Algorithms and data structures for memory hierarchies

在越来越多的应用领域，需要收集和分析大量数据，以提取战略业务决策所需的信息，并做出新的科学发现。例如，沃尔玛数PB大小的客户交易数据库，支持谷歌搜索引擎的海量网页索引，通过现代测序技术获得的大量基因组数据的收集和分析，以及使用激光雷达技术和卫星图像构建海量、高度详细的地理模型。这些海量数据为以前无法想象的新发现提供了巨大的机会，但从这些数据集中提取有用的信息需要能够处理它们的计算工具。

In an increasing number of application areas, massive amounts of data are collected and analyzed to extract the information needed for strategic business decisions and to make new scientific discoveries. Examples include Walmart's petabyte-sized customer transaction database, a massive index of web pages powering Google's search engine, the collection and analysis of large amounts of genome data made available through modern sequencing technologies, and the construction of massive, highly detailed geographic models using LIDAR technology and satellite imagery. These massive amounts of data present tremendous opportunities for new discoveries that were previously unimaginable, but extracting useful information from such data sets requires computational tools that are capable of processing them.