VLSI design of configurable low-power coarse-grained array architecture

Biomedical signal acquisition from in- or on-body sensors often requires local (on-node) low-level pre-processing before the data are sent to a remote node for aggregation and further processing. Local processing is required for many different operations, which include signal cleanup (noise removal), sensor calibration, event detection and data compression. In this environment, processing is subject to aggressive energy consumption restrictions, while often operating under real-time requirements. These conflicting requirements impose the use of dedicated circuits addressing a very specific task or the use of domain-specific customization to obtain significant gains in power efficiency. However, economic and time-to-market constraints often make the development or use of application-specific platforms very risky.One way to address these challenges is to develop a sensor node with a general-purpose architecture combining a low-power, low-performance general microprocessor or micro-controller with a coarse-grained reconfigurable array (CGRA) acting as an accelerator. A CGRA consists of a fixed number of processing units (e.g., ALUs) whose function and interconnections are determined by some configuration data.The objective of this work is to create an RTL-level description of a low-power CGRA of ALUs and produce a low-power VLSI (standard cell) implementation, that supports power-saving features.The CGRA implementation should use as few resources as possible and fully exploit the intended operation environment. The design will be evaluated with a set of simple signal processing task

Mutual Impact between Clock Gating and High Level Synthesis in Reconfigurable Hardware Accelerators

With the diffusion of cyber-physical systems and internet of things, adaptivity and low power consumption became of primary importance in digital systems design. Reconfigurable heterogeneous platforms seem to be one of the most suitable choices to cope with such challenging context. However, their development and power optimization are not trivial, especially considering hardware acceleration components. On the one hand high level synthesis could simplify the design of such kind of systems, but on the other hand it can limit the positive effects of the adopted power saving techniques. In this work, the mutual impact of different high level synthesis tools and the application of the well known clock gating strategy in the development of reconfigurable accelerators is studied. The aim is to optimize a clock gating application according to the chosen high level synthesis engine and target technology (Application Specific Integrated Circuit (ASIC) or Field Programmable Gate Array (FPGA)). Different levels of application of clock gating are evaluated, including a novel multi level solution. Besides assessing the benefits and drawbacks of the clock gating application at different levels, hints for future design automation of low power reconfigurable accelerators through high level synthesis are also derived

Design for energy-efficient and reliable fog-assisted healthcare IoT systems

Cardiovascular disease and diabetes are two of the most dangerous diseases as they are the leading causes of death in all ages. Unfortunately, they cannot be completely cured with the current knowledge and existing technologies. However, they can be effectively managed by applying methods of continuous health monitoring. Nonetheless, it is difficult to achieve a high quality of healthcare with the current health monitoring systems which often have several limitations such as non-mobility support, energy inefficiency, and an insufficiency of advanced services. Therefore, this thesis presents a Fog computing approach focusing on four main tracks, and proposes it as a solution to the existing limitations. In the first track, the main goal is to introduce Fog computing and Fog services into remote health monitoring systems in order to enhance the quality of healthcare. In the second track, a Fog approach providing mobility support in a real-time health monitoring IoT system is proposed. The handover mechanism run by Fog-assisted smart gateways helps to maintain the connection between sensor nodes and the gateways with a minimized latency. Results show that the handover latency of the proposed Fog approach is 10%-50% less than other state-of-the-art mobility support approaches. In the third track, the designs of four energy-efficient health monitoring IoT systems are discussed and developed. Each energy-efficient system and its sensor nodes are designed to serve a specific purpose such as glucose monitoring, ECG monitoring, or fall detection; with the exception of the fourth system which is an advanced and combined system for simultaneously monitoring many diseases such as diabetes and cardiovascular disease. Results show that these sensor nodes can continuously work, depending on the application, up to 70-155 hours when using a 1000 mAh lithium battery. The fourth track mentioned above, provides a Fog-assisted remote health monitoring IoT system for diabetic patients with cardiovascular disease. Via several proposed algorithms such as QT interval extraction, activity status categorization, and fall detection algorithms, the system can process data and detect abnormalities in real-time. Results show that the proposed system using Fog services is a promising approach for improving the treatment of diabetic patients with cardiovascular disease

Approximation Opportunities in Edge Computing Hardware : A Systematic Literature Review

With the increasing popularity of the Internet of Things and massive Machine Type Communication technologies, the number of connected devices is rising. However, while enabling valuable effects to our lives, bandwidth and latency constraints challenge Cloud processing of their associated data amounts. A promising solution to these challenges is the combination of Edge and approximate computing techniques that allows for data processing nearer to the user. This paper aims to survey the potential benefits of these paradigms’ intersection. We provide a state-of-the-art review of circuit-level and architecture-level hardware techniques and popular applications. We also outline essential future research directions.publishedVersionPeer reviewe

Exploring perspectives of people with type-1 diabetes on goalsetting strategies within self-management education and care

Background. Collaborative goal-setting strategies are widely recommended for diabetes self-management support within healthcare systems. Creating self-management plans that fit with peoples’ own goals and priorities has been linked with better diabetic control. Consequently, goal-setting has become a core component of many diabetes selfmanagement programmes such as the ‘Dose Adjustment for Normal Eating (DAFNE) programme’. Within DAFNE, people with Type-1 Diabetes (T1D) develop their own goals along with action-plans to stimulate goal-achievement. While widely implemented, limited research has explored how goal-setting strategies are experienced by people with diabetes.Therefore, this study aims to explore the perspectives of people with T1D on theimplementation and value of goal-setting strategies within DAFNE and follow-up diabetes care. Furthermore, views on barriers and facilitators to goal-attainment are explored.Methods. Semi-structured interviews were conducted with 20 people with T1D who attended a DAFNE-programme. Following a longitudinal qualitative research design, interviews took place 1 week, and 6-8 months after completion of DAFNE. A recurrent cross-sectional approach is applied in which themes will be identified at each time-point using thematic analyses.Expected results. Preliminary identified themes surround the difference in value that participants place on goal-setting strategies, and the lack of support for goal-achievement within diabetes care.Current stage. Data collection complete; data-analysis ongoing.Discussion. Goal-setting strategies are increasingly included in guidelines for diabetes support and have become essential parts of many primary care improvement schemes. Therefore, exploring the perspectives of people with T1D on the value and implementation of goal-setting strategies is vital for their optimal application