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SIMD.float32x4

This is an experimental technology, part of the Harmony (ECMAScript 7) proposal.
Because this technology's specification has not stabilized, check the compatibility table for usage in various browsers. Also note that the syntax and behavior of an experimental technology is subject to change in future version of browsers as the spec changes.

The SIMD.float32x4 data type is a 128-bit vector divided into 4 lanes storing single precision floating point values.

Figure 1: SIMD.float32x4 in a 128-bit SIMD register.

Syntax

SIMD.float32x4(x, y, z, w);

Parameters

The input values are specified in double precision floating and are converted to single precision floating point values before being stored.

x Optional: An double specifying the value of the first lane. Defaults to NaN.
y Optional: An double specifying the value of the second lane. Defaults to NaN.
z Optional: An double specifying the value of the third lane. Defaults to NaN.
w Optional: An double specifying the value of the fourth lane. Defaults to NaN.

Constructors

In addition to the simple constructors, the SIMD API provides the following constructor. Note that you can also convert from another SIMD data type to float32x4.

SIMD.float32x4.splat(): Creates an float32x4 with all lanes set to a given value.

Operations

To actually do something with SIMD types, SIMD operations are needed that work on SIMD data types.

Checking SIMD types

SIMD.float32x4.check(): Returns a new float32x4 if the parameter is a valid float32x4 data type. Throws a TypeError otherwise.

Accessing and mutating lanes

SIMD.float32x4.extractLane(): Returns the value of the given lane.
SIMD.float32x4.replaceLane(): Returns a new float32x4 with the given lane value replaced.

Loading from and storing into typed arrays

SIMD.float32x4.load(): Returns a new float32x4 with the lane values loaded from a typed array.
SIMD.float32x4.store(): Stores an float32x4 into a typed array.

Arithmetic operations

SIMD.float32x4.abs(): Returns a new float32x4 with the absolute lane values.
SIMD.float32x4.add(): Returns a new float32x4 with the lane values added (a + b).
SIMD.float32x4.div(): Returns a new float32x4 with the lane values divided (a / b).
SIMD.float32x4.mul(): Returns a new float32x4 with the lane values multiplied (a * b).
SIMD.float32x4.neg(): Returns a new float32x4 with the negated lane values.
SIMD.float32x4.reciprocalApproximation(): Returns a new float32x4 with an approximation of the reciprocal lane values.
SIMD.float32x4.reciprocalSqrtApproximation(): Returns a new float32x4 with an approximation of the reciprocal square root lane values.
SIMD.float32x4.sub(): Returns a new float32x4 with the lane values subtracted (a - b).
SIMD.float32x4.sqrt(): Returns a new float32x4 with the square root of the lane values.

Shuffling and swizzling

SIMD.float32x4.shuffle(): Returns a new float32x4 with the lane values shuffled.
SIMD.float32x4.swizzle(): Returns a new float32x4 with the lane values swizzled.

Min/max and clamping

SIMD.float32x4.clamp(): Returns a new float32x4 with the lane values clamped between a lower limit and an upper limit.
SIMD.float32x4.max(): Returns a new float32x4 with the maximum of the lane values.
SIMD.float32x4.maxNum(): Returns a new float32x4 with the maximum of the lane values, preferring numbers over NaN.
SIMD.float32x4.min(): Returns a new float32x4 with the minimum of the lane values.
SIMD.float32x4.minNum(): Returns a new float32x4 with the minimum of the lane values, preferring numbers over NaN.

Selections

SIMD.float32x4.select(): Returns a new float32x4 with the lane values being a mix of the lanes depending on the selector mask.
SIMD.float32x4.selectBits(): Returns a new float32x4 with the lane values being a mix of bits depending on the selector mask.

Comparisons

SIMD.float32x4.equal(): Returns a selection mask depending on a == b.
SIMD.float32x4.notEqual(): Returns a selection mask depending on a != b.
SIMD.float32x4.lessThan(): Returns a selection mask depending on a < b.
SIMD.float32x4.lessThanOrEqual(): Returns a selection mask depending on a <= b.
SIMD.float32x4.greaterThan(): Returns a selection mask depending on a > b.
SIMD.float32x4.greaterThanOrEqual(): Returns a selection mask depending on a >= b.

Bitwise logical operations

SIMD.float32x4.and(): Returns a new float32x4 with the logical AND of the lane values (a & b).
SIMD.float32x4.or(): Returns a new float32x4 with the logical OR of the lane values (a | b).
SIMD.float32x4.xor(): Returns a new float32x4 with the logical XOR of the lane values (a ^ b).
SIMD.float32x4.not(): Returns a new float32x4 with lane with the logical NOT of the lane values (~a).

Data conversions (packing / unpacking)

SIMD.float32x4.fromInt32x4(): Creates a new float32x4 data type with a float conversion from an int32x4.
SIMD.float32x4.fromInt32x4Bits(): Creates a new float32x4 data type with a bit-wise copy from an int32x4.
SIMD.float32x4.fromFloat64x2(): Creates a new float32x4 data type with a float conversion from a float64x2.
SIMD.float32x4.fromFloat64x2Bits(): Creates a new float32x4 data type with a bit-wise copy from a float64x2.
SIMD.float32x4.fromInt16x8Bits(): Creates a new float32x4 data type with a bit-wise copy from an int16x8.
SIMD.float32x4.fromInt8x16Bits(): Creates a new float32x4 data type with a bit-wise copy from an int8x16.

Examples

Constructing an float32x4

new SIMD.float32x4(1, 2, 3, 4); // float32x4[1, 2, 3, 4]
new SIMD.float32x4(1, 2);       // float32x4[1, 2, NaN, NaN]
new SIMD.float32x4();           // float32x4[NaN, NaN, NaN, NaN]

Specifications

SIMD is not yet part of an official standards document or draft. For standardization work and a Polyfill implementation based on typed arrays, see the ecmascript_simd GitHub repository.

Feature	Chrome	Firefox (Gecko)	Internet Explorer	Opera	Safari
Basic support	Not supported	Nightly build	Not supported	Not supported	Not supported

Feature	Android	Chrome for Android	Firefox Mobile (Gecko)	IE Mobile	Opera Mobile	Safari Mobile
Basic support	Not supported	Not supported	Nightly build	Not supported	Not supported	Not supported

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Contributors to this page: fscholz

Last updated by: fscholz, May 7, 2015 5:16:53 AM

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