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<MIT's Introduction to Algorithms, Lectures 22 and 23: Cache Oblivious Algorithms ⁄ >




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This is a happy and sad moment at the same time - I have finally reached the last two lectures of MIT's undergraduate algorithms course. These last two lectures are on a fairly new area of algorithm research called "cache oblivious algorithms."

Cache-oblivious algorithms take into account something that has been ignored in all the lectures so far, particularly, the multilevel memory hierarchy of modern computers. Retrieving items from various levels of memory and cache make up a dominant factor of running time, so for speed it is crucial to minimize these costs. The main idea of cache-oblivious algorithms is to achieve optimal use of caches on all levels of a memory hierarchy without knowledge of their size.

Cache-oblivious algorithms should not be confused with cache-aware algorithms. Cache-aware algorithms and data structures explicitly depend on various hardware configuration parameters, such as the cache size. Cache-oblivious algorithms do not depend on any hardware parameters. An example of cache-aware (not cache-oblivious) data structure is a B-Tree that has the explicit parameter B, the size of a node. The main disadvantage of cache-aware algorithms is that they are based on the knowledge of the memory structure and size, which makes it difficult to move implementations from one architecture to another. Another problem is that it is very difficult, if not impossible, to adapt some of these algorithms to work with multiple levels in the memory hierarchy. Cache-oblivious algorithms solve both problems.



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