A novel low power hybrid cache using GC-EDRAM cells

In a typical embedded CPU, large on-chip storage is critical to meet high performance requirements. However, the fast increasing size of the on-chip storage based on traditional SRAM cells makes the area cost and energy consumption unsustainable for future embedded applications. Replacing SRAM with DRAM on the CPU’s chip is generally considered not worthwhile because DRAM is not compatible with the common CMOS logic and requires additional processing steps beyond what is required for CMOS. However a special DRAM technology, Gain-Cell embedded-DRAM (GC-eDRAM)  [1], [2], [3] is logic compatible and retains some of the good properties of DRAM (small and low power). In this paper we evaluate the performance of a novel hybrid cache memory where the data array, generally populated with SRAM cells, is replaced with GC-eDRAM cells while the tag array continues to use SRAM cells. Our evaluation of this cache demonstrates that, compared to the conventional SRAM-based designs, our novel architecture exhibits comparable performance with less energy consumption and smaller silicon area, enabling the sustainable on-chip storage scaling for future embedded CPUs.     

基于VMware的Linux系统下Cortex-A8平台的环境搭建

Cortex-A8平台是嵌入式系统技术的综合体现,Cortex-A8平台在VMware的Linux操作系统下需要将实体计算机作为Cortex-A8平台的通信终端,借助虚拟机下的Linux操作系统为其编译内核和可执行的命令,在虚拟机上安装和挂载Samba服务和NFS服务。文章详述Cortex-A8平台复杂实验环境的搭建过程。     

Estimation of Antenna Correlation Coefficient of N-Port Lossy MIMO Array

This paper proposes a simple yet accurate method for estimating the antenna correlation coefficient (ACC) of a high-order multiple-input multiple-output (MIMO) antenna. The conventional method employed to obtain the ACC from three-dimensional radiation patterns is costly and difficult to measure. An alternate method is to use the S-parameters, which can be easily measured using a network analyzer. However, this method assumes that the antennas are highly efficient, and it is therefore not suitable for lossy MIMO antenna arrays. To overcome this limitation, we define and utilize the non-coupled radiation efficiency in the S-parameter-based ACC formula. The accuracy of the proposed method is verified by the simulation results of a 4-port highly coupled lossy MIMO array. Further, the proposed method can be applied to N-port arrays by expanding the calculation matrix.     

FPGA-based architecture to estimate the input glucose in a dark fermenter using a super-twisting observer

This article presents a digital architecture design for a Super-Twisting Observer (STO) implemented in a Field-Programmable Gate Array (FPGA). The STO is robust in the presence of uncertainties, which makes it suitable to estimate unknown inputs present in biological systems and applications based on sensorless control accurately. The proposed STO is used to estimate the glucose concentration in the inflow of a hydrogen production bioreactor (e.g., dark fermenter). The dark fermenter is not generally recognized as a swift process. Therefore, the observer digital architecture design criteria aim to optimize hardware resources and reduce power consumption through an iterative approach to perform internal arithmetic operations efficiently. Besides, an analysis of the errors produced by internal operations, observer discretization, and fixed-point data representation is presented and discussed. Numerical results showed that embedding the super-twisting observer into the FPGA is a reliable, low-power consumption, and efficient alternative to estimate the input glucose in a dark fermenter.     

Emotion recognition at the edge with AI specific low power architectures

Nowadays Deep Learning is applied in almost every research field and helps getting amazing results in a great number of challenging tasks. The main problem is that this kind of learning and consequently Neural Networks that can be defined deep, are resource intensive. They need specialized hardware to perform computation in a reasonable time. Many tasks are mandatory to be as much real-time as possible . It is needed to optimize many components such as code, algorithms, numeric accuracy and hardware, to make them “efficient and usable”. All these optimizations can help us to produce incredibly accurate and fast learning models. The paper reports a study in this direction for the challenging face detection and emotion recognition tasks.     

基于AVR单片机的风电机组自动消防控制系统

野外或海上安装的风电系统如发生火灾将造成严重的损失,急需装备自动消防控制系统。面向风电机舱的消防安全,研制基于AVR单片机嵌入式技术的用于火灾感应和检测以及远程监控的消防控制系统。采用了温度、烟度以及图像等信息感应火灾情况,通过电启动超细干粉灭火装置进行自动灭火。最后利用RS485总线和光纤网络将单片机检测仪和远程控制器连接起来,构成完善的风力发电场消防报警和控制系统。初步试验结果表明该系统达到了设计目标,可用于风电系统的消防安全控制。     

基于ARM&FPGA的玻璃刻花机控制器的设计

在分析玻璃刻花工艺的基础上,研究了以嵌入式微处理器ARM和FPGA为核心架构的玻璃刻花机控制器硬件平台,以及以Linux和Xenomai构建的实时操作系统为软件框架的软件平台。针对玻璃刻花加工对同步控制、误差补偿和加工工艺的要求,研究了相关的功能模块,完成玻璃刻花机控制器的设计开发。     

基于ARM的浅层气检测仪

针对地质勘察和地下建筑施工中存在的浅层气泄漏与喷发等安全问题,对浅层气的危害及其特性进行了研究,对目前在用的的浅层气检测的方法进行了归纳,提出了一种基于ARM-Linux技术的便携式浅层气检测仪用于检测以甲烷与二氧化碳为主要成分的浅层气。采用非色散红外吸收(NDIR)原理的气体传感器检测浅层气中CH4与CO2的浓度。利用微处理器S3C2440集成的ADC单元进行了数据采集,设计了一种双通道ADC单元Linux驱动程序以实现两路模/数转换,采用防脉冲干扰平均滤波算法实现了测量数据的软件滤波。将采集到的浅层气浓度数据存入了SQLite数据库。使用Linux操作系统中集成开发环境Qt Creator设计了仪器界面,可分别显示实时浓度、历史数据及数据曲线。最后,根据流量比混合法在浅层气测量实验台配置出不同标准浓度的气体并进行了测量实验。研究结果表明,该检测仪运行稳定可靠、重复性较好,具有较好的实用性。     

停车场远程视频监控系统的设计与开发

提出和实现了一种基于嵌入式设备的停车场视频监控和车位检测方案。在嵌入式Linux操作系统下,通过调用计算机视觉库OpenCV中的图像处理函数,实现多车位的检测,检测结果保存到嵌入式数据库中。通过嵌入式设备将车位信息发送给PC或手持设备,并以图像的形式显示,达到远程车位检测的目的。本系统还移植了Mjpgstreamer实现停车场的远程视频监控。车位状态的检测采用2种判据:一是车位范围内差影的均值;二是车位区域内的边缘点数。测试结果表明,该方案可以很好地运行在嵌入式平台,为停车诱导提供支持。     

Qt Embedded环境下柱上开关控制器的人机接口设计

为了解决传统柱上开关智能化程度低的缺点,研发了一种新型智能柱上开关控制器。针对新型智能柱上开关控制器所需人机接口的要求,讨论了基于 Qt Embedded的智能柱上开关控制器人机界面的设计,并提供了一种灵活的按键控制人机界面的方法。可供相关的工程设计参考。