Cluster storage is an important solution to large-scale data storage systems.
集群存储是解决大规模数据存储的重要方法。
The best-known is Hadoop, a large-scale data storage approach being used by a growing number of businesses.
最为著名的是Hadoop，被数目不断增长的商业机构使用的一种大型数据储存方式。
2013-2016, Privacy Protection Model and Its Core Techniques for Sharing Large-scale Data, China 973 Program, Co-PI.
大规模数据共享的隐私保护模型与关键技术研究，973前期研究专项， 2013-2016，参与。
One way to think about R is that it's an efficient, flexible tool for managing, summarizing, and exploiting large-scale data.
应该认识到 R是一个可以管理、总结和利用大规模数据的有效而灵活的工具。
Advances in mass spectrometry-driven proteomics rely on robust bioinformatics tools that enable large-scale data analysis.
质谱驱动的蛋白质组学的进展依赖于使得大规模数据分析成为可能的鲁棒的生物信息学工具。
Since its introduction in 1984, GAUSS has been a standard for serious number crunching and complex modeling of large-scale data.
从1984年推广使用以来，Gauss也成为大规模数据处理和复杂建模的标准。
It's a challenging problem to improve the scalability, adaptability and performance of replica location service in large-scale data grids.
如何提高副本定位服务的可扩展性和自适应性，是大规模数据网格系统面临的重要难题。
A new PricewaterhouseCoopers Technology report explains how the Semantic Web and Linked data can help enterprises manage their large-scale data better.
普华永道(PricewaterhouseCoopers)最新的一封技术报告(link)阐释了语义网和连接数据将如何更好的帮助企业管理大规模的数据。
The execute model of single instruction, multiple threads (SIMT) of CUDA is very suitable for parallel to execute the same operations for large-scale data;
CUDA的单指令、多线程（SIMT）的执行模型，很适合大型数据上并行执行相同的操作；
High performance computer technology is the base of the modern scientific and technological researches, engineering development and large-scale data processing.
高性能计算机技术是现代科学技术研究、工程技术开发和大规模数据处理的基础。
The answer, according to PwC, is Semantic Web techniques. PwC believes that the Semantic Web offers a practical way to address the problem of large-scale data integration.
根据普华永道的报告，问题的答案是语义网技术，普华永道相信，语义网为解决大规模的数据整合问题提供了一种实际可行的方法。
Precision Medicine relies on advent medical imaging technique, fusion of multi-modality medical imaging and information, and large-scale data mining on medical cases.
医学成像新技术、多模态医学成像的图像与信息融合、大数据病例的挖掘，是实现临床精准医疗的重要工程基础。
Large-scale data acquisition may bring the danger of congestion in the condition of limited hardware limits, cause large consumptions of nodes or even network paralysis.
在有限的硬件条件下，大规模数据采集易使网络产生拥塞现象，并造成节点能耗大幅度增加，严重时会造成网络的瘫痪。
Particularly in large-scale data processing to the original Gauss wave million for the improvement of law-equation in a significant way to enhancing the speed of data processing systems.
特别是在大规模数据的处理上，对原有的高斯消元法解方程进行了改进，在很大程度上提高了系统处理数据的速度。
Based on the major problems of FCM, the modification methods are put forward, and the large-scale data experiments test and analyze the improvement effects of different modification methods.
针对FCM的主要问题，从不同的角度提出了改进的方法，并通过大规模的实验数据测试分析了不同方法的改进效果。
The geostationary meteorological satellite ground application system is a main system with high speed communication, large-scale data processing, product service giving, and mass data storage.
静止气象卫星地面应用系统是一个具有高速通信、大规模数据处理、高时效产品服务、海量数据存储功能的大型业务应用系统。
This algorithm does not have to standardize the data, uses a kind of global criterion function based on the statistical histogram to depict clusters, specially is suitable for the large-scale data.
该算法不需标准化数据，应用一种基于统计直方图的全局准则函数进行聚类，特别适用于大规模数据。
Data Grid is the distributed management of large-scale data and the infrastructure analysis; it has implemented uniform storage, management, access and transmission of distributed, heterogeneous data.
数据网格是海量数据分布式管理和分析的基础设施，它实现了分布、异构空间数据的统一存储、管理、访问和传输。
While your personal computer only keeps one copy of a file, large-scale services like Facebook rely on what are called content delivery networks to manage data and distribution.
虽然你的个人电脑只能保存一个文件的一个副本，但像Facebook 这样的大型服务项目，则会依赖于所谓的内容分发网络来管理数据和分发。
To achieve performance improvements, they also need to operate on large scale data - they rely on large scale cluster processing.
为了提升性能，他们还需要操纵大范围数据：使用大范围集群处理。
Therefore, the data cleansing server needs to be able to scale in order to process large data volumes.
因此，数据清理服务器需要能够进行扩展，以处理大量数据。
This extended use of the execution flow notation is motivated by the need to provide a hierarchy of data representation, which is necessary for large-scale, distributed traces.
这种扩展的主要原因是在大型分布式应用程序的跟踪时需要提供分层次的数据表示形式。
We were able to scale the WebSphere Customer Center application to large user, transaction, and data volumes and offered our clients many extension mechanisms.
我们可以扩展WebSphereCustomerCenter应用程序，从而满足大规模的用户、事务和数据量，并为我们的客户机提供很多扩展机制。
While Mnesia excels at scalability and low latency in transactions on horizontally fragmented data, one remaining challenge may be how it will scale in terms of very large datasets.
对于横向分片数据，Mnesia在伸缩性和低延迟事务上表现突出，接下来的一个挑战可能是对于超大规模数据集它如何伸展。
Last month, Amazon's CTO Werner Vogels posted an article describing approaches to tolerate eventual data consistency in large-scale distributed systems.
上个月，亚马逊公司的CTOWernerVogels发表了一篇文章，描述在大型分布式系统中容忍最终数据一致性的方法。
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)。
The theme of changing data architectures was noticeable throughout the conference, and from the perspective of many different companies, including large scale users of data as well as vendors.
在整个会议上，改变数据结构的主题都非常引人注目，很多不同的公司都提出了自己的观点，包括很多数据用户和厂商。
The theme of changing data architectures was noticeable throughout the conference, and from the perspective of many different companies, including large scale users of data as well as vendors.
在整个会议上，改变数据结构的主题都非常引人注目，很多不同的公司都提出了自己的观点，包括很多数据用户和厂商。
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