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  2. Locality of reference - Wikipedia

    en.wikipedia.org/wiki/Locality_of_reference

    In computer science, locality of reference, also known as the principle of locality, [1] is the tendency of a processor to access the same set of memory locations repetitively over a short period of time. [2] There are two basic types of reference locality – temporal and spatial locality.

  3. Memory access pattern - Wikipedia

    en.wikipedia.org/wiki/Memory_access_pattern

    In computing, a memory access pattern or IO access pattern is the pattern with which a system or program reads and writes memory on secondary storage.These patterns differ in the level of locality of reference and drastically affect cache performance, [1] and also have implications for the approach to parallelism [2] [3] and distribution of workload in shared memory systems. [4]

  4. Memory hierarchy - Wikipedia

    en.wikipedia.org/wiki/Memory_hierarchy

    Most modern CPUs are so fast that for most program workloads, the bottleneck is the locality of reference of memory accesses and the efficiency of the caching and memory transfer between different levels of the hierarchy [citation needed]. As a result, the CPU spends much of its time idling, waiting for memory I/O to complete.

  5. LIRS caching algorithm - Wikipedia

    en.wikipedia.org/wiki/LIRS_caching_algorithm

    LIRS (Low Inter-reference Recency Set) is a page replacement algorithm with an improved performance over LRU (Least Recently Used) and many other newer replacement algorithms. [1] This is achieved by using "reuse distance" [ 2 ] as the locality metric for dynamically ranking accessed pages to make a replacement decision.

  6. Row- and column-major order - Wikipedia

    en.wikipedia.org/wiki/Row-_and_column-major_order

    This is primarily due to CPU caching which exploits spatial locality of reference. [1] In addition, contiguous access makes it possible to use SIMD instructions that operate on vectors of data. In some media such as magnetic-tape data storage , accessing sequentially is orders of magnitude faster than nonsequential access.

  7. Cache replacement policies - Wikipedia

    en.wikipedia.org/wiki/Cache_replacement_policies

    The most efficient caching algorithm would be to discard information which would not be needed for the longest time; this is known as Bélády's optimal algorithm, optimal replacement policy, or the clairvoyant algorithm. Since it is generally impossible to predict how far in the future information will be needed, this is unfeasible in practice.

  8. Page replacement algorithm - Wikipedia

    en.wikipedia.org/wiki/Page_replacement_algorithm

    Locality of reference of user software has weakened. This is mostly attributed to the spread of object-oriented programming techniques that favor large numbers of small functions, use of sophisticated data structures like trees and hash tables that tend to result in chaotic memory reference patterns, and the advent of garbage collection that ...

  9. Cache placement policies - Wikipedia

    en.wikipedia.org/wiki/Cache_placement_policies

    Cache placement policies are policies that determine where a particular memory block can be placed when it goes into a CPU cache.A block of memory cannot necessarily be placed at an arbitrary location in the cache; it may be restricted to a particular cache line or a set of cache lines [1] by the cache's placement policy.