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m the word "data" is plural Tag: Reverted |
Reverted good faith edits by M C Wendl (talk): It is both |
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{{cite web|url=http://www.oxforddictionaries.com/definition/english/cache|archive-url=https://web.archive.org/web/20120818122040/http://oxforddictionaries.com/definition/english/cache|url-status=dead|archive-date=18 August 2012|title=Cache|work=Oxford Dictionaries|access-date=2 August 2016}}</ref> is a hardware or software component that stores data so that future requests for that data can be served faster; the data stored in a cache might be the result of an earlier computation or a copy of data stored elsewhere. A '''cache hit''' occurs when the requested data can be found in a cache, while a '''cache miss''' occurs when it cannot. Cache hits are served by reading data from the cache, which is faster than recomputing a result or reading from a slower data store; thus, the more requests that can be served from the cache, the faster the system performs.<ref>{{Cite journal|last1=Zhong|first1=Liang|last2=Zheng|first2=Xueqian|last3=Liu|first3=Yong|last4=Wang|first4=Mengting|last5=Cao|first5=Yang|date=February 2020|title=Cache hit ratio maximization in device-to-device communications overlaying cellular networks|url=http://dx.doi.org/10.23919/jcc.2020.02.018|journal=China Communications|volume=17|issue=2|pages=232–238|doi=10.23919/jcc.2020.02.018|s2cid=212649328|issn=1673-5447}}</ref>
To be cost-effective, caches must be relatively small. Nevertheless, caches are effective in many areas of computing because typical [[Application software|computer applications]] access data with a high degree of [[locality of reference]]. Such access patterns exhibit temporal locality, where data
==Motivation==
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When the cache client (a CPU, web browser, [[operating system]]) needs to access data presumed to exist in the backing store, it first checks the cache. If an entry can be found with a tag matching that of the desired data, the data in the entry is used instead. This situation is known as a '''cache hit'''. For example, a web browser program might check its local cache on disk to see if it has a local copy of the contents of a web page at a particular [[URL]]. 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 expensive access of data from the backing store. Once the requested data
During a cache miss, some other previously existing cache entry is typically removed in order to make room for the newly retrieved data. The [[Heuristic (computer science)|heuristic]] used to select the entry to replace is known as the [[Cache replacement policies|replacement policy]]. One popular replacement policy, least recently used (LRU), replaces the oldest entry, the entry that was accessed less recently than any other entry. More sophisticated caching algorithms also take into account the frequency of use of entries.
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A write-back cache is more complex to implement since it needs to track which of its locations have been written over and mark them as ''dirty'' for later writing to the backing store. The data in these locations are written back to the backing store only when they are evicted from the cache, a process referred to as a ''lazy write''. For this reason, a read miss in a write-back cache will often require two memory backing store accesses to service: one for the write back, and one to retrieve the needed data. Other policies may also trigger data write-back. The client may make many changes to data in the cache, and then explicitly notify the cache to write back the data.
Since no data
* ''Write allocate'' (also called ''fetch on write''): data at the missed-write ___location is loaded to cache, followed by a write-hit operation. In this approach, write misses are similar to read misses.
* ''No-write allocate'' (also called ''write-no-allocate'' or ''write around''): data at the missed-write ___location is not loaded to cache, and is written directly to the backing store. In this approach, data
Both write-through and write-back policies can use either of these write-miss policies, but usually they are paired.<ref name="HennessyPatterson2011">{{cite book|last1=Hennessy|first1=John L.|url=https://books.google.com/books?id=v3-1hVwHnHwC&pg=SL2-PA12|title=Computer Architecture: A Quantitative Approach|last2=Patterson|first2=David A.|publisher=Elsevier|year=2011|isbn=978-0-12-383872-8|page=B–12|language=en}}</ref><ref>{{cite book|title=Computer Architecture A Quantitative Approach|last1=Patterson|first1=David A.|last2=Hennessy|first2=John L.|isbn=1-55860-069-8|date=1990|page=413|publisher=Morgan Kaufmann Publishers}}</ref>
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