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6.3: The memory hierarchy

  • Page ID
    59428
  • At some point during this chapter, a question like the following might have occurred to you: “If caches are so much faster than main memory, why not make a really big cache and forget about memory?”

    Without going too far into computer architecture, there are two reasons: electronics and economics. Caches are fast because they are small and close to the CPU, which minimizes delays due to capacitance and signal propagation. If you make a cache big, it will be slower.

    Also, caches take up space on the processor chip, and bigger chips are more expensive. Main memory is usually dynamic random-access memory (DRAM), which uses only one transistor and one capacitor per bit, so it is possible to pack more memory into the same amount of space. But this way of implementing memory is slower than the way caches are implemented.

    Also main memory is usually packaged in a dual in-line memory module (DIMM) that includes 16 or more chips. Several small chips are cheaper than one big one.

    The trade-off between speed, size, and cost is the fundamental reason for caching. If there were one memory technology that was fast, big, and cheap, we wouldn’t need anything else.

    The same principle applies to storage as well as memory. Solid state drives (SSD) are fast, but they are more expensive than hard drives (HDD), so they tend to be smaller. Tape drives are even slower than hard drives, but they can store large amounts of data relatively cheaply.

    The following table shows typical access times, sizes, and costs for each of these technologies.

    Table \(\PageIndex{1}\): Memory access times, sizes, and costs.
    Device Access time Typical size Cost
    Register 0.5 ns 256 B ?
    Cache 1 ns 2 MiB ?
    DRAM 100 ns 4 GiB $10 / GiB
    SSD 10 µs 100 GiB $1 / GiB
    HDD 5 ms 500 GiB $0.25 / GiB
    Tape minutes 1-2 TiB $0.02 / GiB

    The number and size of registers depends on details of the architecture. Current computers have about 32 general-purpose registers, each storing one “word”. On a 32-bit computer, a word is 32 bits or 4 B. On a 64-bit computer, a word is 64 bits or 8 B. So the total size of the register file is 100–300 B.

    The cost of registers and caches is hard to quantify. They contribute to the cost of the chips they are on, but consumers don’t see that cost directly.

    For the other numbers in the table, I looked at the specifications for typical hardware for sale from online computer hardware stores. By the time you read this, these numbers will be obsolete, but they give you an idea of what the performance and cost gaps looked like at one point in time.

    These technologies make up the “memory hierarchy” (note that this use of “memory” also includes storage). Each level of the hierarchy is bigger and slower than the one above it. And in some sense, each level acts as a cache for the one below it. You can think of main memory as a cache for programs and data that are stored permanently on SSDs and HHDs. And if you are working with very large datasets stored on tape, you could use hard drives to cache one subset of the data at a time.

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