Vector Extensions - D Programming Language
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# Vector Extensions

Contents

1. core.simd
   1. Properties
   2. Conversions
   3. Accessing Individual Vector Elements
   4. Conditional Compilation
2. X86 And X86_64 Vector Extension Implementation
   1. Vector Operation Intrinsics

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.

Implementation Defined: Which vector types are supported depends on the target. The implementation is expected to only support the vector types that are implemented in the target's hardware.
Best Practices: Use the declarations in core.simd instead of the language Vector grammar.

## core.simd

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

    import core.simd;

Implementation Defined:

These types and operations will be the ones defined for the architecture the compiler is targeting. If a particular CPU family has varying support for vector types, an additional runtime check may be necessary. The compiler does not emit runtime checks; those must be done by the programmer.

Depending on the architecture, compiler flags may be required to activate support for SIMD types.

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 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, it is supported ...
    else
        ... nope, use workaround ...

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

A typical workaround would be to use array vector 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

Implementation Defined:

The following describes the specific implementation of the vector types for the X86 and X86_64 architectures.

The vector extensions are currently implemented for the OS X 32 bit target, and all 64 bit targets.

core.simd defines the following types:

Vector Types
Type Name | Description | gcc Equivalent
--- | --- | ---
void16 | 16 bytes of untyped data | no equivalent
byte16 | 16 bytes | signed char __attribute__((vector_size(16)))
ubyte16 | 16 ubytes | unsigned char __attribute__((vector_size(16)))
short8 | 8 shorts | short __attribute__((vector_size(16)))
ushort8 | 8 ushorts | ushort __attribute__((vector_size(16)))
int4 | 4 ints | int __attribute__((vector_size(16)))
uint4 | 4 uints | unsigned __attribute__((vector_size(16)))
long2 | 2 longs | long __attribute__((vector_size(16)))
ulong2 | 2 ulongs | unsigned long __attribute__((vector_size(16)))
float4 | 4 floats | float __attribute__((vector_size(16)))
double2 | 2 doubles | double __attribute__((vector_size(16)))
void32 | 32 bytes of untyped data | no equivalent
byte32 | 32 bytes | signed char __attribute__((vector_size(32)))
ubyte32 | 32 ubytes | unsigned char __attribute__((vector_size(32)))
short16 | 16 shorts | short __attribute__((vector_size(32)))
ushort16 | 16 ushorts | ushort __attribute__((vector_size(32)))
int8 | 8 ints | int __attribute__((vector_size(32)))
uint8 | 8 uints | unsigned __attribute__((vector_size(32)))
long4 | 4 longs | long __attribute__((vector_size(32)))
ulong4 | 4 ulongs | unsigned long __attribute__((vector_size(32)))
float8 | 8 floats | float __attribute__((vector_size(32)))
double4 | 4 doubles | double __attribute__((vector_size(32)))

Note: for 32 bit gcc, it's long long instead of long.

Supported 128-bit Vector Operators
Operator | void16 | byte16 | ubyte16 | short8 | ushort8 | int4 | uint4 | long2 | ulong2 | float4 | double2
--- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | ---
= | × | × | × | × | × | × | × | × | × | × | ×
+ | – | × | × | × | × | × | × | × | × | × | ×
- | – | × | × | × | × | × | × | × | × | × | ×
* | – | – | – | × | × | – | – | – | – | × | ×
/ | – | – | – | – | – | – | – | – | – | × | ×
& | – | × | × | × | × | × | × | × | × | – | –
| | – | × | × | × | × | × | × | × | × | – | –
^ | – | × | × | × | × | × | × | × | × | – | –
+= | – | × | × | × | × | × | × | × | × | × | ×
-= | – | × | × | × | × | × | × | × | × | × | ×
*= | – | – | – | × | × | – | – | – | – | × | ×
/= | – | – | – | – | – | – | – | – | – | × | ×
&= | – | × | × | × | × | × | × | × | × | – | –
|= | – | × | × | × | × | × | × | × | × | – | –
^= | – | × | × | × | × | × | × | × | × | – | –
unary~ | – | × | × | × | × | × | × | × | × | – | –
unary+ | – | × | × | × | × | × | × | × | × | × | ×
unary- | – | × | × | × | × | × | × | × | × | × | ×

Supported 256-bit Vector Operators
Operator | void32 | byte32 | ubyte32 | short16 | ushort16 | int8 | uint8 | long4 | ulong4 | float8 | double4
--- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | ---
= | × | × | × | × | × | × | × | × | × | × | ×
+ | – | × | × | × | × | × | × | × | × | × | ×
- | – | × | × | × | × | × | × | × | × | × | ×
* | – | – | – | – | – | – | – | – | – | × | ×
/ | – | – | – | – | – | – | – | – | – | × | ×
& | – | × | × | × | × | × | × | × | × | – | –
| | – | × | × | × | × | × | × | × | × | – | –
^ | – | × | × | × | × | × | × | × | × | – | –
+= | – | × | × | × | × | × | × | × | × | × | ×
-= | – | × | × | × | × | × | × | × | × | × | ×
*= | – | – | – | – | – | – | – | – | – | × | ×
/= | – | – | – | – | – | – | – | – | – | × | ×
&= | – | × | × | × | × | × | × | × | × | – | –
|= | – | × | × | × | × | × | × | × | × | – | –
^= | – | × | × | × | × | × | × | × | × | – | –
unary~ | – | × | × | × | × | × | × | × | × | – | –
unary+ | – | × | × | × | × | × | × | × | × | × | ×
unary- | – | × | × | × | × | × | × | × | × | × | ×

Operators not listed are not supported at all.

### Vector Operation Intrinsics

See core.simd for the supported intrinsics.

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