The project presents a high performance reconfigurable platform for security, video processing and connected health applications. A heterogeneous system for real-time prototyping of IPs used for people identification and recognition, video processing and connected health application is proposed. Novel techniques for efficient acquisition, visualisation and processing of heterogeneous data will be developed and implemented on a high performance reconfigurable platform.
The communication presentations (keynote talks, facilitated break-out sessions, posters) will be continuously in May and June.
Abbes Amira is Professor in Visual Communications at University of the West of Scotland (United Kingdom).
The research interests of Prof. Amira comprise image and vision systems, embedded systems, image/video processing and analysis, pattern recognition, and connected health and security.
|CHIST-ERA Conference 2013 - Abbes Amira.pdf||5.96 MB|
Alexandros Koliousis is Research Associate at the Department of Computer Science, Imperial College London (United Kingdom), and a member of the Experimental Software Systems (ESS) group, also affiliated with the Large-Scale Distributed Systems (LSDS) group.
The research interest of Dr. Koliousis lie in areas of distributed computing, including self-organizing networks; environmental sensor systems; (home) network monitoring and management; complexity of routing protocols; classification of network flows; complex queries over data streams; and data center management.
Today, the dominant approach to constructing data centres is to assemble large numbers of commodity resources for computation, communication, and storage. But for many emerging big data applications, an infrastructure built from a homogeneous, commodity platform is inadequate to meet latency and throughput requirements. How can we provide a new generation of cloud data centres that can exploit heterogeneous cloud computing resources incorporating the latest advances in hardware accelerators, programmable networks, and storage technologies? The challenge is to provide a convenient, cost-effective, energy-efficient, high-performance, multi-tenant Platform-as-a-Service to big data applications that can hide the complexity of managing a heterogeneous computing infrastructure.
|CHIST-ERA Conference 2013 - Alexandros Koliousis.pdf||2.44 MB|
Dr. Anil Anthony Bharath is Reader in Image Analysis, and an Associate Director of Imperial's Institute for Security Science and Technology.
The research interests of Dr. Bharath includes imaging, image analysis, acoustics, and signal processing.
The "Picture This..." Programme aims to apply engineering science to develop assistive systems for blind and visually impaired people. “Assistive systems” refers to the heterogenous collection of devices and supporting architectures and processes. Scientific/Technical themes include: distributed architectures for the analysis of signal, image and video data; cloud-based processing systems; algorithms for energy-efficient inference on mobile devices; crowdsourcing of data, including visual cues; visual detection of hazards; security and reliability of “crowdsourced” navigational information; new devices; methods and grammars for supporting heterogenous computing systems. We suggest strong emphasis on benchmarking performance, at all system levels: power, accuracy, latency, usability.
Egons Lavendelis is assistant professor at Riga Technical University (Latvia).
The research interests of Mr. Lavendelis include Intelligent agents, Multi-agent systems, Agent-oriented software engineering, Intelligent tutoring systems, Ontology-based software systems, Autonomous software and robotic systems, Machine learning.
The poster will present a project idea of using multi-agent approach for modelling of complex technical and social systems. The multi-agent paradigm allows increasing the abstraction level of interaction among system’s elements. This approach provides means for modelling of various complex systems with highly heterogeneous elements. We propose to combine the existing modelling methods with multi-agent paradigm and high performance computing (HPC) that is available at Riga Technical University.
|CHIST-ERA Conference 2013 - Egons Lavendelis.pdf||451.3 KB|
Iraklis A. Klampanos is Research Associate in the Centre for Intelligent Systems and their Applications of the School of Informatics of the University of Edinburgh.
Diversity, in every dimension, is a key attribute of today’s data bonanza. Our research takes a holistic view, embracing this diversity and the consequent intricate interactions between users and systems. We created the Dispel data-streaming language to describe complex computation patterns at high levels of abstraction, while providing meta-information for optimisation. Provenance and contextual information must be harnessed to achieve autonomous execution, data placement, energy efficiency and reliability. Research is needed, that builds foundations for comprehensible and tractable paths through the rapidly evolving data landscape. This must be driven by and tested at realistic scales and diversity levels.
Kevin Curran is Reader in Computer Science and group leader for the Ambient Intelligence Research Group at the University of Ulster (Northern Ireland).
The research interests of Dr. Curran comprise computer networking and systems; in particular location positioning within indoor environments, pervasive computing and internet security.
The increasing availability and decreasing cost of mobile devices equipped with WiFi radios has led to increasing demand for multimedia applications in both professional and entertainment contexts. The streaming of multimedia however requires strict adherence to QoS levels in order to guarantee suitable quality for end users. MANETs lack the centralised control, coordination and infrastructure of wireless networks as well as presenting a further element of complexity in the form of device mobility. Such constraints make achieving suitable QoS a nontrivial challenge and much work has already been presented in this area. We present out work on a bottom-up routing protocol which specifically takes into account mobility and other unique characteristics of MANETs in order to improve QoS for multimedia streaming. Geographic Predictive Routing (GPR) uses Artificial Neural Networks to accurately predict the future locations of neighbouring devices for making location and mobility-aware routing decisions. GPR is intended as the first step towards creating a fully QoS-aware networking framework for enhancing the performance of multimedia streaming in MANETs.
Leandro Fiorin is Research Associate in ALaRI, the Advanced Learning and Research Institute, part of the Faculty of Informatics of the University of Lugano (Switzerland).
The research interests of Mr. Fiorin include Networks-on-Chips (NoCs), Multiprocessor System-on-Chips (MPSoCs), Reconfigurable Systems.
The design of next generation heterogeneous computing platforms is facing new challenges: the scaling provided by Moore’s law led to hitting the “power wall” as well as to falling under the law of diminishing returns, for which density increase was not met by accompanying performance increase. The use of heterogeneous multiprocessor platforms, both in the embedded and in the high performance computing seems the right approach to be followed. However, a number of new directions at the design and at run-time are now open to be explored for optimizing the system both in terms of performance and energy efficiency: number and type of processors, use of dedicated accelerators, resiliency of the overall system, mapping of applications into existing cores, software application customization, etc. In this poster, we summarize our research activity in the optimization of fault-tolerant and adaptive computing platforms, as results of the participation in several EU and national projects focusing on the development of methodologies for the multi-objective design space exploration of multiprocessor system-on-chip platforms.
|CHIST-ERA Conference 2013 - Leandro Fiorin.pdf||267.65 KB|
Sabri Pllana is an Associate Professor at the Department of Computer Science of the Linnaeus University in Sweden.
The research interests of Prof. Pllana include intelligent programming environments and performance-oriented software engineering for parallel and distributed systems.
Programming heterogeneous computing systems so far proved to be prohibitively difficult for mainstream programmers. Commonly research projects have avoided addressing fundamental issues of programming heterogeneous systems and provided similar (directive-based) solutions with the well-known limitations. We argue that it is now the time to rethink the heterogeneous programming and go beyond directive-based languages.
|CHIST-ERA Conference 2013 - Sabri Pllana & Danny Weyns.pdf||155.5 KB|
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