Design and Implementation of Arithmetic Logic Unit in DSCH3 and Microwind
Proposed Abstract:
The Arithmetic Logic Unit (ALU) is a fundamental component in digital systems, particularly in the central processing units (CPUs) of microprocessors, where it executes essential arithmetic and logical functions. This paper presents the design and implementation of an 8-bit Arithmetic Logic Unit (ALU) using CMOS technology, developed and simulated in DSCH3 and Microwind environments. The primary goal of this research is to design an efficient and compact ALU optimized for performance and area efficiency. The 8-bit ALU performs eight operations: ripple carry addition, ripple borrow subtraction, multiplication, XOR, left shift, right shift, NAND, and NOR. Each logic gate within the ALU is constructed using CMOS logic to enhance power efficiency and integration density. This paper provides a detailed description of the ALU's CMOS-based architecture, its key components, and the control mechanism for operation selection. Performance metrics, including speed, area efficiency, and power consumption, are analyzed to assess the ALU’s effectiveness in CMOS technology.
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Efficient Approximate Floating-Point Multiplier with Runtime Reconfigurable Frequency and Precision
Base Paper Abstract:
Deep Neural Networks (DNNs) perform intensive matrix multiplications but can tolerate inaccurate intermediate results to some degree. This makes them a perfect target for energy reduction by approximate computing. However, current research in this direction requires DNNs redesign and does not provide the flexibility for users to trade accuracy for energy saving. In this brief, we propose a runtime reconfigurable approximate floating-point multiplier and present details of its hardware implementation. The flexible computation precision is provided by our error correction module, which is controlled by reconfigurable clock signals. The circuit design solves the glitch and metastability problems. The proposed approximate multiplier with three precision levels is evaluated on Synopsys design compiler and Xilinx FPGA platforms. Experimental results demonstrate the advantages of our approach in terms of speed, hardware overhead, and power consumption, while ensuring a controllable accuracy loss for DNNs inferences.
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FPGA Implementation of 8×8 Truncated Multiplier Using Brent Kung Parallel Prefix Adder
Proposed Abstract:
Multiplication is a critical operation in many digital signal processing and machine learning applications, where fast and efficient computation is essential. However, conventional multipliers that compute n x n bit products result in significant hardware overhead and increased power consumption. To address these challenges, this paper proposes an FPGA implementation of an 8x8 truncated multiplier utilizing the Brent-Kung parallel prefix adder to improve both speed and resource efficiency. The proposed truncated multiplier limits the output to n bits, discarding the least significant bits and utilizing a variable correction technique to minimize the error introduced by truncation. By selectively summing the most significant columns, the design achieves a balance between accuracy and hardware efficiency, providing a reduced-area solution for approximate computing. The Brent-Kung parallel prefix adder is integrated into the multiplier architecture to optimize the carry propagation stage, reducing the overall critical path delay. This adder is known for its logarithmic depth, which significantly improves the speed of the summation process while using fewer logic gates compared to traditional adders. This design was implemented in Verilog HDL and synthesized on a Xilinx Virtex-5 FPGA platform. Comparative analysis with a conventional multiplier shows that the proposed truncated multiplier achieves a notable reduction in FPGA resource utilization, including logic elements and power consumption, without sacrificing significant accuracy. The architecture particularly suitable for applications where speed and low power consumption are paramount, such as real-time image processing, DSP systems, and machine learning accelerators.
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Efficient CRC-BCH Unified Encoder for Global Positioning System
Base Paper Abstract:
GPS uses ECCs to see if an error occurs when the data sent from the satellite reaches the user. Each message structure uses ECCs such as Hamming Code, CRC, BCH Code, and LDPC Code. If the satellite contains all of the encoders, it has a negative impact to the area and power consumption. Therefore, in this paper, we propose a CRC-BCH unified encoder for GPS, which is efficient in terms of space and power consumption. Since both the CRC and BCH encoders use shift registers, the design was made using this part. To replace the existing encoder, the CRC-BCH encoder must have the same output. To validate this, we used individual CRC and BCH encoders and confirmed that the generated output was identical to the output of the proposed encoder. The proposed CRC-BCH unified encoder was synthesized at an operating frequency of 400 MHz using the CMOS 28nm process. The synthesis results showed that it used 16.67% less area and consumed 19.68% less power than the existing encoder. Therefore, the proposed CRC-BCH unified encoder offers advantages in terms of satellite weight and energy efficiency.
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FPGA Implementation of Comparative Analysis and Performance Evaluation for Different LFSR Techniques
Proposed Abstract:
In this study, we explore the implementation and performance evaluation of various Linear Feedback Shift Register (LFSR) techniques on Field Programmable Gate Arrays (FPGAs). LFSRs are fundamental components in numerous digital applications, including cryptography, pseudorandom number generation, error detection, and secure communications. We specifically focus on five different LFSR methodologies: Fibonacci LFSR, Galois LFSR, Non-Linear Feedback Shift Register (NLFSR), Modular LFSR and Masked LFSR. Each technique is implemented on an FPGA platform, utilizing Verilog HDL for design specification and synthesis. The study begins with a detailed examination of the theoretical underpinnings and operational mechanisms of each LFSR technique, followed by their FPGA implementations. We then conduct a comprehensive performance analysis, focusing on critical parameters such as area utilization, power consumption, throughput, and randomness quality. The analysis reveals the strengths and trade-offs associated with each method, providing insights into their suitability for various applications. Our results demonstrate that while Fibonacci and Galois LFSRs offer simplicity and ease of implementation, more advanced techniques like NLFSR and Masked LFSR provide enhanced security features at the cost of increased complexity. The study concludes with recommendations on selecting the appropriate LFSR technique based on the specific requirements of the application, highlighting the balance between security, performance, and resource efficiency in FPGA-based designs.
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Design and Implementation of 32-bit CSPRNG using the PRESENT cipher with Dual Polynomial PRNG
Base Paper Abstract:
Random Number Generators (RNGs) are substantially used in many security domains, providing a fundamental source of unpredictability essential for tasks such as cryptography, simulations, and statistical analyses. The efficiency and quality of an RNG directly impact the reliability and security of diverse applications, making advancements in RNG design, as explored in this study, of significant importance for enhancing computational processes. This paper presents an innovative Pseudo-Random Number Generator (PRNG) that leverages the efficiency of two carefully selected Linear Feedback Shift Registers (LFSRs) and a connecting XOR gate. The investigation of five polynomials identified an optimal pair, resulting in a notable improvement of over 200X in the length of random bit sequences compared to a single LFSR-based PRNG. The Basys3 FPGA board with the xc7a35tcpg236-1 FPGA chip was used to implement and synthesize the proposed design. Two significant findings emerge from this research. Firstly, using variable polynomials demonstrates a huge enhancement in the duration of randomness, outperforming the impact of variable seeds. A noteworthy observation is that employing the same polynomials in different branches does not result in optimal results. Secondly, managing more seeds is associated with an increased area cost, underscoring the efficiency of handling two polynomials.
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Ultra Lightweight Cryptography: Exploring the Application and Optimization of the PRESENT Cipher
Proposed Abstract:
The PRESENT cipher, an ultra-lightweight block cipher, has been designed specifically for environments where resource constraints are a critical factor, such as RFID tags, sensor networks, and various IoT devices. Its compact design, featuring a 64-bit block size, 80-bit key, and 31 rounds, makes it particularly suitable for applications requiring minimal hardware resources, low power consumption, and moderate security. Unlike more robust ciphers like AES, which demand significant computational and memory resources, PRESENT strikes an optimal balance between efficiency and security for constrained devices. This paper explores the practical applications of the PRESENT cipher in secure communication protocols, device authentication, and data encryption in low-power systems. By synthesizing 16-bit, 32-bit, and 64-bit implementations on a Xilinx Virtex-5 FPGA, we demonstrate the cipher’s adaptability across a range of use cases, analyzing key performance metrics such as area, delay, and power consumption. Our findings indicate that PRESENT is highly effective in scenarios where traditional cryptographic solutions are too resource-intensive, offering a viable alternative for securing data in pervasive computing environments. PRESENT’s applications extend to securing communication in embedded systems, protecting sensitive information in contactless payment systems, and enabling secure data transmission in wireless sensor networks. The cipher’s lightweight design ensures that it can be implemented in devices with limited processing capabilities, making it an ideal choice for modern IoT applications. However, the trade-off between security and efficiency must be carefully considered. While PRESENT is suitable for applications with moderate security requirements, it may not provide the level of protection needed for high-security environments.
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Efficient Pseudo Random Number Generator (PRNG) Design on FPGA
Proposed Abstract:
Random Number Generators (RNGs) are substantially used in many security domains, providing a fundamental source of unpredictability essential for tasks such as cryptography, simulations, and statistical analyses. The efficiency and quality of an RNG directly impact the reliability and security of diverse applications, making advancements in RNG design, as explored in this study, of significant importance for enhancing computational processes. This paper presents an innovative Pseudo-Random Number Generator (PRNG) that leverages the efficiency of two carefully selected Linear Feedback Shift Registers (LFSRs) and a connecting XOR gate. The investigation of five polynomials identified an optimal pair, resulting in a notable improvement of over 200X in the length of random bit sequences compared to a single LFSR-based PRNG. The Basys3 FPGA board with the xc7a35tcpg236-1 FPGA chip was used to implement and synthesize the proposed design. Two significant findings emerge from this research. Firstly, using variable polynomials demonstrates a huge enhancement in the duration of randomness, outperforming the impact of variable seeds. A noteworthy observation is that employing the same polynomials in different branches does not result in optimal results. Secondly, managing more seeds is associated with an increased area cost, underscoring the efficiency of handling two polynomials.
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Optimized Dual Accumulator based RISC Architecture with Advanced Memory and Peripheral Operations
Proposed Abstract:
This paper presents an optimized Reduced Instruction Set Computer (RISC) architecture that leverages a dual accumulator design to enhance computational efficiency and performance. The architecture is scheduled to support advanced memory management and peripheral operations, addressing the growing need for high-speed data processing in embedded systems. The dual accumulator approach allows for parallel execution of arithmetic operations, reducing the number of instruction cycles and improving overall throughput. The architecture is designed with a focus on optimizing area, delay, and power consumption, making it suitable for resource-constrained environments. The proposed design is implemented using Verilog HDL and synthesized on the Xilinx Vivado platform targeting the Zynq FPGA. The architecture’s performance is verified through extensive simulation in Modelsim, and a comparative analysis is conducted to evaluate the improvements in key parameters such as area utilization, processing delay, and power efficiency. The results demonstrate that the optimized dual accumulator-based RISC architecture significantly outperforms traditional single accumulator designs, making it an ideal solution for modern embedded applications that require both high performance and low power consumption.
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Hardware-Efficient Logarithmic Floating-Point Multipliers for Error-Tolerant Applications
Base Paper Abstract:
The increasing computational intensity of important new applications poses a challenge for their use in resource restricted devices. Approximate computing using power-efficient arithmetic circuits is one of the emerging strategies to reach this objective. In this article, five hardware-efficient logarithmic floating-point (FP) multipliers are proposed, which all use simple operators, such as adders and multiplexers, to replace complex and costlier conventional FP multipliers. Radix-4 logarithms are used to further reduce the hardware complexity. These designs produce double-sided error distributions to mitigate error accumulation in complex computations. The proposed multipliers provide superior trade-offs between accuracy and hardware, with up to 30.8% higher accuracy than a recent logarithmic FP design or up to 68× less energy than the conventional FP multiplier. Using the proposed FP logarithmic multipliers in JPEG image compression achieves higher image quality than a recent logarithmic multiplier design with up to 4.7 dB larger peak signal-to-noise ratio. For training in benchmark NN applications, the proposed FP multipliers can slightly improve the classification accuracy while achieving 4.2× less energy and 2.2× smaller area than the state-of-the-art design.
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A High Speed CRC-32 Implementation on FPGA
Base Paper Abstract:
Cyclic Redundancy Check (CRC) is widely used for transmission error detection in various communication interfaces. As the transmission rate increases, accelerating CRC with lower resource consumption for high-speed interfaces becomes significant. This paper analyzes and implements a typical CRC algorithm (Stride-x) and designs a padding-zero strategy to support the input data length with multiples of byte. Besides, experiments are conducted to validate the proposed algorithm on Xilinx FPGA platforms. When stride is 1, the proposed algorithm outperforms a typical parallel CRC algorithm in throughput and resource consumption with various input bus widths (32/128/256 bits).
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High Performance FIR and IIR Filters Based on FPGA for 16 Hz Signal Processing
Base Paper Abstract:
The goal of the research to design and implement digital filters (Finite Impulse Response (FIR) and Infinite Impulse Response (IIR)) based on Field Programmable Gate Array (FPGA) by using the copulation between MATLAB/Simulink and Xilinx ISE Design Suite programs. low pass digital filter was implemented with different types of windowing methods that calculate the filter coefficient of FIR filter and different types of IIR filter with three numbers of filter order that are (5th order, 8th order, and 10th order). These different types of digital filters and filter orders are applied with the addition of a sine signal with a frequency of 16 Hz and a random noise signal. The work was done by two approaches: the first by simulation method through coupling between MATLAB/Simulink and Xilinx ISE Design Suite programs. While the second is by the practical method of loading these simulation block diagrams on FPGA. The performance of the work is measured by the difference between the sine signal and filtered signal and by the difference between the simulation results and practical results. Using FPGA with digital filters in this research gives a major advantage which is the simulation results equal to the practical results (Difference equal to zero).
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Soft-Error-Aware SRAM with Multinode Upset Tolerance for Aerospace Applications
Base Paper Abstract:
As technology scales down, the critical charge (QC) of vulnerable nodes decreases, making SRAM cells more susceptible to soft errors in the aerospace industry. This article proposes a Soft-Error-Aware 16T (S8P8N) SRAM cell for aerospace applications to address this issue. The properties of S8P8N are evaluated and compared with 6T, DICE, QUCCE12T, WEQUATRO, RHBD10T, RHBD12T, S4P8N, SEA14T, and SRRD12T. Simulation results indicate that all vulnerable nodes and key node pairs of the proposed cell can recover to their original states when affected by a soft error. Additionally, it can recover from key multinode upsets. The write speed of the proposed cell is found to be reduced by 20.3%, 50.1%, 74.1%, 63.7%, and 50.41% compared to 6T, DICE, QUCCE12T, WEQUATRO, and RHBD10T, respectively. The read speed of the proposed cell is found to be reduced by 56.6%, 52.2%, 62.5%, and 35.2% compared to 6T, SRRD12T, RHBD12T, and S4P8N, respectively. It also shows that the hold power of the proposed cell is found to be reduced by 14.1%, 13.8%, 17.7%, and 23.4% compared to DICE, WEQUATRO, RHBD10T, and RHBD12T. Furthermore, the read static noise margin (RSNM) of the proposed cell is found to be enhanced by 157%, 67%, and 32% compared to RHBD12T, SEA14T, and SRRD12T. All these improvements are achieved with a slight area penalty.
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Efficient Image Conversion and Restoration System with Hexadecimal Encoding and Quality Evaluation
Abstract:
The proposed work aims to facilitate the conversion of images into a hexadecimal format for efficient storage and manipulation, and subsequently restore them to their original form. This conversion is beneficial for reducing storage space and simplifying data transmission. The system supports multiple color spaces, including grayscale, RGB, and YCbCr, enhancing its versatility in image processing tasks. Users select an image file, which the system processes according to the selected mode: converting the image or its channels to a hexadecimal format and saving the data to files. During restoration, the system reads the hexadecimal files, reconstructs the image, and displays it. To ensure the fidelity of the restored images, the system computes and displays quality metrics such as Peak Signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE), and Structural Similarity Index (SSIM). This comprehensive solution provides an efficient method for image data handling and quality assessment, ensuring accurate and reliable image restoration.
Proposed System:The proposed system aims to facilitate the conversion of images into a hexadecimal format and subsequently restore them to their original form. This system supports multiple color spaces, including grayscale, RGB, and YCbCr, and evaluates the quality of the restored images using metrics such as Peak Signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE), and Structural Similarity Index (SSIM).
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Design and Evaluation of Inexact Computation based Systolic Array for Convolution
Base Paper Abstract:
Systolic Array (SA) architecture is a unique computation architecture where the inputs are continuously flowing, and the processing elements perform the desired computations in parallel. SA’s are prominently investigated due to the emergence of heavy and large processing elements for modern-day Convolution Neural Network (CNN) applications. Taking this cue, SA architectures of the order of kernel size and configured with approximate multipliers are investigated for image processing applications. The approximate array multiplier derived from approximate 4-2 compressors were employed to achieve hardware benefits without losing on the image quality metrics. The SA architecture is configured to the same size as filter kernels in a view to achieve maximum utilization, and the same is compared with other existing SA architectures for hardware metrics. The computational time for processing an image of size 256 × 256 was evaluated for approximated SA. This work investigates approximate SA for Gaussian smoothing and image outline feature extraction applications to showcase the reliability of the design. The novel approximate SA architecture is a step toward designing compact sized SoC designs for real-time image and video processing applications.
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Extraction of Fetal ECG from Abdominal and Thorax ECG Using a Non-Causal Adaptive Filter Architecture
Base Paper Abstract:
Extracting the Electrocardiogram (ECG) of a fetus from the ECG signal of the maternal abdomen is a challenging task due to different artifacts. The paper proposes a N-tap non-causal adaptive filter (NC-AF) that update the weight by considering the N number of past weights and N − 1 number of the reference signal and error signal samples after the processing sample number n. Using the maternal abdominal signal as the primary signal and thorax signal as the reference input, the output e(n) is obtained from the mean of N number of errors. The filtering performance of NC-AF was evaluated using the Synthetic dataset and Daisy dataset with the metrics such as correlation coefficient (γ), peak root mean square difference (PRD), the output signal to noise ratio (SNR), root mean square error (RMSE), and fetal R-peak detection accuracy (FRPDA). The NC-AF provides a maximum correlation coefficient, PRD, SNR, RMSE and FRPDA of 0.9851, 83.04%, 8.52 dB, 0.208 and 97.09% respectively with filter length N = 38. The paper also proposes the architecture of NC-AF that can be implemented in hardware like FPGA. Further, the NC-AF was implemented on Virtex-7 FPGA and its performance is evaluated in terms of resource utilization, throughput, and power consumption. For filter length N = 38 and word length L = 24, the maximum performance of the filter can be attained with a power consumption of 1.287W and a maximum clock frequency of 139.47 MHz.
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Implementation of High-Precision MFCC Feature Extraction Using FPGA for Speech Recognition
Proposed Abstract:
Speaker recognition is one of the technologies that may be used for biometric identification, and it offers higher application possibilities in many sectors. At the moment, the implementation of the speaker identification algorithm on the hardware is mostly dependent on the SOC of the FPGA. An FPGA-based real-time technique for extracting acoustic characteristics is presented in this research. The method is based on MFCC, which stands for Mel Frequency Cepstral Coefficients. The trials have shown that the FPGA-based MFCC calculation has a high level of accuracy; the purpose of this study is to enhance the performance assessment of MFCC by making use of novelty-based architecture. In this study, a technique for FPGA-based speech recognition is provided. This approach was developed by investigation and analysis of the speaker recognition algorithm. The IFFT, the Mell filter, the DFT, the derivatives, and the Hamming Window with pre-emphasis are every aspect of this approach. This proposed MFCC will be constructed with an AHB interface in order to facilitate higher access DMA Controller when it is used in SOC applications. This work was carried out using Verilog HDL, and it was generated with Xilinx Vivado FPGA. Additionally, all of the parameters were analyzed and compared with regard to area, latency, and power.
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Parallel Pipelined Architecture and Algorithm for Matrix Transposition Using Registers
Base Paper Abstract:
In this brief, we present a new algorithm and architecture for continuous-flow matrix transposition using registers. The algorithm supports P-parallel matrix transposition. The hardware architecture reaches the theoretical minimums in terms of latency and memory. It is composed of a group of identical cascaded basic swap circuits, whose stages are determined by the corresponding algorithm, and can be controlled via a set of counters. Compared with the state-of-the-art architecture, the proposed architecture supports matrices whose rows and columns are integer multiples of P. Here P can be arbitrary, including but not limited to power-of-two integers. Moreover, our results provide additional insight into continuous-flow non-square matrix transposition.
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A Reversible Processor Architecture and Its Reversible Logic Design
Proposed Abstract:
This paper presents the design and FPGA implementation of a 16-bit reversible processor architecture employing Fredkin, Feynman, and PERES gate architectures for reversible logic design. Reversible computing offers promising advantages in terms of energy efficiency and information loss prevention, making it suitable for various emerging computing paradigms. The proposed processor architecture encompasses a carefully crafted instruction set, data path, and control logic, all realized using reversible logic gates. Key components such as the ALU, register file, and memory elements are designed with an emphasis on reversibility. The design is implemented using Hardware Description Languages (HDLs), targeting a specific FPGA platform. The paper outlines the design methodology, gate-level implementation details, memory design considerations, FPGA synthesis, and testing procedures. Furthermore, it discusses optimization strategies and presents simulation results to validate the functionality and efficiency of the proposed reversible processor architecture. This work contributes to the advancement of reversible computing and provides insights into the practical realization of reversible processor architectures on FPGA platforms.
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Design and Analysis of a Majority Logic Based Imprecise 6-2 Compressor for Approximate Multipliers
Base Paper Abstract:
Approximate computing is an emerging paradigm for trading off computing accuracy to reduce energy consumption and design complexity in a variety of applications, for which exact computation is not a critical requirement. Different from conventional designs using AND-OR and XOR gates, the majority gate is widely used in many emerging nanotechnologies. An ultra-efficient 6-2 compressor is proposed in this paper. It is composed of two majority gates that lead to low energy consumption and high hardware efficiency. The proposed compressor is utilized in the approximate partial product reduction of a modified 8×8 Dadda multiplier with a truncated structure. Experimental results show that this multiplier realizes a significant reduction in hardware cost, especially in terms of power and area, on average by up to 40% and 31% respectively, compared to exact and state-of-the-art designs. The application of image multiplication is also presented to assess the practicability of the multiplier. The results show that the proposed multiplier results in images with higher quality in peak signal to noise ratio (PSNR) and mean structural similarity index metric (MSSIM) compared to other designs.
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MInSC: A VLSI Architecture for Myocardial Infarction Stages Classifier for Wearable Healthcare Applications
Base Paper Abstract:
Myocardial Infarction (MI) is a critical heart abnormality causing millions of fatalities worldwide every year. MI progress in three stages based on its severity causing several changes in an Electrocardiogram (ECG) signal. It is very critical to capture these variations, which requires continuous monitoring of the ECG signal of the patient. Therefore, it becomes imperative to develop a low power VLSI architecture to address the prognosis of MI. In this brief, for the first time, an area and power efficient design of a five stage classifier is proposed, which detects the progression of various stages of MI using ECG beats in real time. The proposed architecture has an area and total power utilization of 1.38mm2 and 5.12µW, respectively at SCL 180nm Bulk CMOS technology. The low power and area requirements and multiclass classification capability of the proposed design make it suitable to be used in wearable devices.
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Fast and Hardware-Efficient Variable Step Size Adaptive Beamformer
Base Paper Abstract:
Constant step size least mean square (CSS-LMS) is one of the most popular adaptive beamforming algorithms. However, for varying channel signal-to-noise ratios (SNRs), the CSS algorithms are not effective, and there is a need for variable step size (VSS) algorithms. The VSS algorithms provide extremely deep nulls for the interferences; however, they are complex to implement on hardware. Hence, this paper proposes two hardware-efficient variable step size algorithms, namely, efficient variable step size LMS (EVSS-LMS) and reduced complexity parallel LMS (EVSS-RC-pLMS). The proposed EVSS algorithms eliminate the complex operations of VSS algorithms like division and exponential and approximate them to simpler operations. Further, MATLAB simulations demonstrate accelerated convergence, deep nulls, a lower error floor, and better performance in varying SNR environments for the proposed algorithms. Additionally, the finite precision radiation patterns are similar to infinite precision. Hardware synthesis results show the outstanding performance of EVSS in terms of resource utilization on the Xilinx Artix-7 FPGA.
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Design of High Speed 8-bit Vedic Multiplier using Brent Kung Parallel Prefix Adder
Base Paper Abstract:
One of the primary purposes of a digital signal processing system is multiplication. The multiplier’s performance affects the DSP system’s overall performance. Therefore, it is crucial to create an effective and quick multiplier implementation design. Vedic mathematics can be used to simplify complex computations so that they are easier to perform verbally. Urdhva Triyambakam is the multiplication algorithm used in Vedic math. In this paper, we employing Brent Kung adder to enhance the Vedic multiplier’s performance. The Urdhva Tiryagbhyam sutra is being used in place of other multiplication strategies since it applies to all instances of algorithms for N x N bit numbers and produces the least amount of latency. Four 4-bit vedic multipliers, two 8-bit Brent Kung adders, one 4-bit Brent Kung adder, and an OR gate are used to create an 8-bit vedic multiplier. A 4-bit vedic multiplier is created similarly by combining four 2-bit vedic multipliers, two 4-bit Brent Kung Adders, one 2-bit Brent Kung Adder, and one OR gate. These four-bit vedic multipliers are then combined to form an eight-bit vedic multiplier. After that, Xilinx Vivado Software is used to simulate and synthesis the 8 x 8 Vedic Multiplier, which was coded in Verilog HDL. The proposed Vedic Multiplier is outperformed in terms of speed when compared to related works.
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Design and Implementation of an 8-bit Approximate Wallace Tree Multiplier for Energy Efficient Deep Neural Networks
Base Paper Abstract:
Approximate arithmetic computing circuits and architectures have been proven to be energy efficient designs for Deep Neural Networks (DNNs) which are error resilient. In this paper, an approximate 8-bit Wallace Multiplier has been proposed and designed in 90nm CMOS technology for energy efficiency. The proposed 8-bit approximate multiplier design consumes ~32% less energy in comparison to an accurate 8-bit Wallace Tree multiplier with less than 20% Mean Relative Error (MRE).
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An Optimization in Conventional Shift &Add Multiplier for Area-Efficient Implementation on FPGA
Base Paper Abstract:
FPGA is familiar with prototyping and implementing simple to complex DSP systems. The FPGA based design may be highly affected by factors that include selection of an FPGA board, Electronic Design Automation Tool and the Programming Techniques to optimize the algorithm. The algorithm optimization results in a more compact design regarding the area and achieved frequency. In DSP algorithms optimization, the major bottleneck is the multiplier complexity evident in, for example - FIR, IIR, FFT, and others. Research shows much work on multiplier optimization. Despite all possible optimization techniques, the multiplier consumes tremendous resources when translated on hardware, with more power consumption and observed delay. The proposed work is novel in that it brings resources optimization in a familiar shift and add multiplier algorithm by implementing the design in FPGA and comparing the results with the existing shift, and add a multiplier. In the implementation of the design, Xilinx Vertex -7 FPGA is used along with ISE 14.2 simulators. The parameters to compare are the Lookup tables (Logic element of FPGA), adder/subtractors and the multiplexers, along with performance characters, like the operating frequency, delay and total levels of logic (path travelled by the signal in register transfer level). The output shows that the anticipated design is an excellent alternative to the conventional shift and add algorithm.
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FPGA Implementation of TFT 1.8 inch SPI 128×160 Display ROM Interface
Simple Description:
This ST7735R is a display controller used in small TFT (Thin-Film Transistor) LCD displays. It is often used in combination with microcontrollers or FPGAs to drive these displays. The controller supports the Serial Peripheral Interface mode of communication for sending commands and data to the display. This TFT display helps with a greater number of image and video processing applications. Here we have implemented this TFT display in FPGA hardware implementation using Verilog HDL with a novelty-based architecture design. Finally shown the output with TFT Display.
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FPGA Implementation of Spread Spectrum Clock Generator with Onion Modulation
Proposed Abstract:
A Spread Spectrum Clock Generator (SSCG) is used in electronics to purposefully vary the frequency of a clock signal via modulation. Modulation is accomplished by dispersing the energy of the signal throughout a spectrum of frequencies rather than focusing it on a certain frequency. The main objective of using the spread spectrum approach in clock generation is to minimize electromagnetic interference (EMI) and enhance electromagnetic compatibility (EMC) in electronic systems. The main reason for using many layers of modulation in spread spectrum clock production, regardless of whether the name "Onion Modulation" is used, is to provide a more advanced and adaptable method for reducing electromagnetic interference. The primary design feature of the onion wave is that the core portion of the waveform has the least steep slope, which serves to generate the output. In order to optimize the frequency effect design, the conventional approach involves using a memory ROM to regulate the slope and obtain the desired onion waveform. This current methodology necessitates substantial memory allocation and an intricate architecture, resulting in higher power consumption. The proposed method presents a unique architecture for onion modulation, which offers reduced logic size and power usage. This architecture was created using Verilog HDL, tested using Modelsim, and implemented using the Xilinx Vertex-5 FPGA.
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An Efficient Image Encryption Algorithm Based on Innovative DES Structure and Hyperchaotic Keys
Base Paper Abstract:
In fact, as a traditional encryption method, DES has been certified as an unsuitable tool for ciphering due to its smaller key space. Further, in concern of the real-time encryption in the current fast communication era, such as 5G, long-time as well as large computational level processes are not gotten into the consideration. As a result, an innovative encryption structure with hyperchaotic keys for efficient encryption is constructed, where the frame of DES structure is applied, the plain image is shuffled through row and column directions in the first round, and then rearranged to be 64 blocks to fit into the frame of DES structure for 4 rounds ciphering with hyperchaotic subkeys. Also, in order to encrypt the content of the image at the block level, a set of alternative S-box has been produced in this article as well. The simulation results indicate that the proposed scheme is feasible and reliable for digital image encrypting, not only a large key space can be obtained, but also the low correlation of the adjacent contents can be achieved, and further, in comparison of several existing approaches, less-computational resource can be proven as well. In particular, due to the innovative DES structure, the computational speed is significantly faster than the original DES algorithm and many other chaos-based image ciphering schemes.
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An Innovative Area Efficient Pixel Shuffling Method for Image Encryption Algorithm
Proposed Abstract:
In image processing and computer vision, pixel shuffling is a method used to increase an image's resolution without adding more parameters or network complexity. With this technique, a low-quality image's pixels are rearranged to produce an output with a better resolution. Pixel shuffling has proven successful in a number of applications, such as image synthesis, super-resolution, and style transfer. Its simplicity and efficiency make it an attractive option for tasks where increasing image resolution is essential, while avoiding the computational overhead associated with more complex architectures. The image line buffer based pixel shuffling technique presented in this study is an alternative to the classic method, which takes up more logic space in VLSI implementations. This proposed method splits and reconstructs the source photos using a 5x5 image line buffer. With the use of block interleave techniques, this pixel shuffling approach handled row and column sequence using this 5x5 picture line buffer. In conclusion, this study was compared with the PSNR and SSIM value; comparisons of logic sizes for area, latency, and power were also examined.
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FPGA Implementation of 64 Block Data Encryption Standard Algorithm
Proposed Abstract:
The Data Encryption Standard (DES) is widely recognized as the inaugural and prevailing symmetric key method used for the cryptographic processes of encrypting and decrypting digital data. Despite its lack of security against determined attackers in contemporary times, the use of this method persists in older systems. This work introduces a novel implementation of the Data Encryption and Decryption Standard algorithm using Field Programming Gate Arrays (FPGAs) that prioritizes security, high throughput, and space efficiency. The suggested solution involves the creation of a system that utilizes a block size of 64 bits and a key length that is also 64 bits. Additionally, the system operates with a data width of 64 bits. This achievement is accomplished by integrating the notion of pipelining with time variable permutations, and then comparing it with previously shown encryption techniques. The permutations undergo temporal variations under the control of the cryptographer. Hence, the cipher text also undergoes alteration while the key and plaintext remain constant. The algorithm under consideration has been successfully executed on the Xilinx Vetex-5 Field-Programmable Gate Array (FPGA) platform. The findings of this study indicate that the suggested implementation exhibits exceptional speed in comparison to other hardware implementations. Additionally, it demonstrates superior area efficiency and significantly enhanced security measures.
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FPGA Implementation of Image Line Buffer to Split and reconstruct a 3×3 size of image pixel with using FIFO Design
Proposed Abstract:
Image line buffers are used in several kinds of image processing applications, particularly where operations must be executed on a per-line basis in order to optimize efficiency. There are many typical applications associated with this technology, including real-time video processing, image filtering, edge detection, computer vision, memory optimization, parallel processing, compression algorithms, and medical imaging. In the context of image and video processing applications, the use of image line buffers may contribute to the optimization of operations when dealing with a continuous stream of frames processed in real time. In the context of image processing, convolutional processes are often used for tasks like as image filtering and blurring. These operations are typically carried out on a per-pixel basis, wherein the value assigned to each pixel is determined by the values of its adjacent pixels. The proposed structure was created using a First-In-First-Out (FIFO) based approach, aiming to decrease the number of logic sizes and complexity in Very Large Scale Integration (VLSI) design architecture. The conversion of design images to hexadecimal and hexadecimal to image format is accomplished using MATLAB GUI applications. These applications also facilitate the comparison of Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) values. The internal architecture of the system is implemented using Verilog Hardware Description Language (HDL). Additionally, the simulation is conducted using Modelsim. Furthermore, the system's performance parameters, including area, delay, and power consumption, are compared with those of the Xilinx Vertex-5 Field Programmable Gate Array (FPGA).
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Toward the Multiple Constant Multiplication at Minimal Hardware Cost
Base Paper Abstract:
Multiple Constant Multiplication (MCM) over integers is a frequent operation arising in embedded systems that require highly optimized hardware. An efficient way is to replace costly generic multiplication by bit-shifts and additions, i. e. a multiplier less circuit. In this work, we improve the state of-the-art optimal approach for MCM, based on Integer Linear Programming (ILP). We introduce a new low-level hardware cost metric, which counts the number of one-bit adders and demonstrate that it is strongly correlated with the LUT count. This new model permitted us to consider intermediate truncations that permit to significantly save resources when a full output precision is not required. We incorporate the error propagation rules into our ILP model to guarantee a user-given error bound on the MCM results. The proposed ILP models for multiple flavors of MCM are implemented as an open-source tool and, combined with an automatic code generator, provide a complete coefficient-to-VHDL flow. We evaluate our models in extensive experiments, and propose an in-depth analysis of the impact that design metrics have on synthesized hardware.
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FPGA Implementation of Single Precision Floating Point Multiplier using High Speed Parallel Prefix Adder based Wallace Tree Multiplier
Base Paper Abstract:
In this paper present, an efficient implementation of single precision method of floating point multiplier target for Xilinx Vertex 5 FPGA using Verilog HDL. The floating point implementation will cover up with 23-bit exponent, 8-bit mantissa, and 1 sign bit. This proposed architecture implement with high speed parallel prefix adder based Wallace Tree Multiplier. a Wallace tree multiplication will provide effective terms of low logic sizes and more speed of operations. In a recent arithmetic applications based circuit design will have more demand with high speed and low area, in this manner the proposed approach of this work will improve the speed of Wallace tree multiplier using 4:2 compressor method without degrading its area parameter. Thus, the proposed method will integrate more efficient and more reliable Kogge stone parallel prefix, Brent kung parallel prefix, Sklansky parallel prefix addition operation in the Wallace tree multiplication on final addition stage at 16-bit data width. Finally, done this floating point multiplier architecture with Wallace tree architecture included normalized rounding method and to reduce area, delay and power. The error difference will have analyzed using Modelsim Software, and analyses optimized logic size's, delay and power consumptions.
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Hybrid Protection of Digital FIR Filters
Base Paper Abstract:
A digital finite impulse response (FIR) filter is a ubiquitous block in digital signal processing applications and its behavior is determined by its coefficients. To protect filter coefficients from an adversary, efficient obfuscation techniques have been proposed, either by hiding them behind decoys or replacing them by key bits. In this article, we initially introduce a query attack that can discover the secret key of such obfuscated FIR filters, which could not be broken by the existing prominent attacks. Then, we propose a first of its kind hybrid technique, including both hardware obfuscation and logic locking using a point function for the protection of parallel direct and transposed forms of digital FIR filters. Experimental results show that the hybrid protection technique can lead to FIR filters with higher security while maintaining the hardware complexity competitive or superior to those locked by prominent logic locking methods. It is also shown that the protected multiplier blocks and FIR filters are resilient to existing attacks. The results on different forms and realizations of FIR filters show that the parallel direct form FIR filter has a promising potential for a secure design.
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Smart Intelligent and Adaptive Traffic Controller using FPGA
Proposed Abstract:
Traffic management is a critical aspect of modern urban infrastructure, and the ever-increasing volume of vehicles on the road demands innovative and adaptive solutions. This work presents a novel approach to traffic control using Field-Programmable Gate Arrays (FPGAs) as the core technology. The proposed system leverages the capabilities of FPGAs to create a Smart, Intelligent, and Adaptive Traffic Controller that can revolutionize urban traffic management. One of the key features of the proposed work is its adaptability. The system can dynamically adjust traffic signal timings and lane allocations in response to changing traffic patterns of 4-way road conditions with the help of sensor inputs. This methodology adaptability enhances road safety and minimizes traffic delays. The use of FPGA technology in the Traffic controller provides several advantages, including high computational performance, low power consumption, and the ability to reconfigure the system as traffic management needs evolve. Additionally, the system is highly scalable and can be deployed in various urban settings.
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Design and Implementation of Arithmetic Logic Unit in HDL
Proposed Abstract:
Arithmetic logic unit (ALU) is an important part of all digital gadgets and applications. This paper presents the design and implementation of an 8-bit Arithmetic Logic Unit (ALU) with a capability to perform eight distinct operations. ALUs are fundamental components in the central processing units (CPUs) of microprocessors and are responsible for executing arithmetic and logical operations. The primary objective of this research is to design an efficient and versatile 8-bit ALU that can execute a wide range of operations while optimizing for performance and area efficiency. The proposed 8-bit ALU is designed to perform the following eight operations: Ripple carry addition, Ripple borrow subtraction, Array multiplication, XOR operation, left shift, right shift, NAND operation and a logical NOR operation. The research presents a detailed description of the ALU's architecture, its constituent components, and the control mechanism for selecting operations. Performance metrics, such as speed, area efficiency, and power consumption, are analyzed and compared with Xilinx FPGA.
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Low power Dadda multiplier using approximate almost full adder and Majority logic based adder compressors
Base Paper Abstract:
An Approximate computing is widely used to have energy-efficient system design in Very Large-Scale Integration (VLSI). This approach is best suited for signal processing and multimedia applications where low power consumption is the main concern. Faster and significant results can be obtained from an approximate computing at the cost of reduced accuracy. In this work, we proposed a very novel design approaches based on various monolithic 4:2 compressors. Proposed approach is applied to have reduced stages in the partial product multiplication. Proposed Monolithic compressor had outperformed over various 4:2 compressors. Our proposed method is based on majority logic based with the use of Dadda multiplication. A new-partial product reduction format is implemented by this multiplier, which reduces the maximum output delay. This method of approach significantly reduces the utilization of number of MOSFETs compared to other multiplier such as Wallace Tree Multipliers. Simulation results are compared with conventional Dadda multiplier and ML based 4:2 compressors. Proposed approximate computing based almost full adder based majority logic based Dadda multiplier achieves reduction of 60.93% in area utilization 72.48% reduction in dynamic power reduction while processing time is also reduced by 72.98%. Dadda multiplication outperforms the other compressors.
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Efficient Design of Behavioral Clock Divider for Multiple Frequency
Proposed Abstract:
Frequency dividers are of utmost importance in frequency synthesizers that are based on phase locked loops. The use of dual modulus presales enhances the versatility of the design in both integer and Fractional-N frequency synthesizers. The selection of an acceptable division ratio is dependent upon the channel spacing and frequency range of the synthesizer. There are several techniques for division in electronic systems, including the injection locked frequency divider (ILFD), complementary ILFDs, flip flop based dividers, dual modulus dividers, and modular dividers. Therefore, these approaches possess some advantages and disadvantages, such as reduced jitter, a restricted frequency tuning range, increased circuit size due to the addition of an LC tank circuit, increased power consumption, and lower quality factor. This work aims at addressing certain issues pertaining to clock dividers and proposes a unique design that utilizes a multiple digital frequency divider based on D flip flops. The architectural design is predicated on the use of a phase shifting mechanism using a D flip flop, which effectively controls the division ratio. The present study involves the use of a preliminary phase shifting melody in conjunction with the Digital Clock Manager (DCM). The auto tuning strategy described in this study aims to adjust the phase difference between two differential clock signals. By intentionally inducing metastability in one or more flip flops, the proposed approach utilizes a digital clock manager in a clock divider to mitigate the effects of metastability and reduce jitter across multiple tuning frequencies. Furthermore, it is worth noting that the logic size and power consumption required for its operation are significantly reduced.
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FPGA Heart Rate Monitoring (Pre Processing – QRS Detection Stage)
Base Paper Abstract:
The continuous monitoring of cardiac patients requires an ambulatory system that can automatically detect heart diseases. This study presents a new field programmable gate array (FPGA)-based hardware implementation of the QRS complex detection. The proposed detection system is mainly based on the Pan and Tompkins algorithm, but applying a new, simple, and efficient technique in the detection stage. The new method is based on the centered derivative and the intermediate value theorem, to locate the QRS peaks. The proposed architecture has been implemented on FPGA using the Xilinx System Generator for digital signal processor and the Nexys-4 FPGA evaluation kit. To evaluate the effectiveness of the proposed system, a comparative study has been performed between the resulting performances and those obtained with existing QRS detection systems, in terms of reliability, execution time, and FPGA resources estimation. The proposed architecture has been validated using the 48 half-hours of records obtained from the Massachusetts Institute of Technology - Beth Israel Hospital (MITBIH) arrhythmia database. It has also been validated in real time via the analogue discovery device.
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Design of Approximate Restoring Divider
Proposed Abstract:
Approximate computing is an emerging paradigm in error-tolerant applications that leads to power-efficient designs without significant loss in quality. The divider in these applications have complex hardware and more latency among the computational blocks resulting in power consumption. Hence approximating the division module would lead to designs with vastly improved power efficiency. A new approximate subtractor (AxSUB) is proposed in this paper with the intent to reduce the hardware complexity while achieving accuracy within permissible limits. The proposed AxSUB and existing approximate subtractor units are used in the restoring array division (RAD) architecture to prove the efficacy of the AxSUB. This proposed architecture design with 8/4 approximate divider using Verilog HDL and synthesized using Xilinx Spartan 6 FPGA, and proved the performance of area, delay and power.
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Hamming based Single Fault Error Correction Code
Proposed Abstract:
Signal processing and communication systems often use digital filters. In certain circumstances, the dependability of such systems is essential, prompting the construction of fault-tolerant filters. Many methods that take use of the structure and characteristics of the filters to achieve fault tolerance have been put forward throughout the years. Technology advances permit more intricate systems with several filters. It is typical for some of the filters in such complicated systems to function in simultaneously, for instance by using the same filter on several input signals. Recently, a straightforward method for achieving fault tolerance was given that takes use of the existence of parallel filters. This paper expands on that concept to demonstrate how error correction codes (ECCs), in which each filter is the equivalent of a bit in a conventional ECC, may be used to secure parallel filters. When there are several parallel filters operating simultaneously, this new technique enables more effective protection. The efficiency of the method in terms of protection and implementation cost is assessed using a case study of parallel finite impulse response filters.
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FPGA Implementation of High Performance Reversible logic based 16×16 Array Multiplier
Proposed Abstract:
In this recent technology of digital gadgets and digital signal processing and image processing method will have more priority in arithmetic operation, such as multiplication, divisions, addition and subtractions. In this operations of arithmetic unit will have number of garbage signal with more memory logic element, due to this problem these arithmetic operations will take more area, delay and power in VLSI system design. Here, this proposed work will present a arithmetic operation using reversible logic method, thus it take memory less logic and less garbage elements, therefore here this reversible logic method will integrated using reversible half adders and full adder in array multiplier and proved the performance with less garbage signals. Finally, this work will have integrated in Verilog HDL, simulated in Modelsim and Synthesized in Xilinx FPGA, and also compared all the parameter in terms of area, delay and power.
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FPGA Implementation of 8×8 Truncated Multiplier
Proposed Abstract:
The operation of multiplication is an often encountered need in the field of digital signal processing. Parallel multipliers provide a rapid approach for performing multiplication operations, while demanding a significant amount of space in VLSI (Very Large Scale Integration) implementations. In the majority of signal processing applications, there is a preference for using a rounded result in order to prevent an increase in the size of the word. Therefore, an important goal in the design process is to minimize the spatial demand of the rounded output multiplier. This study introduces a novel approach to parallel multiplication that efficiently calculates the products of two n-bit values by selectively summing the most important columns using a variable correction technique. This research furthermore includes a comparative analysis of the implementation of 8X8 conventional and truncated multipliers using Verilog Hardware Description Language (HDL) on Field Programmable Gate Arrays (FPGAs). The shortened multiplier demonstrates a much greater decrease in device consumption as compared to the regular multiplier. A conventional multiplier performs computations on n x n bits and produces a weighted sum of the output, consisting of 2n bits. In contrast, a truncated multiplier generates an output of just n bits from the n x n bit input. The use of logic gates in both internal and external hardware design will be decreased. Truncated multipliers provide a viable approach for achieving significant reductions in FPGA resources, latency, and power consumption compared to regular parallel multipliers, particularly in scenarios where the complete accuracy provided by the standard multiplier is unnecessary.
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Design of SEU Tolerant 2D-FFT in SRAM-based FPGA
Base Paper Abstract:
2-Dimensional fast Fourier transform (FFT) has been widely used in radar signal process. Due to the need for high performance, field programmable gate array (FPGA) is an ideal hardware device for this application. For space-borne radar platform such as synthetic aperture radar (SAR), single-event upsets (SEUs) can cause lots of soft errors in static random access memory (SRAM) based FPGA. As to this, protecting the 2D-FFT implemented in FPGA from SEUs is very important. In this article, we analyze the critical weakness induced by SEUs in the 2D-FFT process, and then a 2D-FFT design with high SEU resilience is presented. The design utilizes the advantage of several anti-SEU methods. For butterfly control in FFT, partially triple modular redundancy (TMR) is used. For data buffers, error correction code (ECC) is applied to read and write operation. Furthermore, safe finite state machine (FSM) is adopted by important control registers. Fault injection results show that all these reinforcement technologies contribute to enhance the ability to mitigate the SEU effects.
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FPGA Implementation of D8PSK Demodulator
Base Paper Abstract:
Differential phase shift keying (DPSK) is a modulation scheme that facilitates non coherent demodulation and is employed for various applications such as Wireless Local Area Networks (WLANs), Bluetooth and RFID communication. In this paper, design, development and hardware implementation of a new demapping scheme for Differential 8-PSK (D8PSK) demodulator on a Zynq 7000 FPGA based ZED board is proposed using the concepts of model based design. The proposed work can be easily extended to other M-ary DPSK schemes.
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A Lightweight True Random Number Generator for Root of Trust Applications
Base Paper Abstract:
There are many schemes proposed to protect integrated circuits (ICs) against an unauthorized access and usage, or at least to mitigate security risks. They lay foundations for hardware roots of trust whose crucial security primitives are generators of truly random numbers. In particular, such generators are used to yield one-time challenges (nonces) supporting the IC authentication protocols employed to counteract potential threats such as untrusted users accessing ICs. However, IC vendors raise several concerns regarding the complexity of these solutions, both in terms of area overhead, the impact on the design flow, and testability. These concerns have motivated this work presenting a simple, yet effective, all-digital lightweight and self-testable random number generator to produce a nonce. It builds on a generic ring generator architecture, i.e., an area and time optimized version of a linear feedback shift register, driven by a multiple-output ring oscillator. A comprehensive evaluation, based on three statistical test suits from NIST and BSI, show feasibility and efficiency of the proposed scheme and are reported herein.
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Implementation of a Multipath Fully Differential OTA in 0.18-μm CMOS Process
Base Paper Abstract:
This brief implements a highly efficient fully differential trans conductance amplifier, based on several input-to-output paths. Some traditional techniques, such as positive feedback, nonlinear tail current sources, and current mirror-based paths, are combined to increase the trans conductance, thus leading to larger dc gain and higher gain bandwidth (GBW) product. Two flipped voltage-follower (FVF) cells are employed as variable current sources to provide class-AB operation and adaptive biasing of all other drivers. The proposed structure includes several input-to-output paths that play the role of dynamic current boosters during the slewing phase, thus improving the slew rate (SR) performance. The circuit was fabricated in a TSMC 0.18-µm CMOS process with a silicon area of 54.5 × 30.1 µm. Experimental results show a GBW of 173.3 MHz, a dc gain of 72.7 dB, and an SR of 139.4 V/µs for a capacitive load of 2 × 5 pF. The proposed circuit consumes 619 µW of power, under a supply voltage of 1.8 V.
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Hardware Architecture for Adaptive Edge Directed Interpolation Algorithm
Base Paper Abstract:
Demosaicking refers to the reconstruction of full color image by the incomplete color samples produced by the single-chip image sensor. So there is a need of interpolation to obtain the missing color pixels. In this work a hardware architecture has been proposed for the adaptive edge-directed interpolation algorithm which uses an edge estimator for the interpolation. The proposed hardware architecture is implemented in Verilog HDL (Hardware Description Language) and synthesized using Cadence Genus compiler with 90nm technology in typical mode. For the proposed architecture, the power dissipation is found to be 26 mW, delay is 7.2 ns and requires 2.3 mm2 area. The demosaicked images obtained using the proposed architecture is observed to have better image quality in terms of peak signal-to-noise ratio and structural similarity while comparing with existing architectures.
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ReAdapt: A Reconfigurable Datapath for Runtime Energy-Quality Scalable Adaptive Filters
Base Paper Abstract:
This paper proposes ReAdapt–a reconfigurable datapath architecture for scaling the energy-quality trade-off of adaptive filtering at runtime. The ReAdapt can dynamically select four adaptive filtering algorithms for gradating complexity levels during runtime by reconfiguring the processing flow in its datapath and by blocking the switching activity (e.g., reducing the CMOS dynamic power) of unused modules with data-gating. The ReAdapt proposal can scale the energy-quality trade-off by choosing the following four different levels of filter algorithms complexity: 1) least mean square (LMS); 2) partial update normalized LMS (PU-NLMS); 3) set-membership normalized LMS (SM-NLMS); 4) normalized LMS (NLMS). The ReAdapt architecture reuses common modules of each adaptive filter, resulting in a compact VLSI hardware implementation. The ReAdapt architecture operation is implemented in a case-study for interference mitigation for electroencephalogram (EEG) signal processing. The hardware synthesis results show an increase of 6.80 times in throughput and at least a reduction of 2.84 times in energy per operation compared with the state-of-the-art adaptive filters. This paper also investigates the benefits of dynamically reconfiguring the four ReAdapt operating modes at runtime for different levels of signal-to-noise ratio (SNR) for the processed signals. We also demonstrate that dynamically reconfiguring the ReAdapt operating modes during runtime results in an optimal energy-quality trade-off which is advantageous over the conventional single static mode.
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A Pipelined Reduced Complexity Two Stages Parallel LMS Structure for Adaptive Beam forming
Base Paper Abstract:
In this paper, we propose a reduced complexity parallel least mean square structure (RC-pLMS) for adaptive beamforming and its pipelined hardware implementation. RC-pLMS is formed by two least mean square (LMS) stages operating in parallel (pLMS), where the overall error signal is derived as a combination of individual stage errors. The pLMS is further simplified to remove the second independent set of weights resulting in a reduced complexity pLMS (RC-pLMS) design. In order to obtain a pipelined hardware architecture of our proposed RC-pLMS algorithm, we applied the delay and sum relaxation technique (DRC-pLMS). Convergence, stability and quantization effect analysis are performed to determine the upper bound of the step size and assess the behavior of the system. Computer simulations demonstrate the outstanding performance of the proposed RC-pLMS in providing accelerated convergence and reduced error floor while preserving a LMS identical O(N) complexity, for an antenna array of N elements. Synthesis and implementation results show that the proposed design achieves a significant increase in the maximum operating frequency over other variants with minimal resource usage. Additionally, the resulting beam radiation pattern show that the finite precision DRC-pLMS implementation presents similar behavior of the infinite precision theoretical results.
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Two Efficient Approximate Unsigned Multipliers by Developing New Configuration for Approximate 4:2 Compressors
Base Paper Abstract:
Approximate computing is a promising approach for reducing power consumption and design complexity in applications that accuracy is not a crucial factor. Approximate multipliers are commonly used in error-tolerant applications. This paper presents three approximate 4:2 compressors and two approximate multiplier designs, aiming at reducing the area and power consumption, while maintaining acceptable accuracy. The paper seeks to develop approximate compressors that align positive and negative approximations for input patterns that have the same probability. Additionally, the proposed compressors are utilized to construct approximate multipliers for different columns of partial products based on the input probabilities of the two compressors in adjacent columns. The proposed approximate multipliers are synthesized using the 28nm technology. Compared to the exact multiplier, the first proposed multiplier improves power × delay and area × power by 91% and 86%, respectively, while the second proposed multiplier improves the two parameters by 90% and 84%, respectively. The performance of the proposed approximate methods was assessed and compared with the existing methods for image multiplication, sharpening, smoothing and edge detection. Also, the performance of the proposed multipliers in the hardware implementation of the neural network was investigated, and the simulation results indicate that the proposed multipliers have appropriate accuracy in these applications.
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An Ultra-Efficient Approximate Multiplier with Error Compensation for Error-Resilient Applications
Base Paper Abstract:
Approximate computing is a promising paradigm for trading off accuracy to improve hardware efficiency in error-resilient applications such as neural networks and image processing. This brief presents an ultra-efficient approximate multiplier with error compensation capability. The proposed multiplier considers the least significant half of the product a constant compensation term. The other half is calculated precisely to provide an ultra-efficient hardware-accuracy tradeoff. Furthermore, a low-complexity but effective error compensation module (ECM) is presented, significantly improving accuracy. The proposed multiplier is simulated using HSPICE with 7nm tri-gate Fin FET technology. The proposed design significantly improves the energy-delay product, on average, by 77% and 54% compared to the exact and existing approximate designs. Moreover, the proposed multiplier’s accuracy and effectiveness in neural networks and image multiplication are evaluated using MATLAB simulations. The results indicate that the proposed multiplier offers high accuracy comparable to the exact multiplier in NNs and provides an average PSNR of more than 51dB in image multiplication. Accordingly, it can be an effective alternative for exact multipliers in practical error-resilient applications.
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Optimizing Ternary Multiplier Design with Fast Ternary Adder
Base Paper Abstract:
Existing ternary multiplier designs are difficult to use in ternary systems. Thus, ternary Wallace tree multipliers that reduce the number of transistors by using 4-input ternary adders are proposed to improve the performance of existing ternary multipliers. A ternary carry-select adder is also proposed to reduce the carry propagation delay, used as a carry-chain adder of the Wallace tree. The proposed multipliers are designed with a custom ternary standard cell library synthesized by multi-threshold complementary metal-oxide-semiconductor (CMOS) with a 28 nm process. Power and delay are verified via HSPICE simulation. The proposed 36 × 36 ternary multiplier shows 79.3% power-delay product improvement over the previous ternary multiplier. The proposed 40 × 40 ternary multiplier shows a power-delay product comparable with that of the 64 × 64 binary multiplier synthesized using Synopsys Design Compiler.
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A VLSI-Based Hybrid ECG Compression Scheme for Wearable Sensor Node
Base Paper Abstract:
During smart long-term monitoring of any biomedical signal in wireless body area networks, wearable sensor nodes generate and transmit a large amount of data, increasing transmission power consumption. In order to reduce data storage and power consumption, a lossless data compression technique for an electrocardiogram signal monitoring system is presented in this letter. For this, a hybrid lossless compression algorithm based on Run-length coding and Golomb–Rice coding is proposed to enhance the bit compressing rate. The lossless encoding scheme is implemented on the MIT-BIH arrhythmia database, achieving a compression ratio of 2.91. A VLSI-based architecture of the data compression algorithm is implemented in 90nm CMOS technology that consumes power of 18.78 µW at 100 MHz operating frequency and 1.2 V supply voltage, occupying an area of 0.0051 mm2.
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AxPPA: Approximate Parallel Prefix Adders
Base Paper Abstract:
Addition units are widely used in many computational kernels of several error-tolerant applications such as machine learning and signal, image, and video processing. Besides their use as stand-alone, additions are essential building blocks for other math operations such as subtraction, comparison, multiplication, squaring, and division. The parallel prefix adders (PPAs) is among the fastest adders. It represents a parallel prefix graph consisting of the carry operator nodes, called prefix operators (POs). The PPAs, in particular, are among the fastest adders because they optimize the parallelization of the carry generation (G) and propagation (P). In this work, we introduce approximate PPAs (AxPPAs) by exploiting approximations in the POs. To evaluate our proposal for approximate POs (AxPOs), we generate the following AxPPAs, consisting of a set of four PPAs: approximate Brent–Kung (AxPPA-BK), approximate Kogge–Stone (AxPPAKS), Ladner-Fischer (AxPPA-LF), and Sklansky (AxPPA-SK). We compare four AxPPA architectures with energy-efficient approximate adders (AxAs) [i.e., Copy, error-tolerant adder I (ETAI), lower-part OR adder (LOA), and Truncation (trunc)]. We tested them generically in stand-alone cases and embedded them in two important signal processing application kernels: a sum of squared differences (SSDs) video accelerator and a finite impulse response (FIR) filter kernel. The AxPPA-LF provides a new Pareto front in both energy-quality and area-quality results compared to state-of-the-art energy-efficient AxAs.
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Variable-Precision Approximate Floating-Point Multiplier for Efficient Deep Learning Computation
Base Paper Abstract:
In this brief, a variable-precision approximate floating-point multiplier is proposed for energy efficient deep learning computation. The proposed architecture supports approximate multiplication with BFloat16 format. As the input and output activations of deep learning models usually follow normal distribution, inspired by the posit format, for numbers with different values, different precisions can be applied to represent them. In the proposed architecture, posit encoding is used to change the level of approximation, and the precision of the computation is controlled by the value of product exponent. For large exponent, smaller precision multiplication is applied to mantissa and for small exponent, higher precision computation is applied. Truncation is used as approximate method in the proposed design while the number of bit positions to be truncated is controlled by the values of the product exponent. The proposed design can achieve 19% area reduction and 42% power reduction compared to the normal BFloat16 multiplier. When applying the proposed multiplier in deep learning computation, almost the same accuracy as that of normal BFloat16 multiplier can be achieved.
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Power Efficient Approximate Divider Architecture for Error Resilient Applications
Base Paper Abstract:
Approximate computing is an emerging paradigm in error-tolerant applications that leads to power-efficient designs without significant loss in quality. The divider in these applications have complex hardware and more latency among the computational blocks resulting in power consumption. Hence approximating the division module would lead to designs with vastly improved power efficiency. A new approximate subtractor (AxSUB) is proposed in this paper with the intent to reduce the hardware complexity while achieving accuracy within permissible limits. The proposed AxSUB and existing approximate subtractor units are used in the restoring array division (RAD) architecture to prove the efficacy of the AxSUB. Comprehensive error and synthesis analysis are performed on RAD architectures implemented using AxSUB, and existing methods. Our proposed design achieved a 21% decrease in area and a 28% decrease in power consumption compared to the exact design. The proposed and existing RAD architectures is implemented on change detection applications to validate the quality-effort tradeoff.
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Image Demosaicking using Super Resolution Techniques
Base Paper Abstract:
Limitations do exist on capturing the full color information in a scene, apart from the resolution of captured images. Therefore, mosaic images are the preferred format in digital cameras, where incomplete set of color information is acquired. In this paper, a super resolution demosaicking (SRD) approach is proposed to reconstruct an enhanced-resolution full-color image from the observed samples, robustly and without the need for a training process. The acquisition model assumes degraded observations using known blur and noise. The reconstruction approach iteratively estimates the unknown registration parameters and the demosaicking image simultaneously. Qualitative and quantitative experiments performed on synthetic observations reveal high performance images.
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Advanced Encryption Standard Algorithm with Optimal S-box and Automated Key Generation
Base Paper Abstract:
Advanced Encryption Standard (AES) algorithm plays an important role in a data security application. In general S-box module in AES will give maximum confusion and diffusion measures during AES encryption and cause significant path delay overhead. In most cases, either LUTs or embedded memories are used for S- box computations which are vulnerable to attacks that pose a serious risk to real-world applications. In this paper, implementation of the composite field arithmetic-based Sub-bytes and inverse Sub-bytes operations in AES is done. The proposed work includes an efficient multiple round AES cryptosystem with higher-order transformation and composite field s-box formulation with some possible inner stage pipelining schemes which can be used for throughput rate enhancement along with path delay optimization. Finally, input biometric-driven key generation schemes are used for formulating the cipher key dynamically, which provides a higher degree of security for the computing devices.
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Area and Power Efficient Truncated Booth Multipliers Using Approximate Carry-Based Error Compensation
Base Paper Abstract:
Approximate computing is a promising technique to elevate the performance of digital circuits at the cost of reduced accuracy in numerous error-resilient applications. Multipliers play a key role in many of these applications. In this brief, we propose a truncation based Booth multiplier with a compensation circuit generated by selective modifications in k-map to circumvent the carry appearing from the truncated part. By judicious mapping, hardware pruning and output error reduction is achieved simultaneously. In the quest of power and accuracy trade-off, Truncated and Approximate Carry based Booth Multipliers (TACBM) are proposed with a range of designs based on truncation factor w. When compared with the state-of-the-art multipliers, TACBM outperforms in terms of accuracy and Area Power savings. TACBM (w = 10) provides with 0.02% MRED and 23% reduction in Area-Power product compared to exact Booth multiplier. The multipliers are evaluated using image blending and Multilayer perceptron (MLP) neural network and a high value of accuracy (95.63%) for MLP is achieved.
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Power Efficient Tiny Yolo CNN Using Reduced Hardware Resources Based on Booth Multiplier and WALLACE Tree Adders
Base Paper Abstract:
Convolutional Neural Network (CNN) has attained high accuracy and it has been widely employed in image recognition tasks. In recent times, deep learning-based modern applications are evolving and it poses a challenge in research and development of hardware implementation. Therefore, hardware optimization for efficient accelerator design of CNN remains a challenging task. A key component of the accelerator design is a processing element (PE) that implements the convolution operation. To reduce the amount of hardware resources and power consumption, this article provides a new processing element design as an alternate solution for hardware implementation. Modified BOOTH encoding (MBE) multiplier and WALLACE tree-based adders are proposed to replace bulky MAC units and typical adder tree respectively. The proposed CNN accelerator design is tested on Zynq-706 FPGA board which achieves a throughput of 87.03 GOP/s for Tiny-YOLO-v2 architecture. The proposed design allows to reduce hardware costs by 24.5% achieving a power efficiency of 61.64 GOP/s/W that outperforms the previous designs.
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Reconfigurable Architecture for Real-time Decoding of Canonical Huffman Codes
Base Paper Abstract:
Data compression is an important algorithm which has found its use in modern day algorithms such as Convolutional Neural Networks (CNNs). Reconfigurable platforms (like FPGAs) have strong capabilities to implement time complex tasks like CNNs, however, these algorithms present a big challenge due to high resource demand. Data compression is one of the most utilized techniques to reduce memory utilization in FPGAs. The weights of CNN architecture are usually encoded to store in FPGA. In this paper, we propose design of an efficient decoder based on Canonical Huffman that can be utilized for the efficient decompression of weights in CNN. The proposed design makes use of Hash functions to effectively decode the weights eliminating the need for searching dictionary. The proposed design decodes a single weight in a single clock cycle. Our proposed design has a maximum frequency of 408.97MHz utilizing 1% of system LUTs when tested for Aritix 7 platform.
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A High-Speed FPGA-based True Random Number Generator using Metastability with Clock Managers
Base Paper Abstract:
True random number generators (TRNGs) are fundamentals in many important security applications. Though they exploit randomness sources that are typical of the analog domain, digital-based solutions are strongly required especially when they have to be implemented on Field Programmable Gate Array (FPGA)-based digital systems. This paper describes a novel methodology to easily design a TRNG on FPGA devices. It exploits the runtime capability of the Digital Clock Manager (DCM) hardware primitives to tune the phase shift between two clock signals. The presented auto-tuning strategy automatically sets the phase difference of two clock signals in order to force on one or more flip-flops (FFs) to enter the metastability region, used as a randomness source. Moreover, a novel use of the fast carry-chain hardware primitive is proposed to further increase the randomness of the generated bits. Finally, an effective on-chip post-processing scheme that does not reduce the TRNG throughput is described. The proposed TRNG architecture has been implemented on the Xilinx Zynq XC7Z020 System on Chip (SoC). It passed all the National Institute of Standards and Technology (NIST) SP 800-22 statistical tests with a maximum throughput of 300×106 bit per second. The latter is considerably higher than the throughput of other previously published DCMbased TRNGs.
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Energy-Efficient VLSI Realization of Binary64 Division With Redundant Number Systems
Base Paper Abstract:
VLSI realizations of digit-recurrence binary division usually use redundant representation of partial remainders and quotient digits. The former allows for fast carry-free computation of the next partial remainder, and the latter leads to less number of the required divisor multiples. In studying the previous relevant works, we have noted that the binary carry save (CS) number system is prevalent in the representation of partial remainders, and redundant high radix representation of quotient digits is popular in order to reduce the cycle count. In this paper, we explore a design space containing four division architectures. These are based on binary CS or radix-16 signed digit (SD) representations of partial remainders. On the other hand, they use full or partial pre computation of divisor multiples. The latter uses smaller multiplexer at the cost two extra adders, where one of the operands is constant within all cycles. The quotient digits are represented by radix-16 [−9,9]SDs. Our synthesis-based evaluation of VLSI realizations of the best previous relevant work and the four proposed designs show reduced power and energy figures in the proposed designs at the cost of more silicon area and delay measures. However, our energy-delay product is 26%–35% less than that of the reference work.
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FPGA Implementation of the Adaptive Digital Beamforming for Massive Array
Base Paper Abstract:
With the rise of 5G networks and the increasing number of communication devices, improving communication quality is essential. One approach is adaptive digital beamforming, which adjusts an antenna array’s radiation pattern based on the desired received signal. Adaptation based on Least-Mean Squared (LMS) and its variants is still one of the most common literature methods. Although LMS techniques present good computational performance, the increase in antennas’ numbers led to high-performance hardware. Platforms such as Field Programmable Gate Arrays (FPGAs), designed for massive array systems, enables high-performance energy-efficient architectures. This work proposes a parallel implementation of a massive array beamforming composed of a spatial filter and adaptation unit based on LMS on FPGA. The proposed design presents ten times fewer hardware requirements and 30 times less power consumption than state of the art.
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Determining Application-Specific Knowledge for Improving Robustness of Sequential Circuits
Base Paper Abstract:
Due to their shrinking feature sizes as well as environmental influences, such as high-energy radiation, electrical noise, and particle strikes, integrated circuits are getting more vulnerable to transient faults. Accordingly, how to make those circuits more robust has become an essential step in today’s design flows. Methods increasing the robustness of circuits against these faults already exist for a long period of time but either introduce huge additional logic, change the timing behavior of the circuit, or are applicable for dedicated circuits such as microprocessors only. In this paper, we propose an alternative method, which overcomes these drawbacks by determining application specific knowledge of the circuit, namely the relations of flip-flops and when they assume the same value. By this, we exploit partial redundancies, which are inherent in most circuits anyway (even the optimized ones), to frequently compare the circuit signals for their correctness—eventually leading to an increased robustness. Since determining the correspondingly needed information is a computationally hard task, formal methods, such as bounded model checking, satisfiability-based automatic test pattern generation, and binary decision diagrams, are utilized for this purpose. The resulting methodology requires only a slight increase in additional hardware, does only influence the timing behavior of the circuit negligibly, and is automatically applicable to arbitrary circuits. Experimental evaluations confirm these benefits.
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Approximate Multiplier Design Using Novel Dual-Stage 4 : 2 Compressors
Base Paper Abstract:
High speed multimedia applications have paved way for a whole new area in high speed error-tolerant circuits with approximate computing. These applications deliver high performance at the cost of reduction in accuracy. Furthermore, such implementations reduce the complexity of the system architecture, delay and power consumption. This paper explores and proposes the design and analysis of two approximate compressors with reduced area, delay and power with comparable accuracy when compared with the existing architectures. The proposed designs are implemented using 45 nm CMOS technology and efficiency of the proposed designs have been extensively verified and projected on scales of area, delay, power, Power Delay Product (PDP), Error Rate (ER), Error Distance (ED), and Accurate Output Count (AOC). The proposed approximate 4 : 2 compressor shows 56.80% reduction in area, 57.20% reduction in power, and 73.30% reduction in delay compared to an accurate 4 : 2 compressor. The proposed compressors are utilised to implement 8 × 8 and 16 × 16 Dadda multipliers. These multipliers have comparable accuracy when compared with state-of-the-art approximate multipliers. The analysis is further extended to project the application of the proposed design in error resilient applications like image smoothing and multiplication.
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Two-Stage OTA With All Subthreshold MOSFETs and Optimum GBW to DC-Current Ratio
Base Paper Abstract:
An approach for the design of two-stage class AB OTAs with sub-1µA current consumption is proposed and demonstrated. The approach employs MOS transistors operating in subthreshold and allows maximum gain-bandwidth product (GBW) to be achieved for a given DC current budget, by setting optimum distribution of DC currents in the two amplifier stages. Following this strategy, a class AB OTA was designed in a standard 0.5-µm CMOS technology supplied from 1.6-V and experimentally tested. Measured GBW was 307 kHz with 980-nA DC current consumption while driving an output capacitance of 40 pF with an average slew rate of 96 V/ms.
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Algorithm Level Error Detection in Low Voltage Systolic Array
Base Paper Abstract:
In this brief an approach is proposed to achieve energy savings from reduced voltage operation. The solution detects timing-errors by integrating Algorithm Based Fault Tolerance (ABFT) into a digital architecture. The approach has been studied with a systolic array matrix multiplier operating at reduced voltages, detecting errors on-the-fly to avoid energy demanding memory round-trips. The analysis of the solution has been done using analog-digital co-simulation to extract the transient behavior under different voltages and clock frequencies. HSPICE simulations using 90nm CMOS transistor models, and experiments by reducing operation voltage of an FPGA device were carried out. HSPICE simulations, showed possibility of 10x increase in energy-efficiency by approaching near-threshold region.
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Approximate Pruned and Truncated Haar Discrete Wavelet Transform VLSI Hardware for Energy-Efficient ECG Signal Processing
Abstract:
The approximate computing paradigm emerged as a key alternative for trading off accuracy and energy efficiency. Error-tolerant applications, such as multimedia and signal processing, can process the information with lower-than-standard accuracy at the circuit level while still fulfilling a good and acceptable service quality at the application level. The automatic detection of R-peaks in an electrocardiogram (ECG) signal is the essential step preceding ECG processing and analysis. The Haar discrete wavelet transform (HDWT) is a low-complexity pre-processing filter suitable to detect ECG R-peaks in embedded systems like wearable devices, which are incredibly energy constrained. This work presents an approximate HDWT hardware architecture for ECG processing at very high energy efficiency. Our best-proposal employing pruning within the approximate HDWT hardware architecture requires just seven additions. The use of a truncation technique to improve energy efficiency is also investigated herein by observing the evolution of the signal-to-noise ratio and the ultimate impact in the ECG peak-detection application. This research finds that our HDWT approximate hardware architecture proposal accepts higher truncation levels than the original HDWT. In summary: Our results show about 9 times energy reduction when combining our HDWT matrix approximation proposal with the pruning and the highest acceptable level of truncation while still maintaining the R-peak detection performance accuracy of 99.68% on average.
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A Reliable Low Standby Power 10T SRAM Cell With Expanded Static Noise Margins
Abstract:
This paper explores a low standby power 10T (LP10T) SRAM cell with high read stability and write-ability (RSNM/WSNM/WM). The proposed LP10T SRAM cell uses a strong cross-coupled structure consisting standard inverter with a stacked transistor and Schmitt-trigger inverter with a double-length pull-up transistor. This along with the read path separated from true internal storage nodes eliminates the read-disturbance. Furthermore, it performs its write operation in pseudo differential form through write bit line and control signal with a write-assist technique. To estimate the proposed LP10T SRAM cell’s performance, it is compared with some state-of-the-art SRAM cells using HSPICE in 16-nm CMOS predictive technology model at 0.7 V supply voltage under harsh manufacturing process, voltage, and temperature variations. The proposed SRAM cell offers 4.65X/1.57X/1.46X improvement in RSNM/WSNM/WM and 4.40X/1.69X narrower spread in RSNM/WM compared to the conventional 6T SRAM cell. Furthermore, it shows 1.26X/1.08X/1.01X higher RSNM/WSNM/WM and 1.71X/1.25X tighter/wider spread in RSNM/WM compared to the best studied SRAM cells. The proposed SRAM cell indicates 74.48%/1.41% higher/lower read/write delay compared to the 6T SRAM cell. Moreover, it exhibits the third-(second-) best read (write) dynamic power, consuming 29.69% (26.87%) lower than the 6T SRAM cell. The leakage power is minimized by the proposed design, which is 37.35% and 12.08% lower than that of the 6T and best studied cells, respectively. Nonetheless, the proposed LP10T SRAM cell occupies 1.313X higher area compared to the 6T SRAM cell.
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Reconfigurable Digital Delta-Sigma Modulation Transmitter Architecture for Concurrent Multi-Band Transmission
Abstract:
This paper presents a reconfigurable delta-sigma modulation (DSM) architecture for concurrent multi-band transmission. The reconfigurability in terms of carrier spacing and the number of simultaneous carrier transmission is useful for applications such as carrier aggregation in 5G. This paper uses 4th order reconfigurable multi-band DSM (RMB-DSM) such that the zeros of the noise transfer function can be reconfigured to fall at multiple frequencies, where the carriers are being aggregated. The quantization noise between the transmission bands is a critical issue in the case of multi-band transmission. Therefore, a multi-band additional noise shaping (ANS) function is also introduced, which generates notches around each carrier and reduces the noise level between the multiple pass-bands. The proposed scheme has been validated in simulation, as well as in experiment for aggregating up to four 15 MHz long term evolution (LTE) signals with an overall aggregated bandwidth of 60 MHz. Measurement results show a 10-25% improvement in coding efficiency and 15-35 dB improvement in noise level near the operating frequency band using the proposed multiband augmented noise shaping technique, as compared to the standard DSM. The corresponding improvement of 8% in the overall efficiency is observed by using the proposed multi-band augmented noise shaping technique.
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Soft-Error-Aware Read-Stability-Enhanced Low-Power 12T SRAM With Multi-Node Upset Recoverability for Aerospace Applications
Abstract:
With the advancement of technology, the size of transistors and the distance between them are reducing rapidly. Therefore, the critical charge of sensitive nodes is reducing, making SRAM cells, used for aerospace applications, more vulnerable to soft-error. If a radiation particle strikes a sensitive node of the standard 6T SRAM cell, the stored data in the cell are flipped, causing a single-event upset (SEU). Therefore, in this paper, a Soft-Error-Aware Read-Stability-Enhanced Low Power 12T (SARP12T) SRAM cell is proposed to mitigate SEUs. To analyze the relative performance of SARP12T, it is compared with other recently published soft-error-aware SRAM cells, QUCCE12T, QUATRO12T, RHD12T, RHPD12T and RSP14T. All the sensitive nodes of SARP12T can regain their data even if the node values are flipped due to a radiation strike. Furthermore, SARP12T can recover from the effect of single event multi-node upsets (SEMNUs) induced at its storage node pair. Along with these advantages, the proposed cell exhibits the highest read stability, as the ‘0’-storing storage node, which is directly accessed by the bit line during read operation, can recover from any upset. Furthermore, SARP12T consumes the least hold power. SARP12T also exhibits higher write ability and shorter write delay than most of the comparison cells. All these improvements in the proposed cell are obtained by exhibiting only a slightly longer read delay and consuming slightly higher read and write energy.
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Probability-Driven Evaluation of Lower-Part Approximation Adders
Abstract:
Parallel prefix adder topologies suffer from carry chains forming critical paths, limiting the performance and therefore the efficiency. We study approximation methods that offload the lower-part of calculation to an approximate unit and shorten the carry chain. We derive their accuracy models using probability theory. These models can replace Monte Carlo simulations. Furthermore, they can reveal better accuracy trade-offs without going through the RTL design, synthesis, and simulation of each unit and approximation level individually. Thus, they can eliminate the required design and simulation time and effort. After analyzing area-wise comparisons at varying number of approximated bits, we show that choosing a design that outperforms the others probabilistically also outperforms them in terms of accuracy, power, and performance trade-offs.
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A High-Throughput VLSI Architecture Design of Canonical Huffman Encoder
Abstract:
In this brief, a high-throughput Huffman encoder VLSI architecture based on the Canonical Huffman method is proposed to improve the encoding throughput and decrease the encoding time required by the Huffman code word table construction process. We proposed parallel computing architectures for frequency-statistical sorting and code-size computational sorting. This architecture results in a process of building a tree and assigning symbols that can be completed by scanning the data only once. This solves the problem of the low efficiency of the traditional algorithm, which needs to scan the data twice. Consequently, in addition to the advantages of the high compression ratio inherited from the Canonical Huffman, the proposed architecture has overridden advantages for a high parallelism processing capacity. The experimental results showed that the proposed architecture decreased the encoding time by 26.30% compared to the available Huffman encoder using the standard algorithm when encoding 256 8-bit symbols. Furthermore, the VLSI architecture could further decrease the encoding time when encoding more 8-bit symbols. In particular, when encoding 212,642 8-bit symbols, the proposed VLSI architecture could reduce the encoding time by 87.40%. Thus, compared with the traditional Huffman encoders, this brief achieved the improvement of coding efficiency.
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A Novel In-Memory Wallace Tree Multiplier Architecture Using Majority Logic
Abstract:
In-memory computing using emerging technologies such as resistive random-access memory (ReRAM) addresses the ‘von Neumann bottleneck’ and strengthens the present research impetus to overcome the memory wall. While many methods have been recently proposed to implement Boolean logic in memory, the latency of arithmetic circuits (adders and consequently multipliers) implemented as a sequence of such Boolean operations increases greatly with bit-width. Existing in-memory multipliers require O(n2) cycles which is inefficient both in terms of latency and energy. In this work, we tackle this exorbitant latency by adopting Wallace Tree multiplier architecture and optimizing the addition operation in each phase of the Wallace Tree. Majority logic primitive was used for addition since it is better than NAND/NOR/IMPLY primitives. Furthermore, high degree of gate-level parallelism is employed at the array level by executing multiple majority gates in the columns of the array. In this manner, an in-memory multiplier of O(n.log(n)) latency is achieved which outperforms all reported in-memory multipliers. Furthermore, the proposed multiplier can be implemented in a regular transistor-accessed memory array without any major modifications to its peripheral circuitry and is also energy-efficient.
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Recurrent Neural Networks With Column-Wise Matrix–Vector Multiplication on FPGAs
Abstract:
This article presents a reconfigurable accelerator for Recurrent Neural networks with fine-grained Column Wise matrix–vector multiplication (RENOWN). We propose a novel latency-hiding architecture for recurrent neural network (RNN) acceleration using column-wise matrix–vector multiplication (MVM) instead of the state-of-the-art row-wise operation. This hardware (HW) architecture can eliminate data dependencies to improve the throughput of RNN inference systems. Besides, we introduce a configurable checkerboard tiling strategy which allows large weight matrices, while incorporating various configurations of element-based parallelism (EP) and vector-based parallelism (VP). These optimizations improve the exploitation of parallelism to increase HW utilization and enhance system throughput. Evaluation results show that our design can achieve over 29.6 tera operations per second (TOPS) which would be among the highest for field-programmable gate array (FPGA)-based RNN designs. Compared to state-of-the-art accelerators on FPGAs, our design achieves 3.7–14.8 times better performance and has the highest HW utilization.
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A Configurable Floating Point Multiple Precision Processing Element for HPC and AI Converged Computing
Abstract:
There is an emerging need to design configurable accelerators for the high-performance computing (HPC) and artificial intelligence (AI) applications in different precisions. Thus, the floating-point (FP) processing element (PE), which is the key basic unit of the accelerators, is necessary to meet multiple-precision requirements with energy-efficient operations. However, the existing structures by using high-precision-split (HPS) and low-precision-combination (LPC) methods result in low utilization rate of the multiplication array and long multi term processing period, respectively. In this article, a configurable FP multiple-precision PE design is proposed with the LPC structure. Half precision, single precision, and double precision are supported. The 100% multiplier utilization rate of the multiplication array for all precisions is achieved with improved speed in the comparison and summation process. The proposed design is realized in a 28-nm process with 1.429-GHz clock frequency. Compared with the existing multiple-precision FP methods, the proposed structure achieves 63% and 88% areasaving performance for FP16 and FP32 operations, respectively. The 4× and 20× maximum throughput rates are obtained when compared with fixed FP32 and FP64 operations. Compared with the previous multiple-precision PEs, the proposed one achieves the best energy-efficiency performance with 975.13 GFLOPS/W.
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Low Cost Online Convolution Checksum Checker
Abstract:
Managing random hardware faults requires the faults to be detected online, thus simplifying recovery. Algorithm-based fault tolerance has been proposed as a low-cost mechanism to check online the result of computations against random hardware failures. In this case, the checksum of the actual result is checked against a predicted checksum computed in parallel by a hardware checker. In this work, we target the design of such checkers for convolution engines that are currently the most critical building block in image processing and computer vision applications. The proposed convolution checksum checker, named ConvGuard, utilizes a newly introduced invariance condition of convolution to predict implicitly the output checksum using only the pixels at the border of the input image. In this way, ConvGuard reduces the power required for accumulating the input pixels without requiring large buffers to hold intermediate checksum results. The design of ConvGuard is generic and can be configured for different output sizes and strides. The experimental results show that ConvGuard utilizes only a small percentage of the area/power of an efficient convolution engine while being significantly smaller and more power efficient than a state-of-the-art checksum checker for various practical cases.
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An Efficient and High Speed Overlap Free Karatsuba Based Finite Field Multiplier for FPGA Implementation
Abstract:
Cryptography systems have become inseparable parts of almost every communication device. Among cryptography algorithms, public-key cryptography, and in particular elliptic curve cryptography (ECC), has become the most dominant protocol at this time. In ECC systems, polynomial multiplication is considered to be the most slow and area consuming operation. This article proposes a novel hardware architecture for efficient field-programmable gate array (FPGA) implementation of Finite field multipliers for ECC. Proposed hardware was implemented on different FPGA devices for various operand sizes, and performance parameters were determined. Comparing to state-of-the art works, the proposed method resulted in a lower combinational delay and area–delay product indicating the efficiency of design.
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A Low Cost and High Throughtput FPGA Implementation of the Retinex Algorithm for Real Time Video Enhancement
Abstract:
For video applications in a special environment such as medical imaging, space exploration, and underwater exploration, the video captured by an image sensor is often deteriorated because of low lighting conditions. Therefore, it is necessary to enhance the part of the image that is too dark to distinguish details while maintaining the remaining part with the same brightness. The retinex algorithm is widely used to restore naturalness of a video, especially exhibiting outstanding performance in the enhancement of a dark area. However, it demands large computational complexity because of its intricate structure, such as the Gaussian filter and exponentiation operations, and consequently, it is difficult to process in real time. This article presents a low-cost and high-throughput design of the retinex video enhancement algorithm. The hardware (HW) design is implemented using a field-programmable gate array (FPGA), and it supports a throughput of 60 frames/s for a 1920 × 1080 image with negligible latency. The proposed FPGA design minimizes HW resources while maintaining the quality and the performance by using a small line buffer instead of a frame buffer, by applying the concept of approximate computing for the complex Gaussian filter, and by designing a new and nontrivial exponentiation operation. The proposed design makes it possible to significantly reduce HW resources (up to 79.22% of total resources) compared to existing systems and is compatible with commercialized devices through the standard HDMI/DVI video ports.
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High Performance Accurate and Approximate Multipliers for FPGA based Hardware Accelerators
Abstract:
Multiplication is one of the widely used arithmetic operations in a variety of applications, such as image/video processing and machine learning. FPGA vendors provide high performance multipliers in the form of DSP blocks. These multipliers are not only limited in number and have fixed locations on FPGAs but can also create additional routing delays and may prove inefficient for smaller bit-width multiplications. Therefore, FPGA vendors additionally provide optimized soft IP cores for multiplication. However, in this work, we advocate that these soft multiplier IP cores for FPGAs still need better designs to provide high-performance and resource efficiency. Towards this, we present generic area-optimized, low-latency accurate and approximate soft-core multiplier architectures, which exploit the underlying architectural features of FPGAs, i.e., look-up table (LUT) structures and fast carry chains to reduce the overall critical path delay and resource utilization of multipliers. Compared to Xilinx multiplier LogiCORE IP, our proposed unsigned and signed accurate architecture provides up to 25% and 53% reduction in LUT utilization, respectively, for different sizes of multipliers. Moreover, with our unsigned approximate multiplier architectures, a reduction of up to 51% in the critical path delay can be achieved with an insignificant loss in output accuracy when compared with the LogiCORE IP. For illustration, we have deployed the proposed multiplier architecture in accelerators used in image and video applications, and evaluated them for area and performance gains.
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Reliable CRC Based Error Detection Constructions for Finite Field Multipliers With Applications in Cryptography
Abstract:
Finite-field multiplication has received prominent attention in the literature with applications in cryptography and error-detecting codes. For many cryptographic algorithms, this arithmetic operation is a complex, costly, and time-consuming task that may require millions of gates. In this work, we propose efficient hardware architectures based on cyclic redundancy check (CRC) as error-detection schemes for postquantum cryptography (PQC) with case studies for the Luov cryptographic algorithm. Luov was submitted for the National Institute of Standards and Technology (NIST) PQC standardization competition and was advanced to the second round. The CRC polynomials selected are in-line with the required error-detection capabilities and with the field sizes as well. We have developed verification codes through which software implementations of the proposed schemes are performed to verify the derivations of the formulations. Additionally, hardware implementations of the original multipliers with the proposed error-detection schemes are performed over a Xilinx field-programmable gate array (FPGA), verifying that the proposed schemes achieve high error coverage with acceptable overhead.
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FPGA Based High Definition SPWM Generation With Harmonic Mitigation Property
Abstract:
High-resolution sinusoidal pulse width modulation (SPWM) switching is beneficial in order to achieve compact size and fine sinusoidal output of dc–ac converters. In this article, a novel field-programmable gate array (FPGA) based high-definition SPWM (HD-SPWM) architecture is proposed for adopting a scheme of integrating a lower frequency PWM train to a high-frequency SPWM train in order to suppress inverter output harmonics while achieving high resolution output. An optimized FPGA based two-stage finite-state-machine (FSM) architecture is designed, where the initial stage decides pulse widths of a lower frequency PWM train based on the premeditated pulse width of the high-frequency SPWM train, whereas in the final stage, lower frequency PWM pulse widths are integrated with the high-frequency SPWM pulse widths to generate updated pulse widths of high-frequency SPWM, i.e., HD-SPWM. Moreover, a pre-formulation mathematical model is established for the calculation of duty-cycle count values of pulse trains to support the online adjustment of modulation index (MI) of the HD-SPWM. The proposed generation has the benefits of harmonic mitigation, online fine adjustment of MI, low-processing time, and requirement of a minor segment of a medium-sized FPGA; thereby, providing a good tradeoff between larger designs and higher performance. Theoretical calculations, characteristics, and design contemplations are specified, and the HD-SPWM generation is demonstrated through experimentation with a Xilinx Spartan-3 FPGA board.
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Comparative study of 16-order FIR filter design using different multiplication techniques
Abstract:
This study represents designing and implementation of a low power and high speed 16 order FIR filter. To optimize filter area, delay and power, different multiplication techniques such as Vedic multiplier, add and shift method and Wallace tree (WT) multiplier are used for the multiplication of filter coefficient with filter input. Various adders such as ripple carry adder, Kogge Stone adder, Brent Kung adder, Ladner Fischer adder and Han Carlson adder are analyzed for optimum performance study for further use in various multiplication techniques along with barrel shifter. Secondly optimization of filter area and delay is done by using add and shift method for multiplication, although it increases power dissipation of the filter. To reduce the complexity of filter, coefficients are represented in canonical signed digit representation as it is more efficient than traditional binary representation. The finite impulse-response (FIR) filter is designed in MATLAB using equiripple method and the same filter is synthesized on Xilinx Spartan 3E XC3S500E target field-programmable gate array device using Very High Speed Integrated Circuit Hardware Description Language (VHDL) subsequently the total on-chip power is calculated in Vivado2014.4. The comparison of simulation results of all the filters show that FIR filter with WT multiplier is the best optimized filter.
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Multiplier-free Implementation of Galois Field Fourier Transform on a FPGA
Abstract:
A novel approach to implementing Galois Field Fourier Transform (GFT) is proposed that completely eliminates the need for any finite field multipliers by transforming the symbols from a vector representation to a power representation. The proposed method is suitable for implementing GFTs of prime and nonprime lengths on modern FPGAs that have a large amount of on-chip distributed embedded memory. For GFT of length 255 that is widely used in many applications, the proposed memory based implementation exhibits 25% improvement in latency, 27% improvement in throughput, and 56% reduction in power consumption compared to a finite field multiplier based implementation.
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Constant Time Hardware Architecture for a Gaussian Smoothing Filter
Abstract:
In this paper a new and highly efficient hardware architecture for a bit-serial implementation of a 3*3 filter on FPGA is developed and presented. The concept is implemented on a Gaussian blur spatial filter and it can be extended to other filters with similar characteristics. The proposed Single Instruction Multiple Data (SIMD) architecture provides a constant operating time independent of the size of the given image while the arithmetic operations are limited to the operations of addition. The Multiple Instruction Multiple Data (MIMD) performance is achieved in a near fraction of the cost. Thus, the hardware’s utilization is optimized. The total time needed to perform the filter of interest on the given image is solely dependent on the working clock frequency. The proposed design is evaluated using a small image and is implemented on two FPGA families with various sizes of an image. Also, it is compared with other architectures.
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A Three Stage Comparator and Its Modified Version With Fast Speed and Low Kickback
Abstract:
This brief presents a three-stage comparator and its modified version to improve the speed and reduce the kickback noise. Compared to the traditional two-stage comparators, the three-stage comparator in this work has an extra amplification stage, which enlarges the voltage gain and increases the speed. Unlike the traditional two-stage structure that uses pMOS input pair in the regeneration stage, the three-stage comparator makes it possible to use nMOS input pairs in both the regeneration stage and the amplification stage, further increasing the speed. Furthermore, in the proposed modified version of three-stage comparator, a CMOS input pair is adopted at the amplification stage. This greatly reduces the kickback noise by canceling out the nMOS kickback through the pMOS kickback. It also adds an extra signal path in the regeneration stage, which helps increase the speed further. For easy comparison, both the conventional two-stage and the proposed three-stage comparators are implemented in the same 130-nm CMOS process. Measured results show that the modified version of three-stage comparator improves the speed by 32%, and decreases the kickback noise by ten times. This improvement is not at the cost of increased input referred offset or noise.
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Floating-point discrete wavelet transform-based image compression on FPGA
Abstract:
In the era of data transmission through internet, image compression is considered an active research topic, decreasing the amount of data storage for faster data transfer. In this paper, the hardware implementation of an image compression system using Discrete Wavelet Transform (DWT) is presented. The transposed form Finite Impulse Response (FIR) filter is employed for performing the convolution process, on which the DWT is based. The design is generic to fit for different wavelet types and symmetric to expand for filters of multiple taps. The architecture is implemented on FPGA using IEEE-754 single precision. Floating-Point representation offered higher precision and better accuracy compared to scaled integer values. The proposed hardware design is implemented on Virtex 5 FPGA achieving 243.6 MHz clock frequency.
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A 2.5-V 8-Bit Low power SAR ADC using POLC and SMTCMOS D-FF for IoT Applications
Abstract:
A 2.5-V 8-bit low force and efficient Successive Approximation Register Analog-to-Digital converter (SAR-ADC) utilizing a Principled Open Loop Comparator (POLC) and Switched Multi-Threshold Complementary Metal Oxide Semiconductor (SMTCMOS) D-FF shift Register. In light of high proficiency and low force applications SAR-ADC is increasingly well known, yet it experience the ill effects of resolution and speed confinements. To defeat the above issue proposed a systematic methodology uses low force POLC based SAR-ADC is structured. Considering about the resolution, speed and compact design of 8- bit SAR-ADC, the proposed POLC strategy reasonably diminishes the propagation delay by 37% and decreases the force utilization by 62% appeared differently in relation to the standard system. A D-flip flop is planned to employ SMTCMOS procedure which has low force utilization and productively decline the leakage power. All the above circuits are simulated by using TANNER-EDA tool in 0.25μm CMOS technology produces 97% Efficiency.
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Implementation of Low Power 1-bit Hybrid Full Adder using 22nm CMOS Technology
Abstract:
Adders are plays a vital role in digital and vlsi systems. Arithmetic operations are an essential part of digital systems. During VLSI systems, the entire research is on lowering the scale of transistors for enforcing any other digital system. This proposed architecture implemented by different types of logic systems; each logic performs the different role in the hybrid system. The hybrid Full Adder cell with one bit is implemented in this structure. The proposed method is investigated using 22-nm CMOS hybrid full adder. The proposed architecture demonstrates substantial efficiency in power consumption and delay, based on simulation results. The simulation result expressed that the full adder circuit is used to modern high speed central processing unit in the data path architecture. This form of hybrid Full Adder, reduces the delay and increasing efficiency and mainly used in nano technology applications. The average power consumption of 1.1055uW with moderately low delay of 7.0415 ps was found to be extremely low for 0.8-V supply at 22-nm technology. These kind of adder allocates significant improvements in power, high speed and area compared with previous full adder designs.
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FPGA Implementation of Epileptic Seizure Detection Using ELM Classifier Detection Using ELM Classifier
Abstract:
Electroencephalography (EEG) Signals are widely used to determine the brain disorders. The Electrical activity of human brain is recorded in the form of EEG signal. The abnormal Electrical activity of the human brain is called as epileptic seizure. In epilepsy patients, the seizure occurs at unpredictable times and it causes sudden death. Detection and Prediction of Epileptic seizure is performed by analyzing the EEG signal. The EEG signal of human brain is random in nature, hence detection of seizure in EEG signal is challenging task. Hardware implementation of Epileptic seizure detection system is necessary for real time applications. In this work an accurate approach is used to identify the Epileptic seizure and that is implemented in FPGA (Field Programmable Gate Array).The hardware implementation of epileptic seizure detection algorithm is done using Xilinx System generator tool. In the first step the EEG signal is extracted from the human brain and it is filtered by using Finite Impulse response (FIR) band pass filter. The band pass filter separates the EEG signal into delta, theta, alpha, beta and gamma brain rhythms. The band separated brain signal is modeled by linear prediction theory. In the next step features are extracted from the modeled EEG signal and the classification of normal or seizure signal is done by using Extreme Learning Machine (ELM) classifier. The EEG signals used in this paper were obtained from Epilepsy Center at the University of Bonn, Germany. The hardware architecture, Look up tables, resource utilization, Accuracy and power consumption of the algorithm is analyzed using xilinx zynq7000 all programmable soc.
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ReLOPE: Resistive RAM-Based Linear First-Order Partial Differential Equation Solver
Abstract:
Data movement between memory and processing units poses an energy barrier to Von-Neumann-based architectures. In-memory computing (IMC) eliminates this barrier. RRAM-based IMC has been explored for data-intensive applications, such as artificial neural networks and matrix-vector multiplications that are considered as “soft” tasks where performance is a more important factor than accuracy. In “hard” tasks such as partial differential equations (PDEs), accuracy is a determining factor. In this brief, we propose ReLOPE, a fully RRAM crossbar-based IMC to solve PDEs using the Runge–Kutta numerical method with 97% accuracy. ReLOPE expands the operating range of solution by exploiting shifters to shift input data and output data. ReLOPE range of operation and accuracy can be expanded by using fine-grained step sizes by programming other RRAMs on the BL. Compared to software-based PDE solvers, ReLOPE gains 31.4× energy reduction at only 3% accuracy loss.
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A Low Power and High Speed Voltage Level Shifter Based on a Regulated Cross Coupled Pull Up Network
Abstract:
In this brief, a fast and very low power voltage level shifter (LS) is presented. By using a new regulated cross-coupled (RCC) pull-up network, the switching speed is boosted and the dynamic power consumption is highly reduced. The proposed (LS) has the ability to convert input signals with voltage levels much lower than the threshold voltage of a MOS device to higher nominal supply voltage levels. The presented LS occupies a small silicon area owing to its very low number of elements and is ultra-low-power, making it suitable for low-power applications such as implantable medical devices and wireless sensor networks. Results of the post-layout simulation in a standard 0.18-μm CMOS technology show that the proposed circuit can convert up input voltage levels as low as 80 mV. The power dissipation and propagation delay of the proposed level shifter for a low/high supply voltages of 0.4/1.8 V and input frequency of 1 MHz are 123.1 nW and 23.7 ns, respectively.
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A High-Performance Multiply-Accumulate Unit by Integrating Additions and Accumulations into Partial Product Reduction Process
Abstract:
In this paper, we propose a low-power high-speed pipeline multiply-accumulate (MAC) architecture. In a conventional MAC, carry propagations of additions (including additions in multiplications and additions in accumulations) often lead to large power consumption and large path delay. To resolve this problem, we integrate a part of additions into the pa rtial product reduction (PPR) process. In the proposed MAC architecture, the addition and accumulation of higher significance bits are not performed until the PPR process of the next multiplication. To correctly deal with the overflow in the PPR process, a small-size adder is designed to accumulate the total number of carries. Compared with previous works, experimental results show that the proposed MAC architecture can greatly reduce both power consumption and circuit area under the same timing constraint.
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Low-Cost and Programmable CRC Implementation Based on FPGA
Abstract:
Cyclic redundancy check (CRC) is a well-known error detection code that is widely used in Ethernet, PCIe, and other transmission protocols. The existing FPGA-based implementation solutions encounter the problem of excessive resource utilization in high-performance scenarios. The padding zeros problem and the introduction of programmability further exacerbate this problem. In this brief, the stride-by-5 algorithm is proposed to achieve the optimal utilization of FPGA resources. The pipelining go back algorithm is proposed to solve the padding zeros problem. The method of reprogramming by HWICAP is proposed to realize programmability with small and constant resource utilization. The experimental results show that the resource utilization of the proposed non-segmented architecture is 80.7%-87.5% and 25.1%-46.2% lower than that of two state of-the-art FPGA-based CRC implementations, and the proposed segmented architecture has lower resource utilization, by 81.7%- 85.9% and 2.9%-20.8%, than two state-of-the-art architectures. Furthermore, throughput and programmability are guaranteed.
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Design of ultra-low power consumption approximate 4-2 compressors based on the compensation characteristic
Abstract:
Approximate computing is tentatively applied in some digital signal processing applications which have an inherent tolerance for erroneous computing results. The approximate arithmetic blocks are utilized in them to improve the electrical performance of these circuits. Multiplier is one of the fundamental units in computer arithmetic blocks. Moreover, the 4-2 compressors are widely employed in the parallel multipliers to accelerate the compression process of partial products. In this paper, three novel approximate 4-2 compressors are proposed and utilized in 8-bit multipliers. Meanwhile, an error-correcting module (ECM) is presented to promote the error performance of approximate multiplier with the proposed 4-2 compressors. In this paper, the number of the approximate 4-2 compressor’s outputs is innovatively reduced to one, which brings further improvements in the energy efficiency. Compared with the exact 4-2 compressors, the simulation results indicate that the proposed approximate compressors UCAC1, UCAC2, UCAC3 achieve 24.76%, 51.43%, and 66.67% reduction in delay, 71.76%, 83.06%, and 93.28% reduction in power and 54.02%, 79.32%, and 93.10% reduction in area, respectively. And the utilization of these proposed compressors in 8-bit multipliers brings 49.29% reduction of power consumption on average.
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An Efficient Implementation of Floating Point Multiplier
Abstract:
In this paper we describe an efficient implementation of an IEEE 754 single precision floating point multiplier targeted for Xilinx Virtex-5 FPGA. VHDL is used to implement a technology-independent pipelined design. The multiplier implementation handles the overflow and underflow cases. Rounding is not implemented to give more precision when using the multiplier in a Multiply and Accumulate (MAC) unit. With latency of three clock cycles the design achieves 301 MFLOPs. The multiplier was verified against Xilinx floating point multiplier core.
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FPGA implementation of low power and high speed image edge detection algorithm
Abstract:
Image processing is a vital task in data processing system for applications in medical fields, remote sensing, microscopic imaging etc., Algorithms for processing image exist except for real time system style, hardware implementation is most popular principally. This paper presents a design for Sobel filter based edge detection on Field Programmable Gate Array (FPGA) board. Hardware implementation of the Sobel edge detection algorithm is chosen because it presents an honest scope for similarity over software package. On the opposite hand, Sobel edge detection will work with less deterioration in high level of noise. Edges are primarily the noticeable variation of intensities in a picture. Edges facilitate to spot the placement of an object and also the boundary of a selected entity within the image. It conjointly helps in feature extraction and pattern recognition. Hence, edge detection is of nice importance in pc vision. The planned design for edge detection exploitation Sobel algorithm is designed using structural Verilog lipoprotein synthesized exploitation Cadence Genus and enforced using Cadence Innovus. The practicality of the planning is verified exploitation normal pictures by FPGA implementation. The proposed architecture reduce the power, delay and space complexity compare to three existing architectures.
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A Design Implementation and Comparative Analysis of Advanced Encryption Standard (AES) Algorithm on FPGA
Abstract:
As the technology is getting advanced continuously the problem for the security of data is also increasing. The hackers are equipped with new advanced tools and techniques to break any security system. Therefore people are getting more concern about data security. The data security is achieved by either software or hardware implementations. In this work Field Programmable Gate Arrays (FPGA) device is used for hardware implementation since these devices are less complex, more flexible and provide more efficiency. This work focuses on the hardware execution of one of the security algorithms that is the Advanced Encryption Standard (AES) algorithm. The AES algorithm is executed on Vivado 2014.2 ISE Design Suite and the results are observed on 28 nanometers (nm) Artix-7 FPGA. This work discusses the design implementation of the AES algorithm and the resources consumed in implementing the AES design on Artix-7 FPGA. The resources which are consumed are as follows- Slice Register (SR), Look-Up Tables (LUTs), Input/Output (I/O) and Global Buffer (BUFG).
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