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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.
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.
Cache hierarchy, or multi-level cache, is a memory architecture that uses a hierarchy of memory stores based on varying access speeds to cache data.Highly requested data is cached in high-speed access memory stores, allowing swifter access by central processing unit (CPU) cores.
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.
Rarely, but especially in algorithms, coherence can instead refer to the locality of reference. Multiple copies of the same data can exist in different cache simultaneously and if processors are allowed to update their own copies freely, an inconsistent view of memory can result.
Temporal locality, where the algorithm fetches the same pieces of memory multiple times; Spatial locality, where the subsequent memory accesses are adjacent or nearby memory addresses. Cache-oblivious algorithms are typically analyzed using an idealized model of the cache, sometimes called the cache-oblivious model. This model is much easier to ...