尽管这个问题总是被忽视，但在数据密集型应用程序中，数据流确实会消耗大量带宽。
While often overlooked, data flow consumes a larger share of bandwidth in data-intensive applications.
该文针对广域分布式环境和数据密集型应用的需求提出一个面向服务的文件管理系统。
A service oriented file management system for the demand of the wide area distributed environment and data intensive applications is proposed.
但是针对图像处理这类数据密集型应用的特点，传统的处理器体系结构已明显不能提供足够的数据处理能力。
But facing the characteristics of the data-intensive applications, e. g. the image manipulation, the traditional processor architectures are unable to supply enough data processing abilities.
由于光网络具有大容量、低延时、动态控制以及任意粒度带宽等特性，把光网络与分布式计算系统结合，为数据密集型应用提供很好的应用环境。
On the other hand, optical networking can offer huge capacity and relatively low latency, as well as dynamic control and allocation of bandwidth at various granularities.
比如数据库连接池就是单例设计模式的一个例子：我们一般不想让应用程序具有连接池类的多个资源密集型实例。
An example use case for a singleton would be a database connection pool: you don't want your application to have multiple resource-intensive instances of a connection pool class.
如果对源数据库的访问不可靠，在缓存层争取弹性可能会提高读密集型应用程序的总体稳定性。
If access to the source database is unreliable, striving for resiliency in the cache layer might improve overall stability for read-intensive applications.
但是，在目前阶段，GE的突破还只是停留在实验室阶段，尚未有规模市场供应和投入计划的方案，而且仅应用于数据密集型企业。
However, at this stage, ge's breakthrough is lab-only, with no solution yet for a mass market offering and launch plans, vague as they are, for data-intensive business USES only.
就JFS2而言，这种情况不再可能发生，甚至不再需要，因为已经对它进行了优化，以便更加高效地处理元数据密集型的应用程序。
With JFS2, that is no longer possible, or even necessary, because it was tuned in order to handle metadata-intensive types of applications much more efficiently.
我们的主要客户使用AppistryEAF来简化数据和CPU密集型应用的开发和部署，典型的如以一种高可靠的方式来处理大量数据。
The majority of our customers are using Appistry EAF to simplify the development and deployment of data and CPU intensive applications, typically to process lots of data in a highly reliable way.
Moonlight在设计时已经考虑到对于数据和存储密集型Web应用程序的处理。
Moonlight was designed with data and memory intensive web application processes in mind.
网络技术的进步为数据密集或计算密集型的应用提供了大规模、分布式的处理能力。
Advances in network technology provide large scale distributed computing capacity for those applications that deal with heavy computation task.
数据库应用系统是数据密集型计算机应用，它的核心是数据库的设计。
Database application system is a computer application of type of dense data, whose kernel is the design of database.
数据密集型的科学与工程应用(如计算力学数值模拟、气象预测)需要在广域、分布式的计算环境中快速安全的传输海量的数据。
Data-intensive scientific and engineering applications often require the efficient transfer of terabytes or even petabytes of data in wide-area, distributed computing environments.
数据密集型程序有着广泛的应用，已经成为高性能计算中最重要的应用程序之一。
Recently data intensive applications have been focused as one of the most important applications for high performance computing.
数据网格广泛应用于数据密集型计算，为大数据量、分布存储数据资源提供快速的信息检索和数据访问的支持。
Data Grid is widely used in data-intensive computing, which provide rapid information retrieval and data access support for large amounts of distributed storage data resources.
数据网格广泛应用于数据密集型计算，为大数据量、分布存储数据资源提供快速的信息检索和数据访问的支持。
Data Grid is widely used in data-intensive computing, which provide rapid information retrieval and data access support for large amounts of distributed storage data resources.
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