With the exponential growth of data comes an ever-increasing need to process and analyze the so-called Big Data. High performance computing architectures have been devised to address the needs for handling Big Data processing not only from a transaction processing viewpoint but also from an analytics perspective. This book provides a comprehensive view on the recent trend toward high performance computing architectures especially as it relates to analytics and data mining. Topics that are covered include: big data (and its characteristics), high performance computing for analytics, massively parallel processing (MPP) databases, algorithms for big data, in-memory databases, implementation of machine learning algorithms for big data platforms, and analytics environments. However none gives a historical and comprehensive view of all these separate topics in a single document. Through the understanding of these topics corporations can create an ideal analytic environment that is better suited to the challenges of todays analytics demands.