describe the design and implementation of SPiDER, which is an interactive source-level debugging system for both regular and irregular High-Performance Fortran (HPF) programs. SPiDER combines a base debugging system for message-passing programs with a high-level debugger that interfaces with an HPF compiler. SPiDER, in addition to conventional debugging functionality, allows a single process of a parallel program to be expected or the entire program to be examined from a global point of view. A sophisticated visualization system has been developed and included in SPiDER to visualize data distributions, data-to-processor mapping relationships, and array values. SPiDER enables a programmer to dynamically change data distributions as well as array values. For arrays whose distribution can change during program execution, an animated replay displays the distribution sequence together with the associated source code location. Array values can be stored at individual execution points and compared against each other to examine execution behavior (e.g. convergence behavior of a numerical algorithm). Finally, SPiDER also offers limited support to evaluate the performance of parallel programs through a graphical load diagram. SPiDER has been fully implemented and is currently being used for the development of various real-world applications. Several experiments are presented that demonstrate the usefulness of SPiDER. Copyright © 2002 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Smart levees are being increasingly investigated as a flood protection technology. However, in large-scale emergency situations, a flood decision support system may need to collect and process data from hundreds of kilometers of smart levees; such a scenario requires a resilient and scalable IT infrastructure, capable of providing urgent computing services in order to perform frequent data analyses required in decision making, and deliver their results in a timely fashion. We present the ISMOP IT infrastructure for smart levee monitoring, designed to support decision making in large-scale emergency situations. Most existing approaches to urgent computing services in decision support systems dealing with natural disasters focus on delivering quality of service for individual, isolated subsystems of the IT infrastructure (such as computing, storage, or data transmission). We propose a holistic approach to dynamic system management during both urgent (emergency) and normal (non-emergency) operation. In this approach, we introduce a Holistic Computing Controller which calculates and deploys a globally optimal configuration for the entire IT infrastructure, based on cost-of-operation and quality-of-service (QoS) requirements of individual IT subsystems, expressed in the form of Service Level Agreements (SLAs). Our approach leads to improved configuration settings and, consequently, better fulfilment of the system’s cost and QoS requirements than would have otherwise been possible had the configuration of all subsystems been managed in isolation.