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Engineering LibreTexts

7.7: Caching policy

  • Page ID
    43009
  • The memory hierarchy suggests a framework for thinking about caching. At every level of the hierarchy, we have to address four fundamental questions of caching:

    • Who moves data up and down the hierarchy? At the top of the hierarchy, register allocation is usually done by the compiler. Hardware on the CPU handles the memory cache. Users implicitly move data from storage to memory when they execute programs and open files. But the operating system also moves data back and forth between memory and storage. At the bottom of the hierarchy, administrators move data explicitly between disk and tape.
    • What gets moved? In general, block sizes are small at the top of the hierarchy and bigger at the bottom. In a memory cache, a typical block size is 128 B. Pages in memory might be 4 KiB, but when the operating system reads a file from disk, it might read 10s or 100s of blocks at a time.
    • When does data get moved? In the most basic cache, data gets moved into cache when it is used for the first time. But many caches use some kind of “prefetching”, meaning that data is loaded before it is explicitly requested. We have already seen one form of prefetching: loading an entire block when only part of it is requested.
    • Where in the cache does the data go? When the cache is full, we can’t bring anything in without kicking something out. Ideally, we want to keep data that will be used again soon and replace data that won’t.

    The answers to these questions make up the “cache policy”. Near the top of the hierarchy, cache policies tend to be simple because they have to be fast and they are implemented in hardware. Near the bottom of the hierarchy, there is more time to make decisions, and well-designed policies can make a big difference.

    Most cache policies are based on the principle that history repeats itself; if we have information about the recent past, we can use it to predict the immediate future. For example, if a block of data has been used recently, we expect it to be used again soon. This principle suggests a replacement policy called “least recently used,” or LRU, which removes from the cache a block of data that has not been used recently. For more on this topic, see http://en.Wikipedia.org/wiki/Cache_algorithms.

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