• Introduction
• Lexical
• Interpolation Expression Sequence
• Grammar
• Modules
• Declarations
• Types
• Properties
• Attributes
• Pragmas
• Expressions
• Statements
• Arrays
• Associative Arrays
• Structs and Unions
• Classes
• Interfaces
• Enums
• Type Qualifiers
• Functions
• Operator Overloading
• Templates
• Template Mixins
• Contract Programming
• Conditional Compilation
• Traits
• Error Handling
• Unit Tests
• Garbage Collection
• Floating Point
• D x86 Inline Assembler
• Embedded Documentation
• Interfacing to C
• Interfacing to C++
• Interfacing to Objective-C
• Portability Guide
• Named Character Entities
• Memory Safety
• Application Binary Interface
• Vector Extensions
• Better C
• ImportC
• Live Functions
• Windows Programming
• Glossary
• Legacy Code
• Editions

Vector Extensions

CPUs often support specialized vector types and vector operations (a.k.a. media instructions). Vector types are a fixed array of floating or integer types, and vector operations operate simultaneously on them.

Specialized Vector types provide access to them.

The VectorBaseType must be a Static Array. The VectorElementType is the unqualified element type of the static array. The dimension of the static array is the number of elements in the vector.

core.simd

Vector types and operations are introduced by importing core.simd:

import core.simd;

The types defined will all follow the naming convention:

typeNN

where type is the vector element type and NN is the number of those elements in the vector type. The type names will not be keywords.

Properties

Vector types have the property:

Vector Type Properties

Property	Description
.array	Returns static array representation

Vectors support the following properties based on the vector element type. The value produced is that of a vector of the same type with each element set to the value corresponding to the property value for the element type.

Integral Vector Type Properties

Property	Description
.min	minimum value
.max	maximum value

Floating Point Vector Type Properties

Property	Description
.epsilon	smallest increment to the value 1
.infinity	infinity value
.max	largest representable value that is not infinity
.min_normal	smallest representable value that is not 0
.nan	NaN value

Conversions

Vector types of the same size (number_of_elements * size_of_element) can be implicitly converted among each other, this is done as a reinterpret cast (a type paint). Vector types can be cast to their VectorBaseType.

Integers and floating point values can be implicitly converted to their vector equivalents:

int4 v = 7;
v = 3 + v;   // add 3 to each element in v

Accessing Individual Vector Elements

They cannot be accessed directly, but can be when converted to an array type:

int4 v;
(cast(int*)&v)[3] = 2;   // set 3rd element of the 4 int vector
(cast(int[4])v)[3] = 2;  // set 3rd element of the 4 int vector
v.array[3] = 2;          // set 3rd element of the 4 int vector
v.ptr[3] = 2;            // set 3rd element of the 4 int vector

Conditional Compilation

If vector extensions are implemented, the version identifier D_SIMD is set.

Whether a type exists or not can be tested at compile time with an IsExpression:

static if (is(typeNN))
    ... yes, it is supported ...
else
    ... nope, use workaround ...

Whether a particular operation on a type is supported can be tested at compile time with:

float4 a,b;
static if (__traits(compiles, a+b))
    ... yes, add is supported for float4 ...
else
    ... nope, use workaround ...

For runtime testing to see if certain vector instructions are available, see the functions in core.cpuid.

A typical workaround for unsupported vector operations would be to use array operations instead:

float4 a,b;
static if (__traits(compiles, a/b))
    c = a / b;
else
    c[] = a[] / b[];

X86 And X86_64 Vector Extension Implementation

Vector Operation Intrinsics

See core.simd for the supported intrinsics.