单片机抢占式实时多任务处理的简易实现方法

提出了一种采用软件扩展中断技术的简易实时多任务调度程序设计方法,详细介绍了1个调度程序和4个系统调用即软中断触发调用、硬中断进入调度、硬中断退出调用及陷阱调用的实现,并给出了相应的程序框图。该软中断单片机抢占式实时多任务处理方法具有核心程序短、效率高、使用简单等优点,适合于单片机级的应用。     

计算机专业硬件类课程教学改革探讨

本文针对目前国内高校计算机专业教学中普遍存在的"重视软件课程、轻视硬件课程"现象,分析了计算机硬件类课程教学中存在的主要问题,结合自己多年的教学经验,提出了硬件类课程教学改革和学生创新能力培养的措施。     

基于WMI硬件ID激活策略的研究与实现

用客户端PC机器上所有硬件作为客户端唯一标识,而不是某一个硬件,而取得PC机器上所有硬件的ID必须要用到Windows管理规范(WMI)技术.有些硬件本身就没有ID标识,而有些硬件ID的重复率很高,为了解决这个问题,需要采用权值的概念,对于不同的硬件,它所对应的权值是不一样的.为了保护PC机的ID,需要用Hash算法得到每个硬件ID的Hash值,用这些Hash值作为客户端的标识;把客户端所有硬件ID的Hash值组包发送到服务器,这样服务器端就得到了客户端的信息.     

协同分布式图形硬件的混合并行体绘制

由于一般的共享存储并行机缺乏图形硬件,其上产生的3维科学计算数据,无法采用硬件加速的并行体绘制来就地进行数据可视化。为此基于本地并行机和分布式图形工作站,给出了一种混合并行绘制模型。该模型的工作原理是先将源数据存留在并行机,然后通过并行机的多处理器发布远程绘制命令流,进而通过操控工作站的图形硬件完成绘制;后期图像合成在并行机上执行,以发挥共享存储通信优势。通过负载平衡优化,并行绘制流水线有效实现了绘制、合成与显示的重叠。实验结果显示,该方法能以1024×1024图像分辨率,交互绘制并行机上的大规模数据场。     

基于飞腾DSP的多视场星敏感器信息处理系统设计

星敏感器是自主导航姿态控制系统中的重要组成部分之一。作为星敏感器的核心部件,信息处理系统对其整机性能有重要影响。基于飞腾多核DSP+复旦微FPGA架构设计了一种全国产化多视场星敏感器信息处理系统。在设计中采用EMIF接口和GPIO接口与复旦微FPGA进行数据交互及控制,将2片串行 Flash用于存储星库数据和启动程序,将2片DDR3芯片用于缓存数据。详细介绍了信息处理系统的整体软件流程设计、算法流程设计及实现。经试验验证,该系统可稳定运行并输出正确姿态。在星图分辨率为2048×2048的情况下,系统无初始指向时的数据更新频率为20Hz,有初始指向时的数据更新频率为625Hz。运算性能约为普通ARM架构的3倍,对于提升多视场星敏感器的实时性、丰富其工程化实现方法具有重要意义。     

Room-Temperature-Processable Highly Reliable Resistive Switching Memory with Reconfigurability for Neuromorphic Computing and Ultrasonic Tissue Classification

Reversible metal-filamentary mechanism has been widely investigated to design an analog resistive switching memory (RSM) for neuromorphic hardware-implementation. However, uncontrollable filament-formation, inducing its reliability issues, has been a fundamental challenge. Here, an analog RSM with 3D ion transport channels that can provide unprecedentedly high reliability and robustness is demonstrated. This architecture is realized by a laser-assisted photo-thermochemical process, compatible with the back-end-of-line process and even applicable to a flexible format. These superior characteristics also lead to the proposal of a practical adaptive learning rule for hardware neural networks that can significantly simplify the voltage pulse application methodology even with high computing accuracy. A neural network, which can perform the biological tissue classification task using the ultrasound signals, is designed, and the simulation results confirm that this practical adaptive learning rule is efficient enough to classify these weak and complicated signals with high accuracy (97%). Furthermore, the proposed RSM can work as a diffusive-memristor at the opposite voltage polarity, exhibiting extremely stable threshold switching characteristics. In this mode, several crucial operations in biological nervous systems, such as Ca²⁺ dynamics and nonlinear integrate-and-fire functions of neurons, are successfully emulated. This reconfigurability is also exceedingly beneficial for decreasing the complexity of systems—requiring both drift- and diffusive-memristors.     

RISC-V架构硬件辅助用户态内存安全防御方案概览

传统的用户态内存安全防御机制基于x86架构和纯软件方式实现,实现内存安全保护的运行时开销很高,难以部署在生产环境中.近年来,随着主流商业处理器开始提供硬件安全扩展,以及RISC-V等开源处理器架构的兴起,内存安全保护方案开始面向x86-64、ARM、RISC-V等多种体系架构和硬件辅助实现方式.我们对RISC-V架构上实现的内存安全防御方案进行了讨论,并对x86-64、ARM、RISC-V等处理器架构在安全方案设计上的特点进行了比较.得益于开放的指令集架构生态, RISC-V架构的内存安全防御方案相较于其他架构有一些优势.一些低成本的安全防御技术有望在RISC-V架构上实现.     

Implementation and characterization of flash-based hardware security primitives for cryptographic key generation

Hardware security primitives, also known as physical unclonable functions (PUFs), perform innovative roles to extract the randomness unique to specific hardware. This paper proposes a novel hardware security primitive using a commercial off-the-shelf flash memory chip that is an intrinsic part of most commercial Internet of Things (IoT) devices. First, we define a hardware security source model to describe a hardware-based fixed random bit generator for use in security applications, such as cryptographic key generation. Then, we propose a hardware security primitive with flash memory by exploiting the variability of tunneling electrons in the floating gate. In accordance with the requirements for robustness against the environment, timing variations, and random errors, we developed an adaptive extraction algorithm for the flash PUF. Experimental results show that the proposed flash PUF successfully generates a fixed random response, where the uniqueness is 49.1%, steadiness is 3.8%, uniformity is 50.2%, and min-entropy per bit is 0.87. Thus, our approach can be applied to security applications with reliability and satisfy high-entropy requirements, such as cryptographic key generation for IoT devices.     

基于流特征的数据中心非对称流负载均衡方法

数据中心边界广泛部署的地址转换技术产生的非对称流为负载均衡系统的设计带来了挑战.为了解决软件负载均衡系统不能充分发挥多核处理器和网卡硬件能力的问题,提出一种基于流特征的非对称流负载均衡方法.首先,分析网卡的数据包散列机制,提出数据包调度算法,将数据包调度至预期的CPU核;然后,基于会话报文序列的时间与空间特征,构建大象流识别算法;最后,基于识别结果,提出负载均衡方法.实验结果表明,非对称流负载均衡方法可以正确处理非对称流的负载均衡,平均吞吐率提升约14.5%.