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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]
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.
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.
[1] [2] The novelty of PGAS is that the portions of the shared memory space may have an affinity for a particular process, thereby exploiting locality of reference in order to improve performance. A PGAS memory model is featured in various parallel programming languages and libraries, including: Coarray Fortran , Unified Parallel C , Split-C ...
In computing, cache replacement policies (also known as cache replacement algorithms or cache algorithms) are optimizing instructions or algorithms which a computer program or hardware-maintained structure can utilize to manage a cache of information. Caching improves performance by keeping recent or often-used data items in memory locations ...
In a multilevel cache hierarchy, the miss pattern of the higher level cache becomes the re-reference pattern of the immediate lower level cache.Hartstein et al. [4] found that whereas the cache misses for lower levels do not follow a strict power law, as long as the lower level cache is considerably larger than the higher level cache, the miss rate function can be approximated to the power law.
In computing, cache algorithms (also frequently called cache replacement algorithms or cache replacement policies) are optimizing instructions—or algorithms—that a computer program or a hardware-maintained structure can follow in order to manage a cache of information stored on the computer. When the cache is full, the algorithm ...