Data-intensive computing: architectures, algorithms, and applications

摘要

The recent shift from central processing unit (CPU)-intensive computation toward data-intensive computation has been supported by several research and innovation initiatives. These range from computational paradigms, like the popular MapReduce programming model and infrastructure, to advanced and customized dedicated hardware, such as using graphics processing units (GPUs) to run general-purpose applications. The motivations for research on data-intensive computations are numerous. Big data will soon be everywhere: it comes from large physics experiments (such as the Hadron Collider experiments in CERN), popular crowdsourcing projects, social networks, and mobile applications, and it represents the outcomes of genetic and pharmacological research.