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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.
The cache is divided into a Low Inter-reference Recency (LIR) and a High Inter-reference Recency (HIR) partition. The LIR partition is to store the most highly ranked pages (LIR pages) and the HIR partition is to store some of the other pages (HIR pages). The LIR partition holds the majority of the cache, and all LIR pages are resident in the ...
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.
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 ...
An example roofline model with locality walls. The wall labeled as 3 C's denotes the presence all three types of cache misses: compulsory, capacity and conflict misses. The wall labeled as 2 C's represent the presence of either compulsory and capacity or compulsory and conflict misses.
An optimal cache-oblivious algorithm is a cache-oblivious algorithm that uses the cache optimally (in an asymptotic sense, ignoring constant factors). Thus, a cache-oblivious algorithm is designed to perform well, without modification, on multiple machines with different cache sizes, or for a memory hierarchy with different levels of cache ...
NUMA is beneficial for workloads with high memory locality of reference and low lock contention, because a processor may operate on a subset of memory mostly or entirely within its own cache node, reducing traffic on the memory bus. [2] NUMA architectures logically follow in scaling from symmetric multiprocessing (SMP) architectures.