Full Title: WCET-Aware PaRallelization of Model-Based Applications for HeteroGeneOus Parallel Systems
Abstract: Increasing performance and reducing cost, while maintaining safety levels and programmability are the key demands for embedded and cyber-physical systems in European domains, e.g. aerospace, automation, and automotive. For many applications, the necessary performance with low energy consumption can only be provided by customized computing platforms based on heterogeneous many-core architectures. However, their parallel programming with time-critical embedded applications suffers from a complex toolchain and programming process. ARGO (WCET-Aware PaRallelization of Model-Based Applications for HeteroGeneOus Parallel Systems) will address this challenge with a holistic approach for programming heterogeneous multi- and many-core architectures using automatic parallelization of model-based real-time applications. ARGO will enhance WCET-aware automatic parallelization by a cross-layer programming approach combining automatic tool-based and user-guided parallelization to reduce the need for expertise in programming parallel heterogeneous architectures. The ARGO approach will be assessed and demonstrated by prototyping comprehensive time-critical applications from both aerospace and industrial automation domains on customized heterogeneous many-core platforms. The challenging research and innovation action will be achieved by the unique ARGO consortium that brings together industry, leading research institutes and universities. High class SMEs such as Recore Systems, Scilab Enterprises and AbsInt will contribute their diverse know-how in heterogeneous many-core technologies, model-based design environments and WCET calculation. The academic partners will contribute their outstanding expertise in code transformations, automatic parallelization and system-level WCET analysis.
Funded by: The European Program for Research and Innovation HORIZON 2020, ICT 4 – 2015: Customised and low power computing
Implementation Period: 01/01/2016 - 31/12/2019
Acronym: IKYDA 2016 - IMAGINE
Full Title: End-to-End AnalysIs and OptiMizAtion of AlGorithms running on Internet of ΤhiNgs (ΙοΤ) infrastructurE
Abstract: The purpose of this work is to analyze and propose methods and tools for optimal allocation of the resources that can be available by an Internet of Things (IoT) infrastructure. Without restricting the general applicability, we will narrow the search space on applications and algorithms which process data coming from sensors, and specifically from an image sensor, as this can be considered one of the most demanding use cases for the scale of an IoT system. Our goal is to end up with a holistic approach in which all the processing, storage and communication resources of an IoT infrastructure will work in tandem following specific user-defined optimization criteria like reducing the power at system-level or minimizing the volume of transferred data.
Funded by: DAAD, IKY
Implementation Period: 01/03/2016 - 31/12/2017
Full Title: Robots in assisted living environments: Unobtrusive, efficient, reliable and modular solutions for independent ageing
Abstract: Demographic and epidemiologic transitions have brought a new health care paradigm with the presence of both, growing elderly population and chronic diseases. Life expectancy is increasing as well as the need for long-term care. Institutional care for the aged population faces economical struggles with low staffing ratios and consequent quality problems. Although the aforementioned implications of ageing impose societal challenges, at the same time new opportunities arise for the European citizens, the healthcare systems as well as the industry and the European market. Two of the most important aspects of assistive environments and independent living are user acceptance and unobtrusiveness. Mostly explored in a smart home setup and the unobtrusive installation of audio-visual monitoring equipment, the consensus is that users accept monitoring if they are not constantly aware of its presence. A more recent trend is home assistant robots. These two lines of development have for the most part ran without heavily interacting with each other and, even more so, without developing integrated solutions that combine smart home automation with robotics. In RADIO, we will develop an integrated smart home/assistant robot system, with the objective of pursuing a novel approach to acceptance and unobtrusiveness: a system where sensing equipment is not discrete but an obvious and accepted part of the user’s daily life. By using the integrated smart home/assistant robot system as the sensing equipment for health monitoring, we mask the functionality of the sensors rather than the sensors themselves. In this manner, sensors do not need to be discrete and distant or masked and cumbersome to install; they do however need to be perceived as a natural component of the smart home/assistant robot functionalities.
Funded by: The European Program for Research and Innovation HORIZON 2020, PHC-19-2014: Advancing active and healthy ageing with ICT: service robotics within assisted living environments
Implementation Period: 01/04/2015 - 31/03/2018
Full Title: Architecture oriented paraLlelization for high performance embedded Multicore systems using scilAb
Abstract: The mapping process of high performance embedded applications to today’s multiprocessor system on chip devices suffers from a complex toolchain and programming process. The problem here is the expression of parallelism with a pure imperative programming language which is commonly C. This traditional approach limits the mapping, partitioning and the generation of optimized parallel code, and consequently the achievable performance and power consumption of applications from different domains. The Architecture oriented paraLlelization for high performance embedded Multicore systems using scilAb (ALMA) project aims to bridge these hurdles through the introduction and exploitation of a Scilab-based toolchain which enables the efficient mapping of applications on multiprocessor platforms from high level of abstraction. This holistic solution of the toolchain allows the complexity of both the application and the architecture to be hidden, which leads to a better acceptance, reduced development cost and shorter time-to-market. Driven by the technology restrictions in chip design, the end of Moore’s law and an unavoidable increasing request of computing performance, ALMA is a fundamental step forward in the necessary introduction of novel computing paradigms and methodologies. ALMA helps to strengthen the position of the EU in the world market of multiprocessor targeted software toolchains. The challenging research will be achieved by the unique ALMA consortium which brings together industry and academia. High class partners from industry such as Recore and Intracom Telecom, will contribute their expertise in reconfigurable hardware technology for multi-core systems-on-chip, software development tools and real world applications. The academic partners will contribute their outstanding expertise in reconfigurable computing and compilation tools development.
Funded by: ICT-2011.3.4 Computing Systems
Implementation Period: 01/09/2011 - 28/02/2015
Full Title: Advanced multi-paRametric Monitoring and analysis for diagnosis and Optimal management of epilepsy and Related brain disorders
Abstract: The main objective of the project is to manage and analyse a large number of already acquired and new multimodal and advanced technology data from brain and body activities of epileptic patients and controls (MEG, multichannel EEG, video, ECG, GSR, EMG, etc) aiming to design a more holistic, personalized, medically efficient and economical monitoring system. From a medical perspective, the project contributes to medicine by assisting in better understanding of the mechanisms of epilepsy and related disorders as well as their manifestations. From an ICT perspective, new methods and tools are developed for multimodal data pre-processing and fusion of information from various sources. Novel approaches for large scale analysis (both real-time and offline) of multi-parametric streaming and archived data are introduced to discover patterns and associations between external indicators and mental states, detect correlations among parallel observations, and identify vital signs changing significantly. Moreover, in the projects framework, methods for automatically summarizing results and efficiently managing medical data are developed. ARMOR incorporates models derived from data analysis based on already existing communication platform solutions emphasizing on security and ethical issues and performing required adaptations to meet specifications. Special effort is devoted in areas such as data anonymization and provision of required service. ARMOR provides flexible monitoring optimized for each patient and is tested in several case studies and evaluated as a wide use ambulatory monitoring tool for seizures efficient diagnosis and management including possibilities for detecting premonitory signs and feedback to the patient.
Funded by: 7th Framework Program, ICT-2011.5.1: Personal Health, Systems (PHS), b) Intelligent systems for the analysis of multi-parametric data
Implementation Period: 01/11/2011 - 31/04/2015
Full Title: Virtualization of reconfigurable heterogeneous high performance hardware/software systems
Abstract: The main objective of this project is to study, evaluate and propose algorithms to optimize software for embedded systems based on hardware architectures with multiple processor cores. As part of this project we will develop a set of tools for analysis and optimization of embedded software developed for such systems. The tools that will implement the algorithms will suggest scenarios for the allocation of the software (developed by the user) to the available processor cores and will have the opportunity to communicate with the hardware emulator of the platform that contains the processor cores. The tools and algorithms developed will allow the user to compare alternative implementations. The end user will be able to configure the optimization algorithm in order to perform what-if scenarios. The multicore platform that will be used for running the optimized embedded software will be developed by Institute for Information Processing Technology, Karlsruhe Institute of Technology.
Funded by: IKY
Implementation Period: 01/01/2011 - 31/12/2012