avx | 易学教程

inlining failed in call to always_inline '__m256d _mm256_broadcast_sd(const double*)'

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问题 I'm trying to run a Visual Studio cpp project created by a friend of mine. I'm trying to run the file without VS. But I'm getting a list of errors, all in the same format: inlining failed in call to always_inline '__m256d _mm256_broadcast_sd(const double*)': target specific option mismatch| It runs correctly in VS with release mode and breaks when run in debug mode. The include s are as follows: #include "stdafx.h" #include <iostream> #include <stdio.h> #include <stdlib.h> #include <time.h>

AVX inside a VirtualBox VM?

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问题 I install the latest Ubuntu 14.04 amd64(gcc 4.8.2) in virtualbox, run cat /proc/cpuinfo, get result: The processor CORE i52520M does support AVX instructions. I used Ubuntu 12.04 amd64(gcc 4.6), and it supports AVX via /proc/cpuinfo. How can I use the AVX in my software in virtualbox? 回答1: VirtualBox 5.0 beta 3 now supports AVX and AVX2 (which I can confirm from testing). 来源： https://stackoverflow.com/questions/24543874/avx-inside-a-virtualbox-vm

SIMD math libraries for SSE and AVX

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I am looking for SIMD math libraries (preferably open source) for SSE and AVX. I mean for example if I have a AVX register v with 8 float values I want sin(v) to return the sin of all eight values at once. AMD has a propreitery library, LibM http://developer.amd.com/tools/cpu-development/libm/ which has some SIMD math functions but LibM only uses AVX if it detects FMA4 which Intel CPUs don't have. Also I'm not sure it fully uses AVX as all the function names end in s4 (d2) and not s8 (d4). It give better performance than the standard math libraries on Intel CPUs but it's not much better. Intel

Difference between the AVX instructions vxorpd and vpxor

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问题 According to the Intel Intrinsics Guide, vxorpd ymm, ymm, ymm : Compute the bitwise XOR of packed double-precision (64-bit) floating-point elements in a and b, and store the results in dst. vpxor ymm, ymm, ymm : Compute the bitwise XOR of 256 bits (representing integer data) in a and b, and store the result in dst. What is the difference between the two? It appears to me that both instructions would do a bitwise XOR on all 256 bits of the ymm registers. Is there any performance penalty if I

How are the gather instructions in AVX2 implemented?

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Suppose I'm using AVX2's VGATHERDPS - this should load 8 single-precision floats using 8 DWORD indices. What happens when the data to be loaded exists in different cache-lines? Is the instruction implemented as a hardware loop which fetches cache-lines one by one? Or, can it issue a load to multiple cache-lines at once? I read a couple of papers which state the former (and that's the one which makes more sense to me), but I would like to know a bit more about this. Link to one paper: http://arxiv.org/pdf/1401.7494.pdf I did some benchmarking of the AVX gather instructions and it seems to be a

SSE-copy, AVX-copy and std::copy performance

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I'm tried to improve performance of copy operation via SSE and AVX: #include <immintrin.h> const int sz = 1024; float *mas = (float *)_mm_malloc(sz*sizeof(float), 16); float *tar = (float *)_mm_malloc(sz*sizeof(float), 16); float a=0; std::generate(mas, mas+sz, [&](){return ++a;}); const int nn = 1000;//Number of iteration in tester loops std::chrono::time_point<std::chrono::system_clock> start1, end1, start2, end2, start3, end3; //std::copy testing start1 = std::chrono::system_clock::now(); for(int i=0; i<nn; ++i) std::copy(mas, mas+sz, tar); end1 = std::chrono::system_clock::now(); float

Intel c++ compiler, ICC, seems to ingnore SSE/AVX seetings

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问题 I have recently downloaded and installed the Intel C++ compiler, Composer XE 2013, for Linux which is free to use for non-commercial development. http://software.intel.com/en-us/non-commercial-software-development I'm running on a ivy bridge system (which has AVX). I have two versions of a function which do the same thing. One does not use SSE/AVX. The other version uses AVX. In GCC the AVX code is about four times faster than the scalar code. However, with the Intel C++ compiler the

Is _mm_broadcast_ss faster than _mm_set1_ps?

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问题 Is this code float a = ...; __m256 b = _mm_broadcast_ss(&a) always faster than this code float a = ...; _mm_set1_ps(a) ? What if a defined as static const float a = ... rather than float a = ... ? 回答1: mm_broadcast_ss is likely to be faster than mm_set1_ps. The former translates into a single instruction (VBROADCASTSS), while the latter is emulated using multiple instructions (probably a MOVSS followed by a shuffle). However, mm_broadcast_ss requires the AVX instruction set, while only SSE is

Why do SSE instructions preserve the upper 128-bit of the YMM registers?

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问题 It seems to be a recurring problem that many Intel processors (up until Skylake, unless I'm wrong) exhibit poor performance when mixing AVX-256 instructions with SSE instructions. According to Intel's documentation, this is caused by SSE instructions being defined to preserve the upper 128 bits of the YMM registers, so in order to be able to save power by not using the upper 128 bits of the AVX datapaths, the CPU stores those bits away when executing SSE code and reloads them when entering

Code alignment in one object file is affecting the performance of a function in another object file

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I'm familiar with data alignment and performance but I'm rather new to aligning code. I started programming in x86-64 assembly recently with NASM and have been comparing performance using code alignment. As far as I can tell NASM inserts nop instructions to achieve code alignment. Here is a function I have been trying this on a Ivy Bridge system void triad(float *x, float *y, float *z, int n, int repeat) { float k = 3.14159f; int(int r=0; r<repeat; r++) { for(int i=0; i<n; i++) { z[i] = x[i] + k*y[i]; } } } The assembly I'm using for this is below. If I don't specify the alignment my