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The dependency graph contains all local dependencies with distance not greater than the vector size. So, if the vector register is 128 bits, and the array type is 32 bits, the vector size is 128/32 = 4. All other non-cyclic dependencies should not invalidate vectorization, since there won't be any concurrent access in the same vector instruction.
The following containers are defined in the current revision of the C++ standard: array, vector, list, forward_list, deque. Each of these containers implements different algorithms for data storage, which means that they have different speed guarantees for different operations: [1] array implements a compile-time non-resizable array.
The J2SE 5.0 release of Java introduced the Iterable interface to support an enhanced for loop for iterating over collections and arrays. Iterable defines the iterator() method that returns an Iterator. [18]: 266 Using the enhanced for loop, the preceding example can be rewritten as
2.25 ParaSail. 2.26 Pascal. 2.27 Perl. 2.28 ... 1.5.0. [14] Official sources use several names for the construct. ... SystemVerilog supports iteration over any vector ...
In these languages, an operation that operates on entire arrays can be called a vectorized operation, [1] regardless of whether it is executed on a vector processor, which implements vector instructions. Array programming primitives concisely express broad ideas about data manipulation.
Another common use of vectorized indices is a filtering operation. Consider a clipping operation of a sine wave where amplitudes larger than 0.5 are to be set to 0.5. Using S-Lang, this can be done by y = sin(x); y[where(abs(y)>0.5)] = 0.5;
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).
It is the vector equivalent of register indirect addressing, with gather involving indexed reads, and scatter, indexed writes. Vector processors (and some SIMD units in CPUs ) have hardware support for gather and scatter operations, as do many input/output systems, allowing large data sets to be transferred to main memory more rapidly.