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A snippet of C code which prints "Hello, World!". The syntax of the C programming language is the set of rules governing writing of software in C. It is designed to allow for programs that are extremely terse, have a close relationship with the resulting object code, and yet provide relatively high-level data abstraction.
For example, the iterator method is supposed to return an Iterator object, and the pull-one method is supposed to produce and return the next value if possible, or return the sentinel value IterationEnd if no more values could be produced. The following example shows an equivalent iteration over a collection using explicit iterators:
In this example, there is an output dependence between the jth element in S1 and the j+1th element in S2. Here, c[j+1] in statement S2 is written to in one iteration. In the next iteration, c[j] in statement S2, which is the same memory location as c[j+1] in the previous iteration, is written to again.
In C++, a class can overload all of the pointer operations, so an iterator can be implemented that acts more or less like a pointer, complete with dereference, increment, and decrement. This has the advantage that C++ algorithms such as std::sort can immediately be applied to plain old memory buffers, and that there is no new syntax to learn.
The following example demonstrates dynamic loop unrolling for a simple program written in C. Unlike the assembler example above, pointer/index arithmetic is still generated by the compiler in this example because a variable (i) is still used to address the array element.
a b c Deep breaks may be accomplished in APL, C, C++ and C# through the use of labels and gotos. a Iteration over objects was added in PHP 5. a b c A counting loop can be simulated by iterating over an incrementing list or generator, for instance, Python's range() .
Loop splitting is a compiler optimization technique. It attempts to simplify a loop or eliminate dependencies by breaking it into multiple loops which have the same bodies but iterate over different contiguous portions of the index range.
Automatic vectorization, in parallel computing, is a special case of automatic parallelization, where a computer program is converted from a scalar implementation, which processes a single pair of operands at a time, to a vector implementation, which processes one operation on multiple pairs of operands at once.