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Locality of Reference: How Time and Nearby Memory Shape Cache Behavior

Locality of reference describes how program accesses tend to cluster over time and address space. See how temporal and spatial locality shape cache behavior.
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Locality of reference is the tendency for a program to access the same data again soon or to access data near a recently used memory address. The first pattern is temporal locality; the second is spatial locality. Caches take advantage of both by keeping recently used items close to the processor and fetching data in blocks that include nearby addresses.

What locality of reference means

A program’s memory and instruction accesses often cluster in time or address space rather than being completely random. That pattern is called locality of reference. It is a tendency, not a promise that every program or every access will behave the same way. Cornell’s CS 3410 cache notes and the University of Texas at Austin’s CS429 Cache I lecture introduce locality as the behavior that makes caching useful.

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Temporal versus spatial locality

Type What is likely to happen Example How a cache uses it
Temporal locality The same item is accessed again soon. A loop reuses its instructions or repeatedly reads and updates an accumulator. Keep recently accessed items available for reuse.
Spatial locality Addresses near a recently accessed address are accessed soon. A program reads consecutive elements of a contiguous array. Fetch a block that includes the requested address and neighboring addresses.

The key distinction is the dimension each pattern concerns: temporal locality is about when an item is reused; spatial locality is about where an access is relative to another address.

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Temporal locality: reuse over time

If a program uses a value, instruction, or other item, it may use that same item again in the near future. For instance, a loop may repeatedly execute the same instructions and update the same accumulator. A cache can retain recently accessed data so a later access to it can be served without fetching it again from slower memory.

Spatial locality: access near an address

If a program accesses one address, it may soon access addresses nearby. A common example is traversing an array in order: after reading a[i], the program reads a[i+1]. When array elements are stored contiguously, those accesses are close together in address space. This is why caches commonly move data in blocks rather than fetching only one isolated address.

Sequentiality is narrower than spatial locality

Sequential access is a particularly regular spatial pattern: after address s, the next access is likely to be s + 1 within a short sequence of references. Spatial locality does not require accesses to be strictly consecutive; it only describes a tendency for addresses near one another to be used. The University of Massachusetts Amherst’s basic cache tutorial treats sequentiality as a restricted form of spatial locality.

How one loop shows both forms

int sum = 0;
for (int i = 0; i < n; i++) {
    sum += a[i];
}
  • Temporal locality: the loop reuses its instructions, and the accumulator sum is read and updated repeatedly.
  • Spatial locality: the loop reads successive array elements, a[i] and then a[i+1].

The example illustrates likely access patterns, not a guarantee about how every compiler, processor, or workload will behave. The University of Toronto’s ECE243 cache notes also explain locality through loop and array access.

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Why locality matters to caches

A cache is a small, faster storage layer between a processor and larger, slower memory. When recently used data is accessed again, temporal locality gives the cache a reason to keep it available. When nearby addresses are likely to be used, spatial locality gives the cache a reason to fetch a block containing the requested address and its neighbors. MIT OpenCourseWare’s Computation Structures annotated slides describe this block movement in terms of transferring data from DRAM into SRAM.

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Locality explains why these cache strategies often help, but it does not establish a particular hit rate or performance gain. The benefit depends on the program’s actual access pattern and whether its later accesses match what the cache retained or fetched.

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