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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]
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.
Automated In-Memory Dynamic Caching for SQL Server OLTP applications and databases. Code-free, Dynamic Caching, Relational SAP HANA: SAP SE: 2012 Proprietary SAP HANA, short for 'High Performance Analytic Appliance' is an in-memory, column-oriented, relational database management system written in C, C++: solidDB: Unicom Global 1992 Proprietary
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.
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.
Each time a reference is made to that block the counter is increased by one. When the cache reaches capacity and has a new block waiting to be inserted the system will search for the block with the lowest counter and remove it from the cache, in case of a tie (i.e., two or more keys with the same frequency), the Least Recently Used key would be ...
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 ...