simd

Choice between aligned vs. unaligned x86 SIMD instructions

由 早过忘川 提交于 2019-12-10 03:29:07
问题 There are generally two types of SIMD instructions: A. Ones that work with aligned memory addresses, that will raise general-protection (#GP) exception if the address is not aligned on the operand size boundary: movaps xmm0, xmmword ptr [rax] vmovaps ymm0, ymmword ptr [rax] vmovaps zmm0, zmmword ptr [rax] B. And the ones that work with unaligned memory addresses, that will not raise such exception: movups xmm0, xmmword ptr [rax] vmovups ymm0, ymmword ptr [rax] vmovups zmm0, zmmword ptr [rax]

Coding on insufficient hardware

由 旧时模样 提交于 2019-12-10 00:33:10
问题 I am currently coding with SIMD instructions in C++ and trying to use an IDE which shows errors, spelling mistakes, etc whilst coding in real-time. The Problem is, that i am using AVX512 Instructions, which are not supported by my hardware, only the server i use for compiling. Is there a way to code in an IDE with errorchecking, etc without the interference of the AVX512-functions hindering the compiler? 回答1: First of all, you don't need your desktop to support AVX512 to edit source and

SIMD (SSE) instruction for division in GCC

由 痴心易碎 提交于 2019-12-09 18:27:45
问题 I'd like to optimize the following snippet using SSE instructions if possible: /* * the data structure */ typedef struct v3d v3d; struct v3d { double x; double y; double z; } tmp = { 1.0, 2.0, 3.0 }; /* * the part that should be "optimized" */ tmp.x /= 4.0; tmp.y /= 4.0; tmp.z /= 4.0; Is this possible at all? 回答1: I've used SIMD extension under windows, but have not yet under linux. That being said you should be able to take advantage of the DIVPS SSE operation which will divide a 4 float

SSE multiplication 16 x uint8_t

由 帅比萌擦擦* 提交于 2019-12-09 04:55:09
问题 I want to multiply with SSE4 a __m128i object with 16 unsigned 8 bit integers, but I could only find an intrinsic for multiplying 16 bit integers. Is there nothing such as _mm_mult_epi8 ? 回答1: There is no 8-bit multiplication in MMX/SSE/AVX. However, you can emulate 8-bit multiplication intrinsic using 16-bit multiplication as follows: inline __m128i _mm_mullo_epi8(__m128i a, __m128i b) { __m128i zero = _mm_setzero_si128(); __m128i Alo = _mm_cvtepu8_epi16(a); __m128i Ahi = _mm_unpackhi_epi8(a

Storing two x86 32 bit registers into 128 bit xmm register

由 拟墨画扇 提交于 2019-12-08 23:13:20
问题 Is there any faster method to store two x86 32 bit registers in one 128 bit xmm register? movd xmm0, edx movd xmm1, eax pshufd xmm0, xmm0, $1 por xmm0, xmm1 So if EAX is 0x12345678 and EDX is 0x87654321 the result in xmm0 must be 0x8765432112345678. Thanks 回答1: With SSE 4.1 you can use movd xmm0, eax / pinsrd xmm0, edx, 1 and do it in 2 instructions. For older CPUs you can use 2 x movd and then punpckldq for a total of 3 instructions: movd xmm0, edx movd xmm1, eax punpckldq xmm0, xmm1 回答2: I

How to count character occurrences using SIMD

由 爷，独闯天下 提交于 2019-12-08 22:36:54
问题 I am given a array of lowercase characters (up to 1.5Gb) and a character c. And I want to find how many occurrences are of the character c using AVX instructions. unsigned long long char_count_AVX2(char * vector, int size, char c){ unsigned long long sum =0; int i, j; const int con=3; __m256i ans[con]; for(i=0; i<con; i++) ans[i]=_mm256_setzero_si256(); __m256i Zer=_mm256_setzero_si256(); __m256i C=_mm256_set1_epi8(c); __m256i Assos=_mm256_set1_epi8(0x01); __m256i FF=_mm256_set1_epi8(0xFF); _

Why are SIMD instructions not used in kernel?

由 好久不见. 提交于 2019-12-08 20:38:35
问题 I couldn't find much use of SIMD instructions (like SSE/AVX) in kernel (except one place where they were used to speedup parity computation of RAID6). Q1) Any specific reason for this or just the lack of use-case? Q2) What needs to be done today if I want to use SIMD instruction, in say a device driver? Q3) How hard will it be to incorporate framework like ISPC into kernel (just for experimentation)? 回答1: Saving/restoring FPU (including SIMD vector registers) state is more expensive than just

Optimizing SIMD histogram calculation

由 被刻印的时光 ゝ 提交于 2019-12-08 16:03:34
I worked on a code that implements an histogram calculation given an opencv struct IplImage * and a buffer unsigned int * to the histogram. I'm still new to SIMD so I might not be taking advantage of the full potential the instruction set provides. histogramASM: xor rdx, rdx xor rax, rax mov eax, dword [imgPtr + imgWidthOffset] mov edx, dword [imgPtr + imgHeightOffset] mul rdx mov rdx, rax ; rdx = Image Size mov r10, qword [imgPtr + imgDataOffset] ; r10 = ImgData NextPacket: mov rax, rdx movdqu xmm0, [r10 + rax - 16] mov rcx,16 ; 16 pixels/paq PacketLoop: pextrb rbx, xmm0, 0 ; saving the pixel

Is there a good double-precision small matrix SIMD library for x86?

由 我的未来我决定 提交于 2019-12-08 15:48:43
问题 I'm looking for a SIMD library focused small (4x4) matrix operations for graphics. There's lots of single precision ones out there, but I need to support both single and double precision. I've looked at Intel's IPP MX library, but I'd prefer something with source. I'm very interested in SSE3+ implementations of these particular operations: Mat4 * Mat4 Mat4 * Vec4 Mat4 * Array of Mat4 Mat4 * Array of Vec4 Mat4 inversion (nice to have) EDIT: No "premature optimization" answers please. Anyone

System.Numerics.Vectors 'Vector<T>': is it basically just System.UInt128?

由 99封情书 提交于 2019-12-08 07:51:12
问题 I'm looking into Vector<T> in the System.Numerics.Vectors namespace from version 4.5.0-preview1-26216-02. MSDN documentation says: Vector<T> is an immutable structure that represents a single vector of a specified numeric type. The count of a Vector<T> instance is fixed , but its upper limit is CPU-register dependent. https://docs.microsoft.com/en-us/dotnet/api/system.numerics.vector-1 (emphasis added) Even overlooking the misguided wording " count [sic.] of a Vector ", this sentence seems
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