Vec4D: SSE-ASM, SSE-INTRINSICS, NORMAL

Emil · 2016-08-12T12:59:55

I have played around with SSE. I am using VS2012, and I wanted to know what was the fastest way to calculate the length of a vector. The code looks very bad. float Magnitude() const { #if SSE && SSE_ASM float result; //Optimized magnitude calculation with SSE and Assembly __asm { MOV EAX, this //Move [this] to EAX. MOVAPS XMM2, [EAX] //Copy data EAX to XMM2 register MULPS XMM2, XMM2 //Square the XMM2 register. MOVAPS XMM1, XMM2 //Make a copy SHUFPS XMM2, XMM1, _MM_SHUFFLE(1, 0, 3, 2) //Shuffle so that we can add together the elements. ADDPS XMM2, XMM1 //Add the elements. MOVAPS XMM1, XMM2 //Make a copy SHUFPS XMM1, XMM1, _MM_SHUFFLE(0, 1, 0, 1) //Second addition of elements using shuffle ADDPS XMM2, XMM1 SQRTPS XMM2, XMM2 //Get the square root MOVSS [result], XMM2 //Store the result in the float. } return result; #elif SSE __m128 tmp = _mm_mul_ps(components, components); tmp = _mm_add_ps(_mm_shuffle_ps(tmp, tmp, _MM_SHUFFLE(1, 0, 3, 2)), tmp); tmp = _mm_sqrt_ps(_mm_add_ps(tmp, _mm_shuffle_ps(tmp, tmp, _MM_SHUFFLE(0, 1, 0, 1)))); float result; _mm_store_ss(&result, tmp); return result; #endif #if !SSE && !SSE_ASM return sqrtf(__x * __x + __y * __y + __z * __z + __w * __w); #endif } Guess what, the normal method was as fast as the SSE-Intrinsics, while my assembly code was acctually slower. So yeah, you can't beat the compiler :)

Coding Horrors Community

Started by tapped April 21, 2013 01:35 PM

10 comments, last by Geri 7 years, 8 months ago

Alessio1989

4,648

July 14, 2016 07:36 PM

Just to remeber: by default Visual Studio 2012 and successive versions enable SSE2 optimizations under x86-ia32 too. Not sure about previous versions..

"Recursion is the first step towards madness." - "Skegg?ld, Skálm?ld, Skildir ro Klofnir!"
Direct3D 12 quick reference: https://github.com/alessiot89/D3D12QuickRef/

Geri

407

August 12, 2016 12:59 PM

i dont suggest you to use SSE manually. i experimented it with a bit, i was able to do faster code after a bit of trying than the original on my computer. HOWEVER, after i tryed it on a different cpu, the sse code was far slower on different cpu. so its not really worth - you should do algorithmical optimizations instead.

Vec4D: SSE-ASM, SSE-INTRINSICS, NORMAL

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Vec4D: SSE-ASM, SSE-INTRINSICS, NORMAL

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