intel-intrinsics 1.1.1

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.

Usage



import inteli.xmmintrin; // allows SSE1 intrinsics in both DMD and LDC
import inteli.emmintrin; // allows SSE2 intrinsics in both DMD and LDC

// 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);
    
    // core.simd is publicly imported, or emulated if need be.
    // One can use arithmetic operators / indexing on SIMD types.
    __m128 diffSquared = va - vb;
    diffSquared = _mm_mul_ps(diffSquared, diffSquared);
    __m128 sum = _mm_add_ps(diffSquared, _mm_srli_ps!8(diffSquared));
    sum += _mm_srli_ps!4(sum); 

    return _mm_cvtss_f32(_mm_sqrt_ss(sum));
}
assert(distance([0, 2, 0, 0], [0, 0, 0, 0]) == 2);


Why?

Capabilities

Some instructions aren't accessible using core.simd and ldc.simd capabilities. For example: pmaddwd which is so important in digital video. In this case one need to generate the right IR, or use the right LLVM intrinsic call.

Familiar syntax

Intel intrinsic syntax 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 sizeable SIMD code.

In intel-intrinsics it is extended with indexing and arithmetic operators, for convenience.

Future-proof

intel-intrinsics is a set of stable SIMD intrinsic that the LDC team doesn't have the manpower to maintain. It is mimicked on the set of similar intrinsics in GCC, clang, ICC...

LDC SIMD intrinsics are actually a moving target (https://github.com/ldc-developers/ldc/issues/2019), and you need a layer over it if you want to be sure your code won't break. (The reason is that as things become expressible in IR only in LLVM, x86 builtins get removed).

Portability

Because the D code or LLVM IR is portable, one goal of intel-intrinsics is to be one day platform-independent. One could target ARM one day and still get comparable speed-up.

The long-term goal is:

Write the same SIMD code for LDC GDC and DMD. Support x86 well, and ARM eventually..

Supported instructions set

  • MMX
  • SSE1
  • SSE2

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 user-defined implicit conversions.

Who is using it?

  • Auburn Sounds products use intel-intrinsics extensively for speed-up and having same code for both DMD and LDC.
  • 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
  • Please get in touch to get on that list!
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
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