本文主要讨论分布式存储环境下并行计算的最佳数据分配方案。
The paper discusses the optimal data distribution scheme for distributed environments.
大规模并行处理系统(MPP)和PC机群为并行求解矩阵广义特征值问题提供了分布式存储环境。
Massively parallel Processing system (MPP) and PC cluster provide distributed-memory environments for parallel solving the generalized eigenvalue problem.
目录服务提供了在分布式环境中存储和检索信息的一种方法，比如序列化对象。
Directory services provide a way to store and retrieve information, such as serializable objects, in a distributed environment.
这两个类都非常有用，可作为存储用于分布式或高可用性环境的应用程序中的数据的主要场所。
Both of these classes have some useful purposes and can act as the primary place to store data in applications that are designed for distributed or highly available environments.
本文还演示了如何使用WebSphereApplicationServer中的动态缓存功能来在分布式环境中管理服务内的存储对象的生命周期。
This article also illustrates the use of the dynamic cache feature in WebSphere Application Server to manage the life cycle of stored objects within the service in a distributed environment.
在分布式目录环境中，数据跨多个目录服务器分散存储。
A distributed directory is a directory environment in which data is partitioned across multiple directory servers.
StorageTank系统提供在异构的、分布式的环境中存储器。
The storage Tank system provides storage in heterogeneous, distributed environments.
Ceph在分布式文件系统空间中并不是唯一的，但它在管理大容量存储生态环境的方法上是独一无二的。
Ceph isn't unique in the distributed file system space, but it is unique in the way that it manages a large storage ecosystem.
在集群环境下，将分布式的外设构成一种动态虚拟存储系统能够较好地解决这个问题。
To solve the problem, it is a good idea to construct the distributed disks in cluster system into a DVDA(dynamic virtual parallel disk array).
本文主要研究分布式虚拟环境中与访问代理相关的技术问题，以及武器装备信息存储系统的设计方法与实现技术。
In this thesis, the technology about Access broker is studied and the Weapon Information Storage System is designed and implemented.
研究分布式环境下高效易用的文件系统监控技术，为分布式应用提供可靠的文件存储、安全的文件共享，具有重要的现实意义。
The research of distributed file system monitoring technique, which provides reliable file storing and safe file sharing, is practical and principal.
数值结果表明，算法具有较快的收敛速度，在分布式并行环境下具有较好的并行度和较低的存储要求。
Experimental results show that the algorithms and has quicker convergence speed, and have better parallel level as well as lower request for memory.
数值结果表明，算法具有较快的收敛速度，在分布式并行环境下具有较好的并行度和较低的存储要求。
Experimental results show that the algorithms and has quicker convergence speed, and have better parallel level as well as lower request for memory.
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