simd

AVX segmentation fault on linux [closed]

由 假装没事ソ 提交于 2020-12-25 04:15:17
问题 Closed. This question needs debugging details. It is not currently accepting answers. Want to improve this question? Update the question so it's on-topic for Stack Overflow. Closed 5 years ago . Improve this question I am trying to run this code and it says segmentation fault when I run it. It compiles good. Here is the code. (It works fine on windows). #include<iostream> #include<vector> #include<immintrin.h> const int size = 1000000; std::vector<float>A(size); std::vector<float>B(size); std

Fastest way to horizontally sum SSE unsigned byte vector

由 牧云@^-^@ 提交于 2020-12-23 02:33:19
问题 I need to horizontally add a __m128i that is 16 x epi8 values. The XOP instructions would make this trivial, but I don't have those available. Current method is: hd = _mm_hadd_epi16(_mm_cvtepi8_epi16(sum), _mm_cvtepi8_epi16(_mm_shuffle_epi8(sum, swap))); hd = _mm_hadd_epi16(hd, hd); hd = _mm_hadd_epi16(hd, hd); Is there a better way with up to SSE4.1? 回答1: You can do it with SSE2's _mm_sad_epu8 (psadbw), e.g.: inline uint32_t _mm_sum_epu8(const __m128i v) { __m128i vsum = _mm_sad_epu8(v, _mm

what's the purpose of using media registers that can hold 32 bytes [duplicate]

由 三世轮回 提交于 2020-12-13 04:55:33
问题 This question already has answers here : What is the difference between non-packed and packed instruction in the context of SIMD-operations? (2 answers) What is the benefit of SIMD on a superscalar out-of-order CPU? (1 answer) What are some rules of thumb for when SIMD would be faster? (SSE2, AVX) [closed] (1 answer) Why floating point registers are different than general purpose ones (1 answer) Is there any architecture that uses the same register space for scalar integer and floating point

System.Numerics.Vector<T> Initialization Performance on .NET Framework

由 不羁岁月 提交于 2020-12-13 03:16:49
问题 System.Numerics.Vector brings SIMD support to .NET Core and .NET Framework. It works on .NET Framework 4.6+ and .NET Core. // Baseline public void SimpleSumArray() { for (int i = 0; i < left.Length; i++) results[i] = left[i] + right[i]; } // Using Vector<T> for SIMD support public void SimpleSumVectors() { int ceiling = left.Length / floatSlots * floatSlots; for (int i = 0; i < ceiling; i += floatSlots) { Vector<float> v1 = new Vector<float>(left, i); Vector<float> v2 = new Vector<float>

What is the most efficient way to support CMGT with 64bit signed comparisons on ARMv7a with Neon?

由 对着背影说爱祢 提交于 2020-12-12 05:39:34
问题 This question was originally posed for SSE2 here. Since every single algorithm overlapped with ARMv7a+NEON's support for the same operations, the question was updated to include the ARMv7+NEON versions. At the request of a commenter, this question is asked here to show that it is indeed a separate topic and to provide alternative solutions that might be more practical for ARMv7+NEON. The net purpose of these questions is to find ideal implementations for consideration into WebAssembly SIMD.

Does SSE/AVX provide a means of determining if a result was rounded up?

由 ≡放荡痞女 提交于 2020-12-09 12:20:55
问题 One of the purposes of the C1 bit in the x87 FPU status word is to show whether or not an inexact result was rounded up. Does SSE/AVX provide any such indication for scalar operations? I did not see a similar bit in the MXCSR register. Am I forced to use x87 instructions if I want this information? 回答1: SSE/AVX do not provide hardware support for detecting this, even for scalar instructions like addss . SSE was designed for SIMD, with 4 floats per XMM vector, and presumably Intel didn't want

YUV转RGB（NV21-ARGB）的Neon优化代码

由 柔情痞子 提交于 2020-11-27 02:42:24
说明 此代码仅限于 NV21 格式转 ARGB 格式。 NV21 格式中，Y 单独存储，UV分量交错存储。 使用如下公式： R = Y + 1.402*(V-128); G = Y - 0.34414*(U-128) - 0.71414*(V-128); B = Y + 1.772*(U-128); 浮点乘法用 6位精度处理（即a*b = ((a << 6)*b )>>6） 代码 #ifdef HAS_NEON #include <arm_neon.h> #endif void convertToRGBA( unsigned char * yuv, int w, int h, int * rgba) { for ( int i= 0 ; i<h; ++i) { unsigned char * dst = ( unsigned char *)(rgba + w*i); unsigned char * y = yuv + w*i; unsigned char * uv = yuv + w*h + w*(i/ 2 ); int count = w; #ifdef HAS_NEON /*一次处理16个像素*/ int c = count/ 16 ; asm volatile ( "mov r4, %[c]\t\n" "beq 2f\t\n" "vmov.u8 d7, #255\t\n" /
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