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c = a + b In addition to support for vectorized arithmetic and relational operations, these languages also vectorize common mathematical functions such as sine. For example, if x is an array, then y = sin (x) will result in an array y whose elements are sine of the corresponding elements of the array x. Vectorized index operations are also ...
The OptimJ programming language is an extension of Java 5. As does Java, Optimj provides maps; but OptimJ also provides true associative arrays. Java arrays are indexed with non-negative integers; associative arrays are indexed with any type of key.
The earliest high-level programming languages, including FORTRAN (1957), Lisp (1958), COBOL (1960), and ALGOL 60 (1960), had support for multi-dimensional arrays, and so has C (1972). In C++ (1983), class templates exist for multi-dimensional arrays whose dimension is fixed at runtime [ 3 ] [ 5 ] as well as for runtime-flexible arrays.
While arrays in C are fixed, pointers to them are interchangeable. This flexibility allows C to manipulate any length array using the same code. It also leaves the programmer with the responsibility not to write outside the allocated array, as no checks are built in into the language. In Pascal, arrays are a distinct type from pointers.
The fundamental idea behind array programming is that operations apply at once to an entire set of values. This makes it a high-level programming model as it allows the programmer to think and operate on whole aggregates of data, without having to resort to explicit loops of individual scalar operations.
Elements of a newly created array may have undefined values (as in C), or may be defined to have a specific "default" value such as 0 or a null pointer (as in Java). In C++ a std::vector object supports the store, select, and append operations with the performance characteristics discussed above. Vectors can be queried for their size and can be ...
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Structure of arrays (SoA) is a layout separating elements of a record (or 'struct' in the C programming language) into one parallel array per field. [1] The motivation is easier manipulation with packed SIMD instructions in most instruction set architectures, since a single SIMD register can load homogeneous data, possibly transferred by a wide internal datapath (e.g. 128-bit).