intel-intrinsics 1.0.16

The most practical D SIMD solution! Using SIMD intrinsics with Intel syntax with D.


To use this package, run the following command in your project's root directory:

Manual usage
Put the following dependency into your project's dependences section:

intel-intrinsics

Travis Status

The practical D SIMD solution. Use Intel intrinsics in D code with a wide range of compilers.

This is a work in progress, please complain in the bugtracker.

Usage



import inteli.xmmintrin; // allows SSE1 intrinsics
import inteli.emmintrin; // allows SSE2 intrinsics

// distance between two points in 4D
float distance(float[4] a, float[4] b) nothrow @nogc
{
    __m128 va = _mm_loadu_ps(a.ptr);
    __m128 vb = _mm_loadu_ps(b.ptr);
    __m128 diffSquared = _mm_sub_ps(va, vb);
    diffSquared = _mm_mul_ps(diffSquared, diffSquared);
    __m128 sum = _mm_add_ps(diffSquared, _mm_srli_si128!8(diffSquared));
    sum = _mm_add_ps(sum, _mm_srli_si128!4(sum));
    return _mm_cvtss_f32(_mm_sqrt_ss(sum));
}
assert(distance([0, 2, 0, 0], [0, 0, 0, 0]) == 2);


Who is using it?

  • Pixel Perfect Engine is using intel-intrinsics for blitting images: https://github.com/ZILtoid1991/CPUblit/blob/master/src/CPUblit/composing.d
  • Dplug is using intel-intrinsics for biquad processing for a 10% speed gain over equivalent assembly: https://github.com/AuburnSounds/Dplug/blob/master/dsp/dplug/dsp/iir.d#L104

Why?

Familiar syntax

Why Intel intrinsic syntax? Because it is more familiar to C++ programmers and there is a convenient online guide provided by Intel: https://software.intel.com/sites/landingpage/IntrinsicsGuide/

Without this critical Intel documentation it's much more difficult to write SIMD code for x86.

Future-proof

intel-intrinsics is a set of stable SIMD intrinsic that the LDC team doesn't have the manpower to maintain.

LDC SIMD intrinsics are a moving target (https://github.com/ldc-developers/ldc/issues/2019), and you need a layer over it if you want to be safe.

Because those x86 intrinsics are internally converted to IR, they don't tie to a particular architecture. So you could target ARM one day and still get comparable speed-up.

Portability

Write the same SIMD code for both DMD and LDC.. This is intended to be the most practical SIMD solution for D. Including an emulation layer for DMD 32-bit which doesn't have any SIMD capability right now.

Supported instructions set

  • SSE1
  • SSE2

The lack of AVX intrinsics is explained by the lack of raw speed gain with these instruction sets.

Important difference

When using the LDC compatibility layer (ie. when not using LDC), every implicit conversion of similarly-sized vectors should be done with a cast instead.

__m128i b = _mm_set1_epi32(42);
__m128 a = b;             // NO, only works in LDC
__m128 a = cast(__m128)b; // YES, works in all D compilers

This is because D does not allow implicit conversions, except magically in the compiler for real vector types.

Dependencies:
none
Versions:
1.11.18 2024-Jan-03
1.11.17 2023-Dec-17
1.11.16 2023-Dec-03
1.11.15 2023-Aug-27
1.11.14 2023-Aug-27
Show all 108 versions
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