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External memory algorithms and data structures: dealing with massive data
2001
ACM Computing Surveys
Data sets in large applications are often too massive to fit completely inside the computer's internal memory. The resulting input/output communication (or I/O) between fast internal memory and slower external memory (such as disks) can be a major performance bottleneck. In this article we survey the state of the art in the design and analysis of external memory (or EM) algorithms and data structures, where the goal is to exploit locality in order to reduce the I/O costs. We consider a variety
doi:10.1145/384192.384193
fatcat:tunz4fa3rrgv7hwbk7qsvahd5i