The Advanced Encryption Standard (AES) was developed by Joan Daemen and Vincent Rjimen and endorsed by the National Institute of Standards and Technology in 2001. It was designed to replace the aging Data Encryption Standard (DES) and be useful for a wide range of applications with varying throughput, area, power dissipation and energy consumption requirements. Field Programmable Gate Arrays (FPGAs) are flexible and reconfigurable integrated circuits that are useful for many different applications including the implementation of AES. Though they are highly flexible, FPGAs are often less efficient than Application Specific Integrated Circuits (ASICs); they tend to operate slower, take up more space and dissipate more power. There have been many FPGA AES implementations that focus on obtaining high throughput or low area usage, but very little research done in the area of low power or energy efficient FPGA based AES; in fact, it is rare for estimates on power dissipation to be made at all. This thesis presents a methodology to evaluate the energy efficiency of FPGA based AES designs and proposes a novel FPGA AES implementation which is highly flexible and energy efficient. The proposed methodology is implemented as part of a novel scripting tool, the AES Energy Analyzer, which is able to fully characterize the power dissipation and energy efficiency of FPGA based AES designs. Additionally, this thesis introduces a new FPGA power reduction technique called Opportunistic Combinational Operand Gating (OCOG) which is used in the proposed energy efficient implementation. The AES Energy Analyzer was able to estimate the power dissipation and energy efficiency of the proposed AES design during its most commonly performed operations. It was found that the proposed implementation consumes less energy per operation than any previous FPGA based AES implementations that included power estimations. Finally, the use of Opportunistic Combinational Operand Gating on an AES cipher was found to reduce its dynamic power consumption by up to 17% when compared to an identical design that did not employ the technique.

The purpose of this thesis is to explore the formal verification technique of completion functions and equivalence checking by verifying two pipelined cryptographic circuits, KASUMI and WG ciphers. Most of current methods of communications either involve a personal computer or a mobile phone. To ensure that the information is exchanged in a secure manner, encryption circuits are used to transform the information into an unintelligible form. To be highly secure, this type of circuits is generally designed such that it is hard to analyze. Due to this fact, it becomes hard to locate a design error in the verification of cryptographic circuits. Therefore, cryptographic circuits pose significant challenges in the area of formal verification. Formal verification use mathematics to formulate correctness criteria of designs, to develop mathematical models of designs, and to verify designs against their correctness criteria. The results of this work can extend the existing collection of verification methods as well as benefiting the area of cryptography. In this thesis, we implemented the KASUMI cipher in VHDL, and we applied the optimization technique of pipelining to create three additional implementations of KASUMI. We verified the three pipelined implementations of KASUMI with completion functions and equivalence checking. During the verification of KASUMI, we developed a methodology to handle the completion functions efficiently based on VHDL generic parameters. We implemented the WG cipher in VHDL, and we applied the optimization techniques of pipelining and hardware re-use to create an optimized implementation of WG. We verified the optimized implementation of WG with completion functions and equivalence checking. During the verification of WG, we developed the methodology of ``skipping" that can decrease the number of verification obligations required to verify the correctness of a circuit. During the verification of WG, we developed a way of applying the completion functions approach such that it can deal with a circuit that has been optimized with hardware re-use.

Medical devices processing images or audio or executing complex AI algorithms are able to run more efficiently and meet real time requirements if the parallelism in those algorithms is exploited. In this research a methodology is proposed to exploit the flexibility and short design cycle of FPGAs (Field Programmable Gate Arrays) in order to achieve this target. Hardware/software co-design and dynamic partitioning allow the optimization of the multiprocessor platform design parameters and software code targeting each core to meet real time constraints. This is practically demonstrated by building a real life driver vigilance monitoring system based on visual cues extraction and evaluation. The application drives the whole design process to prove its effectiveness. An algorithm was built to achieve the goal of detecting the eye state of the driver (open or closed) and it is applied on captured consecutive frames to evaluate the vigilance state of the driver. Vigilance state is measured depending on duration of eye closure. This video processing application is then targeted to run on a multi-core FPGA based processing platform using the proposed methodology. Results obtained were very good using the Grimace Face Database and when operating the system on one’s face. On operating the device, a false positive of eye closure must take place two consecutive times in order to get an alarm, which decreases the probability of failure. The timing analysis applied proved the importance of using the concept of parallelism to achieve performance constraints. FPGA technology proved to be a very powerful prototyping tool for complex multiprocessor systems design. The flexible FPGA technology coupled with hardware/software co-design provided means to explore the design space and reach decisions that satisfy the design constraints with minimum time investment and cost.

The imperfections in the semiconductor fabrication process and uncertainty in operating environment of VLSI circuits have emerged as critical challenges for the semiconductor industry. These are generally termed as process and environment variations, which lead to uncertainty in performance and unreliable operation of the circuits. These problems have been further aggravated in scaled nanometer technologies due to increased process variations and reduced operating voltage. Several techniques have been proposed recently for designing digital VLSI circuits under variability. However, most of them have targeted ASICs and custom designs. The flexibility of reconfiguration and unknown end application in FPGAs make design under variability different for FPGAs compared to ASICs and custom designs, and the techniques proposed for ASICs and custom designs cannot be directly applied to FPGAs. An important design consideration is to minimize the modifications in architecture and circuit to reduce the cost of changing the existing FPGA architecture and circuit. The focus of this work can be divided into three principal categories, which are, improving timing yield under process variations, improving power yield under process variations and improving the voltage profile in the FPGA power grid. The work on timing yield improvement proposes routing architecture enhancements along with CAD techniques to improve the timing yield of FPGA designs. The work on power yield improvement for FPGAs selects a low power dual-Vdd FPGA design as the baseline FPGA architecture for developing power yield enhancement techniques. It proposes CAD techniques to improve the power yield of FPGAs. A mathematical programming technique is proposed to determine the parameters of the buffers in the interconnect such as the sizes of the transistors and threshold voltage of the transistors, all within constraints, such that the leakage variability is minimized under delay constraints. Two CAD techniques are investigated and proposed to improve the supply voltage profile of the power grids in FPGAs. The first technique is a place and route technique and the second technique is a logic clustering technique to reduce IR-drops and spatial variation of supply voltage in the power grid.

This article describes an inexpensive way of clock generation for FPGA-based circuit cores, which reduces the number of external clock sources and eases synchronization problems. We introduce a modified version of the BRESENHAM line drawing algorithm and use it outside its original application domain for the rational division of clocks. An optimized hardware design for BRESENHAM-based clock division is presented and the quality of its output is evaluated. The optimal initialization conditions in terms of phase shift and jitter are identified and formally proven. Finally, the complexity characteristics of a generic synthesizable VHDL design based on this algorithm are examined and verified by synthesis examples. Special attention is paid to implementation results in conjunction with different FPGA families.

The purpose of this thesis is to design and implement a linear quadratic optimal controller for a twin-buck converter with zero-voltage-transition (ZVT). The controller calculates duty ratio every cycle based on voltage and current feedback, as well as estimates the time instances when the synchronous rectification power switch current is zero. These time instances are crucial for ZVT operation. Via frequency modulation, the controller is designed to automatically regulate the output voltage to a desired value under load and voltage source variation. Simulations indicate that the proposed control design works. The controller is implemented using a Field Programmable Gate Array (FPGA). The experimental results match the simulations, which further verifies the applicability of the proposed voltage regulation strategy.

Conventionally, to speed up scientific or engineering (S&E) computation programs on general-purpose computers, one may elect to use faster CPUs, more memory, systems with more efficient (though complicated) architecture, better software compilers, or even coding with assembly languages. With the emergence of Field Programmable Gate Array (FPGA) based Reconfigurable Computing (RC) technology, numerical scientists and engineers now have another option using FPGA devices as core components to address their computational problems. The hardware-programmable, low-cost, but powerful “FPGA-enhanced computer” has now become an attractive approach for many S&E applications. A new computer architecture model for FPGA-enhanced computer systems and its detailed hardware implementation are proposed for accelerating the solutions of computationally demanding and data intensive numerical PDE problems. New FPGAoptimized algorithms/methods for rapid executions of representative numerical methods such as Finite Difference Methods (FDM) and Finite Element Methods (FEM) are designed, analyzed, and implemented on it. Linear wave equations based on seismic data processing applications are adopted as the targeting PDE problems to demonstrate the effectiveness of this new computer model. Their sustained computational performances are compared with pure software programs operating on commodity CPUbased general-purpose computers. Quantitative analysis is performed from a hierarchical set of aspects as customized/extraordinary computer arithmetic or function units, compact but flexible system architecture and memory hierarchy, and hardwareoptimized numerical algorithms or methods that may be inappropriate for conventional general-purpose computers. The preferable property of in-system hardware reconfigurability of the new system is emphasized aiming at effectively accelerating the execution of complex multi-stage numerical applications. Methodologies for accelerating the targeting PDE problems as well as other numerical PDE problems, such as heat equations and Laplace equations utilizing programmable hardware resources are concluded, which imply the broad usage of the proposed FPGA-enhanced computers.

With the advances in very large scale integration (VLSI) technology, hardware is going parallel. Software, which was traditionally designed to execute on single core microprocessors, now faces the tough challenge of taking advantage of this parallelism, made available by the scaling of hardware. The work presented in this dissertation studies the acceleration of electronic design automation (EDA) software on several hardware platforms such as custom integrated circuits (ICs), field programmable gate arrays (FPGAs) and graphics processors. This dissertation concentrates on a subset of EDA algorithms which are heavily used in the VLSI design flow, and also have varying degrees of inherent parallelism in them. In particular, Boolean satisfiability, Monte Carlo based statistical static timing analysis, circuit simulation, fault simulation and fault table generation are explored. The architectural and performance tradeoffs of implementing the above applications on these alternative platforms (in comparison to their implementation on a single core microprocessor) are studied. In addition, this dissertation also presents an automated approach to accelerate uniprocessor code using a graphics processing unit (GPU). The key idea is to partition the software application into kernels in an automated fashion, such that multiple instances of these kernels, when executed in parallel on the GPU, can maximally benefit from the GPU?s hardware resources. The work presented in this dissertation demonstrates that several EDA algorithms can be successfully rearchitected to maximally harness their performance on alternative platforms such as custom designed ICs, FPGAs and graphic processors, and obtain speedups upto 800X. The approaches in this dissertation collectively aim to contribute towards enabling the computer aided design (CAD) community to accelerate EDA algorithms on arbitrary hardware platforms.

This dissertation deals with (a) fine granularity video compression technique and (b) its application to robust video transmission over wireless Internet. First, two wavelet-domain motion estimation algorithms, HMRME (Half-pixel Multi-Resolution Motion Estimation) and HSDD (Hierarchical Sum of Double Difference Metric), have been proposed to give wavelet-based FGS (Fine Granularity Scalability) video encoder with either low-complexity or high-performance features. Second, a VLSI-friendly high-performance embedded coder ABEC (Array-Based Embedded Coder) has been built to encode motion compensation residue as bitstream with fine granularity scalability. Third, the analysis of loss-rate prediction over Gilbert channel with loss-rate feedback, and several optimal FEC (Forward Error Correction) assignment schemes applicable for any real-time FGS video transmission system will be presented in this dissertation. In addition to those theoretical works mentioned above, for future study on embedded systems for wireless FGS video transmission, an initiative FPGA-based MPEG-4 video encoder has also been implemented in this work.

In the high-speed indoor wireless applications, IEEE 802.11 series is the most dominating LAN standard in the current markets. In this thesis, the design issues of the IEEE 802.11a physical layer baseband system are addressed. Various key modules including Viterbi codec, FFT/IFFT module, OFDM synchronous circuit have been integrated with several other modules to constitute the entire baseband system. This system has been implemented by Verilog HDL and verified against with the C-based behavior model. In addition, it will also be prototyped and optimized on the Altera DSP FPGA Development Board. The transmission of the I, Q channel for the time domain singal is emulated by using the 10-bits AD/DA modules on the FPGA board. The experimental results shows that the gate counts of the transmitter and the receiver are 81,190 and 413,461 respectively.