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Most APLs expose only a small number of scalar types to the user: one or two [[numeric]] types (such as double-precision real or [[complex]] numbers), and a single [[character]] type. However, for performance reasons these types can be implemented internally using various subset types. For example, [[APL\360#Internal types|APL\360 uses]] numeric arrays of 1-bit [[Boolean]]s, 4-byte integers, or 8-byte floating point numbers, but converts between them transparently so that from the user's perspective all numbers behave like 8-byte floats (as this type contains the others). In [[Dyalog APL]] this hierarchy is [[Dyalog APL#Internal types|significantly expanded]], adding 1-byte and 2-byte integers as well as 16-byte [[complex]] numbers containing the other types (however, Dyalog also allows the user access to [[decimal float]]s if requested, which breaks the strict hierarchy). | Most APLs expose only a small number of scalar types to the user: one or two [[numeric]] types (such as double-precision real or [[complex]] numbers), and a single [[character]] type. However, for performance reasons these types can be implemented internally using various subset types. For example, [[APL\360#Internal types|APL\360 uses]] numeric arrays of 1-bit [[Boolean]]s, 4-byte integers, or 8-byte floating point numbers, but converts between them transparently so that from the user's perspective all numbers behave like 8-byte floats (as this type contains the others). In [[Dyalog APL]] this hierarchy is [[Dyalog APL#Internal types|significantly expanded]], adding 1-byte and 2-byte integers as well as 16-byte [[complex]] numbers containing the other types (however, Dyalog also allows the user access to [[decimal float]]s if requested, which breaks the strict hierarchy). | ||
When working with large arrays, an implementation can dynamically choose the type of arrays as execution progresses. For some operations it is advantageous to force an array to the smallest possible type, a procedure known as "squeezing". The ability to dynamically change array type can be a practical advantage of interpreted array languages over statically typed compiled languages, since the interpreter is sometimes able to choose a smaller type than the compiler. This may be because the programmer chooses a suboptimal type or because the interpreter can take advantage of situations where an array could possible require a larger type, but doesn't in a particular instance of a program. With an implementation using [[vector | When working with large arrays, an implementation can dynamically choose the type of arrays as execution progresses. For some operations it is advantageous to force an array to the smallest possible type, a procedure known as "squeezing". The ability to dynamically change array type can be a practical advantage of interpreted array languages over statically typed compiled languages, since the interpreter is sometimes able to choose a smaller type than the compiler. This may be because the programmer chooses a suboptimal type or because the interpreter can take advantage of situations where an array could possible require a larger type, but doesn't in a particular instance of a program. With an implementation using [[vector instructions]], a smaller internal type can directly translate to faster execution because a vector register (and hence a vector operation) can fit more elements when they are smaller.<ref name="advantage"/> | ||
=== Fast array operations === | === Fast array operations === | ||