欢迎来到数字化、数据密集型、空中监视时代。
例如，想象您正在建立一个数据密集型的系统。
For example, imagine you're building a system that's data intensive.
还可另外购买附加工具，来增强对数据密集型DB 2环境的控制能力。
There are additional tools available at an additional purchase to further enhance your control of data-intensive DB2 environments.
支持Dryad(大伸缩量，数据密集型的并行计算)(即将提供)。
Support for Dryad (large scale, data-intensive parallel programming) (soon).
电信BI系统已经成为数据密集型企业的信息系统建设的重中之重。
Telecom BI system has been the key system of the most important information systems in enterprises with dense data.
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.
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.
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.
网格的目标是实现异构资源共享，及用来解决大规模计算或数据密集型计算等问题。
The goal of Grid is for realizing different kinds of resource-sharing and for solving calculating on a large scale or such problems as the data are calculate intensively.
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.
虽然网格中的存储计算非常适合数据密集型存储，但是存储一个字节大小的对象从经济上来说不合适。
While the storage computing in the grid is well suited for data-intensive storage, it is not economically suited for storing objects as small as 1 byte.
摘要CUDA是一种由NVIDIA推出的并行计算架构，非常适合大规模数据密集型计算。
Abstract CUDA is a parallel computing architecture introduced by NVIDIA, it mainly used for large scale data-intensive computing.
这一增长的原动力来自于各行各业和各地区对于一整套的丰富多样的数据密集型使用场景的需求。
This growth will primarily be driven by a rich and diverse set of data-intensive use cases across multiple industries and geographies.
设计了利用因特网上多个集群的空闲资源来处理生物医学领域数据密集型计算的新药研发网格(DDG)。
Utilizing the idle resources donated by the clusters that scatter over the Internet, drug discovery grid (DDG) can implement efficient data-intensive biologic applications.
数据网格以其良好的数据共享和协同工作能力，满足了诸如高能物理、气候模拟等数据密集型任务的需求。
Data grid meets the demand for data-intensive tasks with good data sharing and collaboration capabilities, such as high-energy physics, climate modeling and so on.
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.
海量遥感图像快速处理是遥感图像处理与分析的重要任务之一，它既是数据密集型，也是计算密集型的工作。
Huge quantity remote sensing image processing is one of the important tasks of remote sensing image processing and analysis, it is not only data intensive work, but also computation intensive work.
对此问题进行深入分析后，我们发现这属于数据密集型行为，由于数据不在缓存内，因此造成较高的内存分页率。
After digging deeper into this issue, we found that this is a data intensive activity, the data is not in the cache, and results in a high paging rate.
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.
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.
提供更丰富，更有表现力的经验往往需要更多的数据密集型的相互作用和管理介绍了在客户端和服务器层数据的新挑战。
Providing a richer, more expressive experience often requires more data-intensive interaction and introduces new challenges in managing data between the client and server tiers.
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.
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.
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.
遗憾的是，对所有不可信数据编码是资源密集型的工作，而且可能对某些Web服务器产生性能方面的影响。
Unfortunately, encoding all untrusted data can be resource intensive and may have a performance impact on some Web servers.
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.
可能有一个请求执行一个简单的算术活动，另一个请求执行一个资源密集型操作，比如数据库读写。
You could have one request perform a simple arithmetic activity and another request perform a resource intensive operation, such as reading or writing to a database.
音频数据的编码是一项cpu密集型任务。
记住，实时搜索可能是数据库密集型的。
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.
应用推荐