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Since the cache exists to bridge the speed gap, its performance measurement and metrics are important in designing and choosing various parameters like cache size, associativity, replacement policy, etc. Cache performance depends on cache hits and cache misses, which are the factors that create constraints to system performance.
The number of available hardware counters in a processor is limited while each CPU model might have a lot of different events that a developer might like to measure. Each counter can be programmed with the index of an event type to be monitored, like a L1 cache miss or a branch misprediction.
Basic LRU maintains an ordered list (the cache directory) of resource entries in the cache, with the sort order based on the time of most recent access. New entries are added at the top of the list, after the bottom entry has been evicted. Cache hits move to the top, pushing all other entries down.
An algorithm is fundamentally a set of rules or defined procedures that is typically designed and used to solve a specific problem or a broad set of problems.. Broadly, algorithms define process(es), sets of rules, or methodologies that are to be followed in calculations, data processing, data mining, pattern recognition, automated reasoning or other problem-solving operations.
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 ...
In this example, the URL is the tag, and the content of the web page is the data. The percentage of accesses that result in cache hits is known as the hit rate or hit ratio of the cache. The alternative situation, when the cache is checked and found not to contain any entry with the desired tag, is known as a cache miss. This requires a more ...
Loop tiling partitions a loop's iteration space into smaller chunks or blocks, so as to help ensure data used in a loop stays in the cache until it is reused. The partitioning of loop iteration space leads to partitioning of a large array into smaller blocks, thus fitting accessed array elements into cache size, enhancing cache reuse and eliminating cache size requirements.
JavaScript, Python, Prolog, Rust, JSON-LD: Open Source (Apache 2.0) Open source in-memory graph database designed for knowledge graph representation [13] TimesTen: now Oracle Corporation: 1997 Java, JDBC, ODBC, SQL, PLSQL, C Proprietary Standalone database or in-memory cache for Oracle Database: TPF (Transaction Processing Facility) IBM 1979 ...