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2019 International SoC Design Conference (ISOCC)最新文献

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Lower-part Stochastic Unipolar Adder to Improve Computation Accuracy 提高计算精度的下半随机单极加法器
Pub Date : 2019-10-06 DOI: 10.1109/ISOCC47750.2019.9078491
Hyounghun Joe, Cheolsoo Park, Hyungtak Kim, Youngmin Kim
Stochastic computing is one of approximate computing, which provides lower power consumption through simpler designs with a tolerable error. However, stochastic computing has a fundamental limitation in bit width. The larger the bit size, the longer the computation time. Besides, the error rate also increases as the bit size increases. In this paper, we propose a new stochastic adder, in which stochastic computing is only applied in the lower bits to reduce overall errors in large bit addition. Simulation shows that the proposed design can achieve up to 17x average error reduction compared with the conventional design when a half of the bit is computed stochastically.
随机计算是近似计算的一种,它通过更简单的设计和可容忍的误差提供更低的功耗。然而,随机计算在位宽度上有一个基本的限制。比特大小越大,计算时间越长。此外,误码率也随着比特大小的增加而增加。在本文中,我们提出了一种新的随机加法器,其中随机计算只应用于低位,以减少大比特加法的总体误差。仿真结果表明,在随机计算一半钻头的情况下,与传统设计相比,所提出的设计可以实现高达17倍的平均误差降低。
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引用次数: 0
FPGA reverse engineering in Vivado design suite based on X-ray project 基于x射线项目的FPGA在Vivado设计套件中的逆向工程
Pub Date : 2019-10-06 DOI: 10.1109/ISOCC47750.2019.9078504
Hoyoung Yu, Hyung-Min Lee, Youngjoo Shin, Youngmin Kim
As FPGA demand grows, interest in FPGA security is also increasing. FPGA Reverse Engineering (RE) in the ISE Design Suite environment has been studied extensively, but FPGA RE in the Vivado Design Suite environment has not been practically studied at present. Particularly, there is no research on Programmable Interconnect Points (PIP). Since a method that correlates bitstream and XDL file is not applicable in Vivado environment, it requires complete analysis of FPGA structure and bitstream. So X-ray project [1] is used for structure analysis. In this paper, we analyze PIP bitstream configuration information based on X-ray project and propose PIP RE method in Vivado Design Suite environment based on it. The proposed method can be extended to full FPGA RE in Vivado Design Suite environment through further studies.
随着FPGA需求的增长,人们对FPGA安全性的兴趣也在增加。ISE Design Suite环境下的FPGA逆向工程(FPGA Reverse Engineering, RE)已经得到了广泛的研究,但是在Vivado Design Suite环境下的FPGA逆向工程目前还没有得到实际的研究。特别是对可编程互连点(PIP)的研究较少。由于比特流和XDL文件的关联方法不适用于Vivado环境,因此需要对FPGA结构和比特流进行完整的分析。因此采用x射线工程[1]进行结构分析。本文分析了基于x射线项目的PIP比特流配置信息,并在此基础上提出了Vivado Design Suite环境下的PIP RE方法。通过进一步的研究,可以将该方法扩展到Vivado Design Suite环境下的全FPGA RE中。
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引用次数: 2
A Wide-Input-Range Ultrasonic Power Regulator with an Adaptive Voltage Generator for Implantable Applications 用于植入式应用的带自适应电压发生器的宽输入范围超声功率调节器
Pub Date : 2019-10-06 DOI: 10.1109/ISOCC47750.2019.9078462
Wei-Jun Liao, T. Tsai
Ultrasonic power transmission provides an attractive solution to minimize the size of the implants while achieving high power levels (100 μW to several mW) required for most implant applications. Also, ultrasonic power transmission is affected by the distance and the alignment, and results in a wide input voltage range. A wide-input-range ultrasonic power regulator with an adaptive voltage generator for implantable applications is presented in this paper. A highfrequency voltage doubler circuit is used in the receiver to regulate the output voltage. On-chip capacitance is used to minimize the volume of the implant. The proposed regulator is designed in TSMC 0.18um CMOS process with 1.8 V supply voltage, and achieves a peak efficiency of 56.2%. The input voltage ranges from ±0.5 V to ±1.8 V.
超声功率传输提供了一个有吸引力的解决方案,以最大限度地减少植入物的尺寸,同时实现大多数植入物应用所需的高功率水平(100 μW到几mW)。此外,超声波功率传输受距离和对准的影响,导致输入电压范围很宽。提出了一种具有自适应电压发生器的可植入型宽输入范围超声功率调节器。接收机采用高频倍压电路来调节输出电压。片上电容用于最小化植入体的体积。该稳压器采用TSMC 0.18um CMOS工艺设计,电源电压为1.8 V,峰值效率为56.2%。输入电压范围:±0.5 V ~±1.8 V。
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引用次数: 0
Basic circuit design of high step-up ratio DC-DC converter 高升压比DC-DC变换器的基本电路设计
Pub Date : 2019-10-06 DOI: 10.1109/ISOCC47750.2019.9078530
Shota Uchino, T. Yamamoto, F. Mohamad, K. Shinohara, T. Iida, T. Kousaka, H. Ohtagaki, H. Asahara
Thermoelectric power generation modules for industrial applications often require an output of several tens of watts, and DC-DC converters used for power matching are required to have high conversion efficiency at low voltage input. In this study, we realize high conversion efficiency at low voltage and we investigate basic circuit performance in the laboratory experiment. In addition, since some of the thermoelectric generation modules have low voltage output characteristics, it is necessary to design high step-up ratio DC-DC converter. In view of the above, we report on the design and trial evaluation of the generated power conditioning system with the high step-up ratio DC-DC converter.
工业应用的热电发电模块通常需要几十瓦的输出,用于功率匹配的DC-DC变换器需要在低电压输入下具有高的转换效率。在这项研究中,我们实现了在低电压下的高转换效率,并在实验室实验中研究了基本电路的性能。另外,由于部分热电发电模块的电压输出特性较低,需要设计高升压比的DC-DC变换器。有鉴于此,我们报告了采用高升压比DC-DC变换器的发电调节系统的设计和试验评价。
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引用次数: 0
Application of Blind-Signal-Processing Algorithm in Image Separation - Blind-Signal-Processing in Image Separation 盲信号处理算法在图像分离中的应用——图像分离中的盲信号处理
Pub Date : 2019-10-06 DOI: 10.1109/ISOCC47750.2019.9078531
Chuen-Yau Chen, Cheng-Yuan Lin, Wei-Ching Liu, Yen-Ting Chen
We take advantage of the relative gradient method and the bound component analysis algorithm to propose the relativegradient bound component analysis algorithm in this paper. This algorithm does not need to compute the inverse matrix and the covariance matrix. It can succesfully separate the mixed pictures without whitening. The time complexity and the space complexity of this algorithm are both lower than those of the original bound component analysis algorithm.
本文利用相对梯度法和界分量分析算法,提出了相对梯度界分量分析算法。该算法不需要计算逆矩阵和协方差矩阵。它可以成功地分离混合图像而不产生白化。该算法的时间复杂度和空间复杂度均低于原有的边界分量分析算法。
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引用次数: 0
Configurable CNN SoC Co-Processor Architecture 可配置CNN SoC协处理器架构
Pub Date : 2019-10-06 DOI: 10.1109/ISOCC47750.2019.9078513
Joshua Adiel Wijaya, T. Adiono
In this paper we proposed a configurable CNN architecture design for use in a SoC co-processor. The co-processor is configured and generated by the proposed design tools utilizing folding architecture and multiple processing elements working in parallel. The proposed system utilized a configurable system designer that can automatically generate the verilog source file that defines a CNN processor that can process various image and kernel sizes. The system designer also able to generate the program code to be run on the SoC platform. The system design has been verified using a ZYNQTM 7000 SoC platform and shows the processing result is similar to the simulation results. The system can reach the processing speed of 72.727 MHz.
本文提出了一种用于SoC协处理器的可配置CNN架构设计。所提出的设计工具利用折叠架构和并行工作的多个处理元素来配置和生成协处理器。所提出的系统利用了一个可配置的系统设计器,该设计器可以自动生成verilog源文件,该文件定义了一个可以处理各种图像和内核大小的CNN处理器。系统设计人员还能够生成在SoC平台上运行的程序代码。在ZYNQTM 7000 SoC平台上对系统设计进行了验证,结果表明处理结果与仿真结果相似。系统的处理速度可达72.727 MHz。
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引用次数: 2
A Wideband Differential Low Noise Amplifier for TVWS Applications in 130 nm CMOS Technology 用于130纳米CMOS技术的TVWS应用的宽带差分低噪声放大器
Pub Date : 2019-10-06 DOI: 10.1109/ISOCC47750.2019.9078520
Huo Yingge, Imran Ali, Kangyoon Lee
In this paper, a wideband differential low noise amplifier (LNA) is presented for TV white space (TVWS) applications. For wideband input matching and high gain over 470~698 MHz TVWS bandwidth, a common-source (CS) complementary resistive shunt feedback amplifier is used in the proposed LNA. This LNA structure also reduces noise. The design achieves 26.4 dB gain and 1.75 dB noise figure. It consumes 22.56 mW power and draws 18.8 mA current from 1.2 V supply. It is integrated into TVWS transceiver with 130 nm CMOS technology and it occupies 531 × 279 μm² chip area.
提出了一种适用于电视白色空间(TVWS)的宽带差分低噪声放大器(LNA)。为了在470~698 MHz的TVWS带宽范围内实现宽带输入匹配和高增益,所提出的LNA采用了共源互补电阻分流反馈放大器。这种LNA结构还可以降低噪声。该设计实现了26.4 dB增益和1.75 dB噪声系数。它消耗22.56兆瓦的功率,从1.2 V电源中吸取18.8毫安的电流。该芯片采用130 nm CMOS技术集成到TVWS收发器中,芯片面积为531 × 279 μm²。
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引用次数: 0
Copyright 版权
Pub Date : 2019-10-06 DOI: 10.1109/isocc47750.2019.9027670
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引用次数: 0
Fast Simulation Method for Analog Deep Binarized Neural Networks 模拟深度二值化神经网络的快速仿真方法
Pub Date : 2019-10-06 DOI: 10.1109/ISOCC47750.2019.9078516
Chaeun Lee, Jaehyun Kim, Jihun Kim, Jaehyun Kim, Cheol Seong Hwang, Kiyoung Choi
We propose a simulation method for analog deep binarized neural networks which enables fast and accurate simulation. This method is based on look-up tables and can accelerate simulation on a GPU. It extracts the look-up tables using a circuit simulator such as SPICE under various types of environments. To prove the validity of this method, we show the experimental results for analog deep binarized neural networks. In the experiment, we could accelerate the simulation by 612K times compared to FineSim simulation on an example of multilayer perceptron.
提出了一种模拟深度二值化神经网络的仿真方法,可以实现快速、准确的仿真。该方法基于查找表,可以在GPU上加速仿真。它使用SPICE等电路模拟器在各种环境下提取查找表。为了证明该方法的有效性,我们给出了模拟深度二值化神经网络的实验结果。在实验中,与FineSim在多层感知器上的仿真相比,我们可以将仿真速度提高612K倍。
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引用次数: 0
Multi-carrier Signal Detection using Convolutional Neural Networks 基于卷积神经网络的多载波信号检测
Pub Date : 2019-10-06 DOI: 10.1109/ISOCC47750.2019.9078534
J. Ruseckas, Gediminas Molis, A. Mackute-Varoneckiene, T. Krilavičius
For efficient spectrum sharing between noncooperating networks a fast spectrum scan must be implemented. Frequency, power, bandwidth and modulation have to be quickly estimated to adapt to the environment and cause minimal interference for other users even when protocol is not known. Here we propose to apply convolutional neural network for multicarrier signal detection and classification as it can measure all these parameters from one short data sample. For the classification and detection tasks, six multi-carrier signal modulations were generated. We have measured detection probability and classification accuracy over wide range of signal-to-noise ratios and have estimated the hardware resources needed for the task. In addition, we have studied impact of signal augmentation during training phase on classification accuracy when only portion of the signal is available. We show that signal four times shorter than 5G radio subframe can be sufficient for the task.
为了在非合作网络之间实现有效的频谱共享,必须实现快速的频谱扫描。必须快速估计频率、功率、带宽和调制,以适应环境,即使在协议未知的情况下,也要尽量减少对其他用户的干扰。本文提出将卷积神经网络应用于多载波信号的检测和分类,因为它可以从一个短数据样本中测量所有这些参数。对于分类和检测任务,生成了6个多载波信号调制。我们在广泛的信噪比范围内测量了检测概率和分类精度,并估计了任务所需的硬件资源。此外,我们还研究了在只有部分信号可用的情况下,训练阶段的信号增强对分类精度的影响。我们表明,比5G无线电子帧短四倍的信号就足以完成这项任务。
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2019 International SoC Design Conference (ISOCC)
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