Variation-aware high-level DSP circuit design optimisation framework for FPGAs

The constant technology shrinking and the increasing demand for systems that operate under different power profiles with the maximum performance, have motivated the work in this thesis. Modern design tools that target FPGA devices take a conservative approach in the estimation of the maximum performance that can be achieved by a design when it is placed on a device, accounting for any variability in the fabrication process of the device. The work presented here takes a new view on the performance improvement of DSP designs by pushing them into the error-prone regime, as defined by the synthesis tools, and by investigating methodologies that reduce the impact of timing errors at the output of the system. In this work two novel error reduction techniques are proposed to address this problem. One is based on reduced-precision redundancy and the other on an error optimisation framework that uses information from a prior characterisation of the device. The first one is a generic architecture that is appended to existing arithmetic operators. The second defines the high-level parameters of the algorithm without using extra resources. Both of these methods allow to achieve graceful degradation whilst variation increases. A comparison of the new methods is laid against the existing methodologies, and conclusions drawn on the tradeoffs between their cost, in terms of resources and errors, and their benefits in terms of throughput. In some cases it is possible to double the performance of the design while still producing valid results.Open Acces

Scalable strategies for tumour targeting of magnetic carriers and seeds

With the evolving landscape of medical oncology, focus has shifted away from nonspecific cytotoxic treatment strategies toward therapeutic paradigms more characteristic of targeted therapies. These therapies rely on delivery vehicles such as nano-carriers or micro robotic devices to boosts the concentration of therapeutics in a specific targeted site inside the body. The use of externally applied magnetic field is suggested to be a predominant approach for remote localisation of magnetically responsive carriers and devices to the target region that could not be otherwise reached. However, the fast decline of the magnetic fields and gradients with increasing distances from the source is posing a major challenge for its clinical application. The aim of this thesis was to investigate potential magnetic delivery strategies which can circumvent some of the typical limitations of this technique. Two different approaches were explored to this end. The first approach was to characterise the ability of a conventional permanent magnet on targeting individual nano-carriers and develop novel magnetic designs which improve the targeting efficiency. The second approach was evaluating the feasibility of a magnetic resonance imaging system to move a millimetre-sized magnetic particle within the body. Phantom and in vivo magnetic targeting experiments illustrated the significant increase in effective targeting depth when our novel magnetic design was used for targeting nano-carriers compared with conventional magnets. In the later part of the thesis, the proof of concept and characterisation experiments showed that a 3 mm magnetic particle can be moved in ex vivo brain tissue using a magnetic resonance imaging system using clinically relevant gradient strengths. The magnetic systems introduced in this thesis provide the potential to target nano-carriers and millimetre-sized thermoseeds to tumours located at deep regions of human body through vasculature and soft tissue respectively

Tools for efficient Deep Learning

In the era of Deep Learning (DL), there is a fast-growing demand for building and deploying Deep Neural Networks (DNNs) on various platforms. This thesis proposes five tools to address the challenges for designing DNNs that are efficient in time, in resources and in power consumption. We first present Aegis and SPGC to address the challenges in improving the memory efficiency of DL training and inference. Aegis makes mixed precision training (MPT) stabler by layer-wise gradient scaling. Empirical experiments show that Aegis can improve MPT accuracy by at most 4\%. SPGC focuses on structured pruning: replacing standard convolution with group convolution (GConv) to avoid irregular sparsity. SPGC formulates GConv pruning as a channel permutation problem and proposes a novel heuristic polynomial-time algorithm. Common DNNs pruned by SPGC have maximally 1\% higher accuracy than prior work. This thesis also addresses the challenges lying in the gap between DNN descriptions and executables by Polygeist for software and POLSCA for hardware. Many novel techniques, e.g. statement splitting and memory partitioning, are explored and used to expand polyhedral optimisation. Polygeist can speed up software execution in sequential and parallel by 2.53 and 9.47 times on Polybench/C. POLSCA achieves 1.5 times speedup over hardware designs directly generated from high-level synthesis on Polybench/C. Moreover, this thesis presents Deacon, a framework that generates FPGA-based DNN accelerators of streaming architectures with advanced pipelining techniques to address the challenges from heterogeneous convolution and residual connections. Deacon provides fine-grained pipelining, graph-level optimisation, and heuristic exploration by graph colouring. Compared with prior designs, Deacon shows resource/power consumption efficiency improvement of 1.2x/3.5x for MobileNets and 1.0x/2.8x for SqueezeNets. All these tools are open source, some of which have already gained public engagement. We believe they can make efficient deep learning applications easier to build and deploy.Open Acces

Parallel implementation of a virtual reality system on a transputer architecture

A Virtual Reality is a computer model of an environment, actual or imagined, presented to a user in as realistic a fashion as possible. Stereo goggles may be used to provide the user with a view of the modelled environment from within the environment, while a data-glove is used to interact with the environment. To simulate reality on a computer, the machine has to produce realistic images rapidly. Such a requirement usually necessitates expensive equipment. This thesis presents an implementation of a virtual reality system on a transputer architecture. The system is general, and is intended to provide support for the development of various virtual environments. The three main components of the system are the output device drivers, the input device drivers, and the virtual world kernel. This last component is responsible for the simulation of the virtual world. The rendering system is described in detail. Various methods for implementing the components of the graphics pipeline are discussed. These are then generalised to make use of the facilities provided by the transputer processor for parallel processing. A number of different decomposition techniques are implemented and compared. The emphasis in this section is on the speed at which the world can be rendered, and the interaction latency involved. In the best case, where almost linear speedup is obtained, a world containing over 250 polygons is rendered at 32 frames/second. The bandwidth of the transputer links is the major factor limiting speedup. A description is given of an input device driver which makes use of a powerglove. Techniques for overcoming the limitations of this device, and for interacting with the virtual world, are discussed. The virtual world kernel is designed to make extensive use of the parallel processing facilities provided by transputers. It is capable of providing support for mUltiple worlds concurrently, and for multiple users interacting with these worlds. Two applications are described that were successfully implemented using this system. The design of the system is compared with other recently developed virtual reality systems. Features that are common or advantageous in each of the systems are discussed. The system described in this thesis compares favourably, particularly in its use of parallel processors.KMBT_22

Auxetic power amplification mechanisms for low frequency vibration energy harvesting

Energy harvesting from locally available small amplitude vibrations can struggle to generate sufficient power for wireless sensor nodes, which thereby constrains their use for structural health monitoring. This work discusses a selection of two-dimensional auxetic substrate designs used to increase a piezoelectric harvester’s power output by 2.18-14.5 times by concentrating the ambient strain energy into the piezoelectric material. The harvesters were modelled and their auxetic designs optimised in COMSOL before empirical testing under sinusoidal or dynamic strain oscillations. The investigated auxetic designs included re-entrant honeycombs, rotating squares, triangles and hexagrams, and -hole structures; the most effective of which was found to be the honeycomb design, with a gain of 5.66 and a raw output of 570 μW at 10 Hz, 100 με. This work also compared PZT (Lead Zirconate Titanate), LN (Lithium Niobate), and MFC (Macro-Fibre Composite) as materials for the active piezoelectric layer. The former was found to be detrimentally brittle but delivered the greatest output, while the LN was stronger but with a significantly lower output. The MFC was more flexible, with only a modest reduction in output compared to PZT, and was found to be the most viable of these materials for future research. A crucial issue during the design stages was appropriately modelling the mechanical losses associated with the bonding between substrate and piezoelectric material; this adhesion was modelled using thin elastic layers (TELs) to emulate each sample by comparing to its output. The value of the stiffness constant per unit area in these TELs was found to be consistent for each sample across a range of input excitations. These kinds of energy harvesters open up many new avenues for wireless self-powered structural health monitoring sensor nodes in infrastructure, buildings, and vehicles, where the ambient vibration energy would otherwise be too diffuse to harvest from.Engineering and Physical Sciences Research Council (EPSRC

The Application of Mixed Reality Within Civil Nuclear Manufacturing and Operational Environments

This thesis documents the design and application of Mixed Reality (MR) within a nuclear manufacturing cell through the creation of a Digitally Assisted Assembly Cell (DAAC). The DAAC is a proof of concept system, combining full body tracking within a room sized environment and bi-directional feedback mechanism to allow communication between users within the Virtual Environment (VE) and a manufacturing cell. This allows for training, remote assistance, delivery of work instructions, and data capture within a manufacturing cell. The research underpinning the DAAC encompasses four main areas; the nuclear industry, Virtual Reality (VR) and MR technology, MR within manufacturing, and finally the 4 th Industrial Revolution (IR4.0). Using an array of Kinect sensors, the DAAC was designed to capture user movements within a real manufacturing cell, which can be transferred in real time to a VE, creating a digital twin of the real cell. Users can interact with each other via digital assets and laser pointers projected into the cell, accompanied by a built-in Voice over Internet Protocol (VoIP) system. This allows for the capture of implicit knowledge from operators within the real manufacturing cell, as well as transfer of that knowledge to future operators. Additionally, users can connect to the VE from anywhere in the world. In this way, experts are able to communicate with the users in the real manufacturing cell and assist with their training. The human tracking data fills an identified gap in the IR4.0 network of Cyber Physical System (CPS), and could allow for future optimisations within manufacturing systems, Material Resource Planning (MRP) and Enterprise Resource Planning (ERP). This project is a demonstration of how MR could prove valuable within nuclear manufacture. The DAAC is designed to be low cost. It is hoped this will allow for its use by groups who have traditionally been priced out of MR technology. This could help Small to Medium Enterprises (SMEs) close the double digital divide between themselves and larger global corporations. For larger corporations it offers the benefit of being low cost, and, is consequently, easier to roll out across the value chain. Skills developed in one area can also be transferred to others across the internet, as users from one manufacturing cell can watch and communicate with those in another. However, as a proof of concept, the DAAC is at Technology Readiness Level (TRL) five or six and, prior to its wider application, further testing is required to asses and improve the technology. The work was patented in both the UK (S. R EDDISH et al., 2017a), the US (S. R EDDISH et al., 2017b) and China (S. R EDDISH et al., 2017c). The patents are owned by Rolls-Royce and cover the methods of bi-directional feedback from which users can interact from the digital to the real and vice versa. Stephen Reddish Mixed Mode Realities in Nuclear Manufacturing Key words: Mixed Mode Reality, Virtual Reality, Augmented Reality, Nuclear, Manufacture, Digital Twin, Cyber Physical Syste

Development of X-ray Tomography Tools for Characterisation of Lithium-Sulfur Batteries

Electrochemical energy storage devices are becoming increasingly ubiquitous in both consumer and industrial applications, driven by a pressing need to reduce carbon emissions for the mitigation of global warming. The electrification of the transport and mobility sector and growth in portable electronic devices demand portable power sources with high energy densities, and lithium-ion (Li-ion) batteries have been adopted extensively in these applications. However, conventional transition metal oxide-based intercalation materials used at the positive electrode are reaching their theoretical limitations, and only relatively minor improvements in theoretical specific capacity can be achieved. // Lithium-sulfur (Li-S) batteries offer higher gravimetric theoretical specific capacity and energy density and are billed as a potential successor to Li-ion technology but suffer from limited cycle life and self-discharge due to complex multi-phase chemistry and parasitic side reactions. // To better understand the fundamental mechanisms behind these processes, advanced characterisation methods involving the use of penetrating radiation (such as X-rays and neutrons) have become invaluable tools to capture the operation and degradation of the Li-S battery. Three-dimensional techniques such as X-ray micro-tomography (micro-CT) are particularly suited to probe the heterogeneous nature of battery electrode microstructures. // In this thesis, main areas of focus will include the application of ex situ and in situ X-ray micro-CT on Li-S batteries and the broader development of in situ tomography cells. The overall scientific aims of this thesis include: measuring the three-dimensional microstructural characteristics of sulfur electrodes; elucidating the three-dimensional nature of both sulfur dissolution and redeposition as a function of state of charge; and developing a better understanding of the transport processes occurring within the Li-S battery and the influence of porosity and tortuosity on electrochemical performance. In parallel, the development of in situ tomography cells capable of electrochemical cycling is an extensive component of this thesis, with applications not solely limited to Li-S batteries or X-ray micro-CT

CAD interface and framework for curve optimisation applications

Computer Aided Design is currently expanding its boundaries to include more design features in its processes. Design is identified as an iterative process converging to solutions satisfying a set of constraints. Its close relation with optimisation indicate that there is strong potential for the integration of optimisation and CAD. The problem addressed in this thesis lies in interfacing the geometric representation of design with other non-geometric aspects. The example of free-form curve modelling is taken to investigate such relationships. Assumptions are made that Optimisation is powered by Evolutionary Computing algorithms like Genetic Algorithms (GA). The geometric definition of curves is commonly supported by NURBS, whose construction constraints are defined locally at the data points. Here the NURBS formulation is used with GA in an attempt to provide complementary handles on the curves shape other than the usual data point coordinates and control points weights. Differential properties are used for optimising NURBS, Hermite interpolation allows for the definition of higher order constraints (tangent, normal, bi-normal) at data points. The assignment of parameter values at the data points, known as parameterisation also provides control of the curve’s shape. Curve optimisation is also performed at the geometric modelling level. Old mathematical theorems established by Frénet and further developed by other mathematicians provide means of defining a curve’s shape with it’s intrinsic equations. Such representation is possible by using Function Representation (F-rep) algebra available in the ACIS software. Frep allows more generic and exact means of interfacing with the curve’s geometry and new functionality for curve inspection and optimisation are proposed in this thesis. The integration of optimisation findings and CAD are documented in the definition of a framework. The framework architecture proposed reconstructs a new CAD environment from separate elements bolted together in a generic Application Programming Interface (API) named “Oli interface”. Functionality created to interface optimisation and CAD makes a requirement list of the work that both sides should undertake to achieve design optimisation in the CAD environment.EThOS - Electronic Theses Online ServiceGBUnited Kingdo