simd

Syntax

#pragma simd [clause[ [,] clause]...]

where clause can be any of the following:

• vectorlength(vl_list)

• private(expr_list, expr)

• linear(var_step_list)

• reduction(oper_var_list)

• [no]assert

Arguments

vectorlength(n1[, n2]...)	n is a vector length (VL). It must be an integer that is a power of 2; the value must be 2, 4, 8, or 16. If you specify more than one n, the vectorizor will choose the VL from the values specified. Causes each iteration in the vector loop to execute the computation equivalent to n iterations of scalar loop execution. Multiple vectorlength clauses are merged as a union.
private(var1[, var2]...)	var is a scalar variable. Causes each variable to be private to each iteration of a loop. Unless the compiler can prove that initial and last values are unused, the initial value is broadcasted to all private instances, and the last value is copied out from the last iteration instance. Multiple private clauses are merged as a union.
linear(var1:step1 [,var2:step2]...)	var is a scalar variable. step is a compile-time positive, integer constant expression. For each iteration of a scalar loop, var1 is incremented by step1, var2 is incremented by step2, and so on. Therefore, every iteration of the vector loop increments the variables by VL*step1, VL*step2, …, to VL*stepN, respectively. If more than one step is specified for a var, a compile-time error occurs. Multiple linear clauses are merged as a union.
reduction(oper:var1 [,var2]…)	oper is a reduction operator. var is a scalar variable. Applies the vector reduction indicated by oper to var1, var2, …, varN. The simd pragma may have multiple reduction clauses with the same or different operators. If more than one reduction operator is associated with a var, a compile-time error occurs.
[no]assert	Directs the compiler to assert or not to assert when the vectorization fails. The default is noassert. If this clause is specified more than once, a compile-time error occurs.

Description

The simd pragma is used to guide the compiler to vectorize more loops. Vectorization using the simd pragma complements (but does not replace) the fully automatic approach.

If you specify the simd pragma with no clause, default rules are in effect for variable attributes, vector length, and so forth

You can only specify a particular variable in at most one instance of a private, linear, or reduction clause.

If the compiler is unable to vectorize a loop, a warning will be emitted (use assert clause to make it an error).

If the vectorizer has to stop vectorizing a loop for some reason, the fast floating-point model is used for the SIMD loop.

Note that the simd pragma may not affect all auto-vectorizable loops. Some of these loops do not have a way to describe the SIMD vector semantics.

The following restrictions apply to the simd pragma:

• The countable loop for the simd pragma has to conform to the for-loop style of an OpenMP worksharing loop construct. Additionally, the loop control variable must be a signed integer type.

• The vector values must be signed 8-, 16-, 32-, or 64-bit integers, single or double-precision floating point numbers, or single or double-precision complex numbers.

• A SIMD loop cannot contain another loop in it; no loop nesting is allowed. Note that inlining can create such an inner loop and cause an error, which may not be obvious at the source level.

• A SIMD loop performs memory references unconditionally. Therefore, all address computations must result in valid memory addresses, even though such locations may not be accessed if the loop is executed sequentially.

To disable transformations that enables more vectorization, specify options -no-vec -no-simd (Linux* and Mac OS* X) or /Qvec- /Qsimd- (Windows*)

Example

Using #pragma simd.

In the example, the function add_floats() uses too many unknown pointers for the compiler's automatic runtime independence check optimization to kick-in. The programmer can enforce the vectorization of this loop by using #pragma simd and avoid the overhead of runtime check:

 void add_floats(float *a, float *b, float *c, float *d, float *e, int n){

  int i;

#pragma simd

  for (i=0; i<n; i++){

    a[i] = a[i] + b[i] + c[i] + d[i] + e[i];

  }

}