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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.
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 ...
Free lists have the disadvantage, inherited from linked lists, of poor locality of reference and so poor data cache utilization, and they do not automatically consolidate adjacent regions to fulfill allocation requests for large regions, unlike the buddy allocation system. Nevertheless, they are still useful in a variety of simple applications ...
Having frequently-used nodes near the root is an advantage for many practical applications (also see locality of reference), and is particularly useful for implementing caches and garbage collection algorithms. Advantages include: Comparable performance: Average-case performance is as efficient as other trees. [3]
The effectiveness of loop interchange depends on and must be considered in light of the cache model used by the underlying hardware and the array model used by the compiler. In C programming language , array elements in the same row are stored consecutively in memory (a[1,1], a[1,2], a[1,3]) ‒ in row-major order .