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Paging obviously benefits from temporal and spatial locality. A cache is a simple example of exploiting temporal locality, because it is a specially designed, faster but smaller memory area, generally used to keep recently referenced data and data near recently referenced data, which can lead to potential performance increases.
Database caching is a process included in the design of computer applications which generate web pages on-demand (dynamically) by accessing backend databases.. When these applications are deployed on multi-tier environments that involve browser-based clients, web application servers and backend databases, [1] [2] middle-tier database caching is used to achieve high scalability and performance.
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]
Another definition is: "a multiprocessor is cache consistent if all writes to the same memory location are performed in some sequential order". [7] 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 ...
This is a form of caching the results of a query, similar to memoization of the value of a function in functional languages, and it is sometimes described as a form of precomputation. [2] [3] As with other forms of precomputation, database users typically use materialized views for performance reasons, i.e. as a form of optimization. [4]
Data layout is critical for correctly passing arrays between programs written in different programming languages. It is also important for performance when traversing an array because modern CPUs process sequential data more efficiently than nonsequential data. This is primarily due to CPU caching which exploits spatial locality of reference. [1]
SQL, ODBC, JDBC, ADO.NET, Embedded SQL, C, C++, Python Proprietary Mimer SQL is a general purpose relational database server that can be configured to run fully in-memory. Mimer SQL has full ACID support, support for stored procedures and is the only database that has a full score on SQL compliance Mnesia: Ericsson: 2014 Open Source Erlang License
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.