External memory algorithms optimize performance for large datasets from "summary" of Data Structures and Algorithms in Python by Michael T. Goodrich,Roberto Tamassia,Michael H. Goldwasser
External memory algorithms are designed to optimize performance for large datasets that cannot fit entirely in internal memory. These algorithms are crucial for handling massive amounts of data efficiently and effectively. In contrast to internal memory algorithms, which assume that all data fits in RAM, external memory algorithms take into account the limitations of external storage devices such as hard drives. The key idea behind external memory algorithms is to minimize the number of costly input/output operations between internal and external memory. Since accessing data from external storage is significantly slower than accessing data from internal memory, reducing the number of these operations is essential for improving performance. External memory algorithms achieve this by efficiently managing data transfers between internal and external memory. ...
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