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Unveiling the True Power of the Latched Ring Oscillator for a Unified PUF and TRNG Architecture 揭示用于统一 PUF 和 TRNG 架构的锁相环振荡器的真正威力
IF 2.8 2区 工程技术 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Pub Date : 2024-09-04 DOI: 10.1109/tvlsi.2024.3448503
Riccardo Della Sala, Davide Bellizia, Giuseppe Scotti
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引用次数: 0
ReAdapt-II: Energy-Quality Optimizations for VLSI Adaptive Filters Through Automatic Reconfiguration and Built-In Iterative Dividers ReAdapt-II:通过自动重新配置和内置迭代除法器优化 VLSI 自适应滤波器的能耗质量
IF 2.8 2区 工程技术 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Pub Date : 2024-09-04 DOI: 10.1109/tvlsi.2024.3446235
Pedro T. L. Pereira, Patrícia Ucker L. Costa, Eduardo da Costa, Paulo Flores, Sergio Bampi
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引用次数: 0
A Second-Order Noise Shaping SAR ADC With Parallel Multiresidual Integrator 带并行多冗余积分器的二阶噪声整形 SAR ADC
IF 2.8 2区 工程技术 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Pub Date : 2024-08-30 DOI: 10.1109/TVLSI.2024.3447740
Yang Zhou;Wenjie Wang;Longbin Zhu;Zhengtao Zhu;Risheng Su;Jianan Zheng;Siyuan Xie;Jihong Li;Fanyi Meng;Zhijun Zhou;Keping Wang
This brief proposes a parallel multiresidual (PMR) integrator to enhance the noise-shaping (NS) effect for successive approximation register (SAR) analog-to-digital converter (ADC). The PMR employs passive integrators in parallel to simultaneously integrate the average result of the multiple sequential residual voltages. The proposed PMR technique provides an alternative scheme to enhance the NS rather than increasing the order of the integrator to suppress the instability and power. A prototype 7-bit second-order NS-SAR ADC is designed and simulated in a 130-nm CMOS process. PMR increases the effective number of bits (ENOBs) to 10.6 bit, which enhances the NS effect of 3.6 bit. It achieves a peak signal-to-noise and distortion ratio (SNDR) of 65.84 dB over a bandwidth of 1.3 kHz at the oversampling ratio (OSR) of 16.
本文提出了一种并行多残差(PMR)积分器,以增强逐次逼近寄存器(SAR)模数转换器(ADC)的噪声整形(NS)效果。PMR 采用并联无源积分器,同时对多个连续残余电压的平均结果进行积分。所提出的 PMR 技术提供了另一种增强 NS 的方案,而不是增加积分器的阶数来抑制不稳定性和功耗。在 130 纳米 CMOS 工艺中设计并模拟了一个 7 位二阶 NS-SAR ADC 原型。PMR 将有效位数 (ENOB) 提高到 10.6 位,从而增强了 3.6 位的 NS 效果。在过采样率(OSR)为 16 的 1.3 kHz 带宽上,它实现了 65.84 dB 的峰值信噪比和失真比(SNDR)。
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引用次数: 0
A 0.05–1.5-GHz PVT-Insensitive Digital-to-Time Converter for QKD Applications 用于 QKD 应用的 0.05-1.5 GHz PVT 不敏感数时转换器
IF 2.8 2区 工程技术 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Pub Date : 2024-08-30 DOI: 10.1109/tvlsi.2024.3447111
Haiyue Yan, Yan Ye, Wenjia Li, Xuefei Bai
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引用次数: 0
Power-Efficient Analog Hardware Architecture of the Learning Vector Quantization Algorithm for Brain Tumor Classification 用于脑肿瘤分类的学习矢量量化算法的高能效模拟硬件架构
IF 2.8 2区 工程技术 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Pub Date : 2024-08-30 DOI: 10.1109/TVLSI.2024.3447903
Vassilis Alimisis;Emmanouil Anastasios Serlis;Andreas Papathanasiou;Nikolaos P. Eleftheriou;Paul P. Sotiriadis
This study introduces a design methodology pertaining to analog hardware architecture for the implementation of the learning vector quantization (LVQ) algorithm. It consists of three main approaches that are separated based on the distance calculation circuit (DCC) and, more specifically; Euclidean distance, Sigmoid function, and Squarer circuits. The main building blocks of each approach are the DCC and the current comparator (CC). The operational principles of the architecture are extensively elucidated and put into practice through a power-efficient configuration (operating less than 650 nW) within a low-voltage setup (0.6 V). Each specific implementation is tested on a brain tumor classification task achieving more than 96.00% classification accuracy. The designs are realized using a 90-nm CMOS process and developed utilizing the Cadence IC Suite for both schematic and physical design. Through a comparative analysis of postlayout simulation outcomes with an equivalent software-based classifier and related works, the accuracy of the applied modeling and design methodologies is validated.
本研究介绍了实现学习矢量量化(LVQ)算法的模拟硬件架构设计方法。它包括基于距离计算电路 (DCC) 的三种主要方法,更具体地说,包括欧氏距离、西格莫函数和 Squarer 电路。每种方法的主要构件是 DCC 和电流比较器 (CC)。通过低电压设置(0.6 V)中的高能效配置(运行功耗小于 650 nW),该架构的运行原理得到了广泛阐释并付诸实践。每个具体实现都在脑肿瘤分类任务中进行了测试,分类准确率超过 96.00%。这些设计采用 90 纳米 CMOS 工艺实现,并利用 Cadence IC Suite 进行原理图和物理设计。通过将布局后仿真结果与基于软件的等效分类器和相关作品进行比较分析,验证了应用建模和设计方法的准确性。
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引用次数: 0
HPR-Mul: An Area and Energy-Efficient High-Precision Redundancy Multiplier by Approximate Computing HPR-Mul:通过近似计算实现面积和能效的高精度冗余乘法器
IF 2.8 2区 工程技术 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Pub Date : 2024-08-29 DOI: 10.1109/TVLSI.2024.3445108
Jafar Vafaei;Omid Akbari
For critical applications that require a higher level of reliability, the triple modular redundancy (TMR) scheme is usually employed to implement fault-tolerant arithmetic units. However, this method imposes a significant area and power/energy overhead. Also, the majority-based voter in the typical TMR designs is highly sensitive to soft errors and the design diversity of the triplicated module, which may result in an error for a small difference between the output of the TMR modules. However, a wide range of applications deployed in critical systems are inherently error-resilient, that is, they can tolerate some inexact results at their output while having a given level of reliability. In this article, we propose a high precision redundancy multiplier (HPR-Mul) that relies on the principles of approximate computing to achieve higher energy efficiency and lower area, as well as resolve the aforementioned challenges of the typical TMR schemes, while retaining the required level of reliability. The HPR-Mul is composed of full precision (FP) and two reduced precision (RP) multipliers, along with a simple voter to determine the output. Unlike the state-of-the-art RP redundancy multipliers (RPR-Muls) that require a complex voter, the voter of the proposed HPR-Mul is designed based on mathematical formulas resulting in a simpler structure. Furthermore, we use the intermediate signals of the FP multiplier as the inputs of the RP multipliers, which significantly enhance the accuracy of the HPR-Mul. The efficiency of the proposed HPR-Mul is evaluated in a 15-nm FinFET technology, where the results show up to 70% and 69% lower power consumption and area, respectively, compared to the typical TMR-based multipliers. Also, the HPR-Mul outperforms the state-of-the-art RPR-Mul by achieving up to 84% higher soft error tolerance. Moreover, by employing the HPR-Mul in different image processing applications, up to 13% higher output image quality is achieved in comparison with the state-of-the-art RPR multipliers.
对于需要更高可靠性的关键应用,通常采用三重模块冗余(TMR)方案来实现容错算术单元。然而,这种方法会带来巨大的面积和功耗/能耗开销。此外,典型的 TMR 设计中基于多数的表决器对软错误和三重模块的设计多样性高度敏感,这可能导致 TMR 模块输出之间的微小差异就会产生错误。然而,部署在关键系统中的各种应用本身都具有抗错能力,也就是说,它们可以在具有一定可靠性水平的同时,容忍输出端出现一些不精确的结果。在本文中,我们提出了一种高精度冗余乘法器(HPR-Mul),它依靠近似计算原理实现了更高的能效和更小的面积,并解决了上述典型 TMR 方案所面临的挑战,同时保持了所需的可靠性水平。HPR-Mul 由全精度(FP)乘法器和两个降低精度(RP)乘法器组成,并通过一个简单的投票器确定输出。与需要复杂投票器的最先进 RP 冗余乘法器(RPR-Muls)不同,拟议的 HPR-Mul 的投票器是根据数学公式设计的,因此结构更简单。此外,我们使用 FP 倍增器的中间信号作为 RP 倍增器的输入,这大大提高了 HPR-Mul 的精度。我们在 15 纳米 FinFET 技术中对所提出的 HPR-Mul 的效率进行了评估,结果显示,与典型的基于 TMR 的乘法器相比,功耗和面积分别降低了 70% 和 69%。此外,HPR-Mul 的软容错能力比最先进的 RPR-Mul 高出 84%。此外,在不同的图像处理应用中使用 HPR-Mul 时,输出图像质量比最先进的 RPR 乘法器高出 13%。
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引用次数: 0
A CMOS Readout Circuit for Resistive Tactile Sensor Array Using Crosstalk Suppression and Nonuniformity Compensation Techniques 采用串音抑制和不均匀性补偿技术的电阻式触觉传感器阵列 CMOS 读出电路
IF 2.8 2区 工程技术 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Pub Date : 2024-08-27 DOI: 10.1109/tvlsi.2024.3447164
Yao Li, Junfeng Geng, Mao Ye, Jiaji He, Xiaoxiao Zheng, Qiuwei Wang, Yiqiang Zhao
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引用次数: 0
Spread Spectrum-Based Countermeasures for Cryptographic RISC-V SoC 基于扩频的密码 RISC-V SoC 对策
IF 2.8 2区 工程技术 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Pub Date : 2024-08-27 DOI: 10.1109/tvlsi.2024.3444851
Thai-Ha Tran, Ba-Anh Dao, Duc-Hung Le, Van-Phuc Hoang, Trong-Thuc Hoang, Cong-Kha Pham
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引用次数: 0
Detect and Replace: Efficient Soft Error Protection of FPGA-Based CNN Accelerators 检测和替换:基于 FPGA 的 CNN 加速器的高效软错误保护
IF 2.8 2区 工程技术 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Pub Date : 2024-08-26 DOI: 10.1109/tvlsi.2024.3443834
Zhen Gao, Yanmao Qi, Jinchang Shi, Qiang Liu, Guangjun Ge, Yu Wang, Pedro Reviriego
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引用次数: 0
IEEE Transactions on Very Large Scale Integration (VLSI) Systems Publication Information IEEE 超大规模集成 (VLSI) 系统论文集 出版信息
IF 2.8 2区 工程技术 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Pub Date : 2024-08-26 DOI: 10.1109/TVLSI.2024.3422690
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引用次数: 0
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IEEE Transactions on Very Large Scale Integration (VLSI) Systems
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