Despite the focus on page loading times and user experience, it is important not to lose sight of the core system metrics such as disk, memory, CPU, and network.
尽管关注的重点是页面装载时间和用户体验，但是也不要忽视核心系统指标，比如磁盘、内存和网络。
A bad network card, hard drive, or memory might result in your system spending a long time waiting for information.
不能正常工作的网卡、硬盘或内存，都可能导致系统花费很长的时间等待信息。
System Processors Memory Disk Swap partition network.
系统处理器内存硬盘交换分区网络。
The idea was to create a caching system that utilises spare memory capacity on the network.
其理念使使用网络中空闲的空间来储存缓存。
It includes analyzing and tuning your system hardware and software for optimal performance of all major components including memory, CPUs, disk drives, and the network. For example.
它包括分析和调优系统硬件及软件，以优化所有主要组件的性能，包括内存、CPU、磁盘驱动器和网络。
Might not just retrieve the value of "property" from memory, but might involve a calculation that pulls data across a network, checks system status, and so on. Similarly, when I write.
可能不只是从内存检索“property”的值，而有可能涉及这样的计算：在网络上传送数据、检查系统状态，等等。
The system was configured with 8 GB memory and one local disk drive. The network used a 1.0 Gbps Ethernet adapter.
系统配有8GB内存及一个本地硬盘，还有一个 1.0Gbps以太网卡。
Therefore, regarding the expansion memory system, must experience a memory (video recording) the system and the network storage device manufacturer technical collaboration process.
所以，对于扩展存储系统来说，也要经历一个存储（录像）系统与网络存储设备厂商的技术合作过程。
Making full use of the distance among the memory speed, network bandwidth, and disk bandwidth, building caches in the system is one of the major methods to enhance the file system performance.
利用主存速度和网络带宽、磁盘带宽之间的差异，在主存中实现缓存是提高并行文件系统性能的主要手段之一。
An incoherent optical system is proposed to implement fuzzy associative memory (FAM) neural network.
本文提出一种模糊联想神经网络的非相干光学实现系统。
In this paper, we discussed some key application problems of shape recognition system based on associative memory neural network.
本课题针对联想记忆网络形状识别系统应用中出现的若干关键问题进行了深入研究。
In this paper, a design of an all-optical multi-value neural network system for implementation of associative memory is presented.
本文提出一种用于联想识别的全光型多值神经网络系统。
In the system, Relation database model is adopted to memory the parameter information of the device, and the adjacent matrix is used to memory the network topology of power system.
该系统利用关系数据库模型存储设备的参数信息，构造邻接矩阵记录电网的拓扑结构。
Then place emphasis on system memory management, network communication;
然后重点描述运行系统内存管理、网络通信；
Optical implementation methods of one dimensional local interconnection neural network (LINN) for associative memory are proposed, and three optoelectronic system are discussed in this paper.
本文提出了一维局域互联关联存贮的光学实现方法，讨论了可用来实现局域互联网的三种光电混合系统。
A new model of neural network associative memory is introduced into the BIT design of radar servo sub-system, which achieves satisfactory effect.
将一种改进了的神经网络联想记忆模型应用于雷达伺服分系统的BIT设计中，取得了比较满意的效果。
Artificial Immune Network Memory Classifier(AINMC)and Artificial Immune Recognition System(AIRS)are two kinds of classifier based on artificial immune systems.
人工免疫网络记忆分类器和人工免疫识别系统是两种人工免疫分类方法。
Artificial Immune Network Memory Classifier(AINMC)and Artificial Immune Recognition System(AIRS)are two kinds of classifier based on artificial immune systems.
人工免疫网络记忆分类器和人工免疫识别系统是两种人工免疫分类方法。
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