Welcome to the digital, data-intensive, spy-in-the-sky age.
欢迎来到数字化、数据密集型、空中监视时代。
Think of the amount of network traffic for such a data-intensive object!
想一想，对于这样一个数据密集的对象，需要多大的网络通信量！
Support for Dryad (large scale, data-intensive parallel programming) (soon).
支持Dryad(大伸缩量，数据密集型的并行计算)(即将提供)。
While often overlooked, data flow consumes a larger share of bandwidth in data-intensive applications.
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。
The slower data speeds mean data-intensive apps don't run very well—online video is choppy, for example.
通过这个网络，数据传输速度很慢，意味着需要大量数据传输的应用程序不能很好的运行，比如说，在线视频经常卡壳。
There are additional tools available at an additional purchase to further enhance your control of data-intensive DB2 environments.
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。
Abstract CUDA is a parallel computing architecture introduced by NVIDIA, it mainly used for large scale data-intensive computing.
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。
This growth will primarily be driven by a rich and diverse set of data-intensive use cases across multiple industries and geographies.
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。
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.
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。
On the contrast, in the data-intensive financial industry, the application of AI technologies to extract value of data is still in a relatively primitive stage.
但是在金融这样一个数据密集的多金行业，数据的应用还停留在比较原始的阶段。
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.
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。
Utilizing the idle resources donated by the clusters that scatter over the Internet, drug discovery grid (DDG) can implement efficient data-intensive biologic applications.
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)。
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.
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。
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。
Their skill set is particularly important in visual interface design, especially as it relates to data-intensive applications and some Web sites, where content outweighs function.
对于视觉界面设计非常重要，尤其是具有大量数据的应用和网站，这里内容常常比功能更重要。
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。
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.
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。
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.
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。
For example, imagine you're building a system that's data intensive.
例如，想象您正在建立一个数据密集型的系统。
Some example applications are signal processing, intensive physics simulations, and some kinds of data processing.
典型应用包括信号处理、密集的物理模拟及某些数据处理。
Taking a data intensive approach.
采用数据强化的方法。
More performance intensive, because more database access is required, for every data element stored there.
存储在那里的每一个数据元素都需要更多的性能加强，因为需要更多的数据库访问。
But will it ever be good enough to replace a traditional keyboard for intensive data entry on a desktop or laptop?
不过虚拟键盘是否就能好到取代传统键盘成为台式和笔记本电脑密集信息的输入途径呢？
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.
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。
Unfortunately, encoding all untrusted data can be resource intensive and may have a performance impact on some Web servers.
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。
Moonlight was designed with data and memory intensive web application processes in mind.
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。
The most flexible, but also the most resource intensive approach, is using a database for all data, including metadata.
最为灵活但也最耗资源的方法是所有数据（包括元数据）都使用一个数据库。
Keeping 100 MB of audio data in memory might be too storage intensive.
将100MB的音频数据存储在内存中可能使存储量过大。
Plus, it makes maintenance and backups more intensive, since there’s more data to deal with.
另外，这将更多的数据处理将加重你维护和备份的难度。
They could process only so much data, and memory-intensive features, like animation and multi-media, were difficult to program.
它们只能处理很少的数据，而一些存储密集的功能，如动画和多媒体，也难以实现。
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