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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.
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]
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.
In computer architecture, cache coherence is the uniformity of shared resource data that is stored in multiple local caches. In a cache coherent system, if multiple clients have a cached copy of the same region of a shared memory resource, all copies are the same.
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.
Note how the use of A[i][j] with multi-step indexing as in C, as opposed to a neutral notation like A(i,j) as in Fortran, almost inevitably implies row-major order for syntactic reasons, so to speak, because it can be rewritten as (A[i])[j], and the A[i] row part can even be assigned to an intermediate variable that is then indexed in a separate expression.
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 ...
Computer software is said to exhibit scalable locality [1] if it can continue to make use of processors that out-pace their memory systems, to solve ever larger problems. This term is a high-performance uniprocessor analog of the use of scalable parallelism to refer to software for which increasing numbers of processors can be employed for ...