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Nested functions can be used for unstructured control flow, by using the return statement for general unstructured control flow.This can be used for finer-grained control than is possible with other built-in features of the language – for example, it can allow early termination of a for loop if break is not available, or early termination of a nested for loop if a multi-level break or ...
Some languages offer further facilities such as naming the various loop statements so that with multiple nested loops there is no doubt as to which loop is involved. Fortran 95, for example: X1 : DO I = 1 , N statements X2 : DO J = 1 , M statements IF ( trouble ) CYCLE X1 statements END DO X2 statements END DO X1
Both MATLAB and GNU Octave natively support linear algebra operations such as matrix multiplication, matrix inversion, and the numerical solution of system of linear equations, even using the Moore–Penrose pseudoinverse. [7] [8] The Nial example of the inner product of two arrays can be implemented using the native matrix multiplication operator.
Alternatives to multilevel breaks include single breaks, together with a state variable which is tested to break out another level; exceptions, which are caught at the level being broken out to; placing the nested loops in a function and using return to effect termination of the entire nested loop; or using a label and a goto statement.
is how one would use Fortran to create arrays from the even and odd entries of an array. 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;
MATLAB does include standard for and while loops, but (as in other similar applications such as APL and R), using the vectorized notation is encouraged and is often faster to execute. The following code, excerpted from the function magic.m , creates a magic square M for odd values of n (MATLAB function meshgrid is used here to generate square ...
The naïve algorithm using three nested loops uses Ω(n 3) communication bandwidth. Cannon's algorithm, also known as the 2D algorithm, is a communication-avoiding algorithm that partitions each input matrix into a block matrix whose elements are submatrices of size √ M/3 by √ M/3, where M is the size of fast memory. [28]
Loop interchange on this example can improve the cache performance of accessing b(j,i), but it will ruin the reuse of a(i) and c(i) in the inner loop, as it introduces two extra loads (for a(i) and for c(i)) and one extra store (for a(i)) during each iteration. As a result, the overall performance may be degraded after loop interchange.