701 research outputs found

    Statistical lossless compression of space imagery and general data in a reconfigurable architecture

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    Analysis of runtime re-configuration systems

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    In recent years Programmable Logic Devices (PLD) and in particular Field Programmable Gate Arrays (FPGAs) have seen a tremendous increase in sales and applications in the area of embedded systems. The main advantage of FPGAs is the flexibility that they offer a designer in reconfiguring the hardware. The flexibility achieved through re-configuration of FPGAs usually incurs an overhead of extra execution time, data memory and also power dissipation; FPGAs provide an ideal template for run-time reconfigurable (RTR) designs. Only recently have RTR enabling design tools that bypass the traditional synthesis and bitstream generation process for FPGAs become available, JBits is one of them. With run-time reconfiguration of FPGAs, we can perform partial reconfiguration, which allows reconfiguration of a part of an FPGA while the other part is executing some functional computation. The partial reconfiguration of a function can be performed earlier than the time when the function is really needed. Such configuration pre-fetch can hide the reconfiguration overhead more effectively; This thesis will implement a reconfigurable system and study the effect of runtime reconfiguration using VERILOG and a new Java based tool JBITS. This work will provide pointers to high level synthesis tools targeting runtime re-configuration

    Compact Field Programmable Gate Array Based Physical Unclonable Functions Circuits

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    The Physical Unclonable Functions (PUFs) is a candidate to provide a secure solid root source for identification and authentication applications. It is precious for FPGA-based systems, as FPGA designs are vulnerable to IP thefts and cloning. Ideally, the PUFs should have strong random variations from one chip to another, and thus each PUF is unique and hard to replicate. Also, the PUFs should be stable over time so that the same challenge bits always yield the same result. Correspondingly, one of the major challenges for FPGA-based PUFs is the difficulty of avoiding systematic bias in the integrated circuits but also pulling out consistent characteristics as the PUF at the same time. This thesis discusses several compact PUF structures relying on programmable delay lines (PDLs) and our novel intertwined programmable delays (IPD). We explore the strategy to extract the genuinely random PUF from these structures by minimizing the systematic biases. Yet, our methods still maintain very high reliability. Furthermore, our proposed designs, especially the TERO-based PUFs, show promising resilience to machine learning (ML) attacks. We also suggest the bit-bias metric to estimate PUF’s complexity quickly

    Efficient reconfigurable architectures for 3D medical image compression

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    This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Recently, the more widespread use of three-dimensional (3-D) imaging modalities, such as magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), and ultrasound (US) have generated a massive amount of volumetric data. These have provided an impetus to the development of other applications, in particular telemedicine and teleradiology. In these fields, medical image compression is important since both efficient storage and transmission of data through high-bandwidth digital communication lines are of crucial importance. Despite their advantages, most 3-D medical imaging algorithms are computationally intensive with matrix transformation as the most fundamental operation involved in the transform-based methods. Therefore, there is a real need for high-performance systems, whilst keeping architectures exible to allow for quick upgradeability with real-time applications. Moreover, in order to obtain efficient solutions for large medical volumes data, an efficient implementation of these operations is of significant importance. Reconfigurable hardware, in the form of field programmable gate arrays (FPGAs) has been proposed as viable system building block in the construction of high-performance systems at an economical price. Consequently, FPGAs seem an ideal candidate to harness and exploit their inherent advantages such as massive parallelism capabilities, multimillion gate counts, and special low-power packages. The key achievements of the work presented in this thesis are summarised as follows. Two architectures for 3-D Haar wavelet transform (HWT) have been proposed based on transpose-based computation and partial reconfiguration suitable for 3-D medical imaging applications. These applications require continuous hardware servicing, and as a result dynamic partial reconfiguration (DPR) has been introduced. Comparative study for both non-partial and partial reconfiguration implementation has shown that DPR offers many advantages and leads to a compelling solution for implementing computationally intensive applications such as 3-D medical image compression. Using DPR, several large systems are mapped to small hardware resources, and the area, power consumption as well as maximum frequency are optimised and improved. Moreover, an FPGA-based architecture of the finite Radon transform (FRAT)with three design strategies has been proposed: direct implementation of pseudo-code with a sequential or pipelined description, and block random access memory (BRAM)- based method. An analysis with various medical imaging modalities has been carried out. Results obtained for image de-noising implementation using FRAT exhibits promising results in reducing Gaussian white noise in medical images. In terms of hardware implementation, promising trade-offs on maximum frequency, throughput and area are also achieved. Furthermore, a novel hardware implementation of 3-D medical image compression system with context-based adaptive variable length coding (CAVLC) has been proposed. An evaluation of the 3-D integer transform (IT) and the discrete wavelet transform (DWT) with lifting scheme (LS) for transform blocks reveal that 3-D IT demonstrates better computational complexity than the 3-D DWT, whilst the 3-D DWT with LS exhibits a lossless compression that is significantly useful for medical image compression. Additionally, an architecture of CAVLC that is capable of compressing high-definition (HD) images in real-time without any buffer between the quantiser and the entropy coder is proposed. Through a judicious parallelisation, promising results have been obtained with limited resources. In summary, this research is tackling the issues of massive 3-D medical volumes data that requires compression as well as hardware implementation to accelerate the slowest operations in the system. Results obtained also reveal a significant achievement in terms of the architecture efficiency and applications performance.Ministry of Higher Education Malaysia (MOHE), Universiti Tun Hussein Onn Malaysia (UTHM) and the British Counci

    Implementation of JPEG compression and motion estimation on FPGA hardware

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    A hardware implementation of JPEG allows for real-time compression in data intensivve applications, such as high speed scanning, medical imaging and satellite image transmission. Implementation options include dedicated DSP or media processors, FPGA boards, and ASICs. Factors that affect the choice of platform selection involve cost, speed, memory, size, power consumption, and case of reconfiguration. The proposed hardware solution is based on a Very high speed integrated circuit Hardware Description Language (VHDL) implememtation of the codec with prefered realization using an FPGA board due to speed, cost and flexibility factors; The VHDL language is commonly used to model hardware impletations from a top down perspective. The VHDL code may be simulated to correct mistakes and subsequently synthesized into hardware using a synthesis tool, such as the xilinx ise suite. The same VHDL code may be synthesized into a number of sifferent hardware architetcures based on constraints given. For example speed was the major constraint when synthesizing the pipeline of jpeg encoding and decoding, while chip area and power consumption were primary constraints when synthesizing the on-die memory because of large area. Thus, there is a trade off between area and speed in logic synthesis
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