Prediction or explicit prefetching might also guess where future reads will come from and make requests ahead of time if done correctly the latency is bypassed altogether. This is mitigated by reading in large chunks, in the hope that subsequent reads will be from nearby locations. it can take hundreds of clock cycles for a modern 4 GHz processor to reach DRAM. The buffering provided by a cache benefits one or both of latency and throughput ( bandwidth):Ī larger resource incurs a significant latency for access – e.g.

There is an inherent trade-off between size and speed (given that a larger resource implies greater physical distances) but also a tradeoff between expensive, premium technologies (such as SRAM) vs cheaper, easily mass-produced commodities (such as DRAM or hard disks). Such access patterns exhibit temporal locality, where data is requested that has been recently requested already, and spatial locality, where data is requested that is stored physically close to data that has already been requested. Nevertheless, caches have proven themselves in many areas of computing, because typical computer applications access data with a high degree of locality of reference. To be cost-effective and to enable efficient use of data, caches must be relatively small.

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. A cache hit occurs when the requested data can be found in a cache, while a cache miss occurs when it cannot. In computing, a cache ( / k æ ʃ/ ( listen) KASH) 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.

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