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Cache hierarchy, or multi-level cache, is a memory architecture that uses a hierarchy of memory stores based on varying access speeds to cache data. Highly requested data is cached in high-speed access memory stores, allowing swifter access by central processing unit (CPU) cores.
The resulting load on memory use is known as pressure (respectively register pressure, cache pressure, and (main) memory pressure). Terms for data being missing from a higher level and needing to be fetched from a lower level are, respectively: register spilling (due to register pressure : register to cache), cache miss (cache to main memory ...
A CPU cache is a hardware cache used by the central processing unit (CPU) of a computer to reduce the average cost (time or energy) to access data from the main memory. [1] A cache is a smaller, faster memory, located closer to a processor core, which stores copies of the data from frequently used main memory locations.
Unlike the case of exclusive cache, where the unique memory capacity is the combined capacity of all caches in the hierarchy. [4] If the size of lower level cache is small and comparable with the size of higher level cache, there is more wasted cache capacity in inclusive caches.
AMAT's three parameters hit time (or hit latency), miss rate, and miss penalty provide a quick analysis of memory systems. Hit latency (H) is the time to hit in the cache. Miss rate (MR) is the frequency of cache misses, while average miss penalty (AMP) is the cost of a cache miss in terms of time. Concretely it can be defined as follows.
Processor performance increase due to cache hierarchy depends on the number of accesses to the cache that satisfy block requests from the cache (cache hits) versus those that do not. Unsuccessful attempts to read or write data from the cache (cache misses) result in lower level or main memory access, which increases latency.
Diagram of a CPU memory cache operation. In computing, a cache (/ k æ ʃ / ⓘ KASH) [1] 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.
Most general purpose computers use a hybrid split-cache modified Harvard architecture that appears to an application program to have a pure Princeton architecture machine with gigabytes of virtual memory, but internally (for speed) it operates with an instruction cache physically separate from a data cache, more like the Harvard model. [1]