Intel® AVX

This paper describes a case study in which AVX instructions are used to enhance the performance of a de-saturation algorithm (a common video filter). The case study takes the algorithm from a non-SIMD state to AVX based SIMD.

Wiener filtering (also known as Least Mean Square filtering) is a technique for removing unwanted noise from an image. This article discusses Wiener filtering, and includes an example of code that has been optimized using Intel® AVX

Intel® Advanced Vector Extensions (Intel® AVX) is a set of instructions for doing SIMD operations on Intel® architecture CPUs. These instructions extend previous SIMD offerings (MMX™ and Intel® SSE). This paper provides an AVX instruction set overview.

The introduction of the 2nd generation Intel® Core™ processor includes Intel® Advanced Vector Extension (Intel® AVX). Intel AVX is a new 256-bit instruction set extension to Intel® SSE. This article describes a simple methodology to utilize Intel AVX.

This article helps developers ensure their C/C++ code with intrinsics produces the optimal assembly and shows how to spot unnecessary register spilling.

This white paper describes a code sample that uses Intel® AVX for computing mesh-based cloth simulation. A structure of arrays (SOA) implementation is used to maximize data parallelism enabling usage of 256-bit (8 float) SIMD processing. Code is provided.

This article shows how to use 256-bit Intel® Advanced Vector Extensions (Intel® AVX) to normalize an array of 3D vectors. We describe a shuffle approach to convert between AOS & SOA on-the-fly in order to make data ready for up to 8-wide SIMD processing.

This C/C++ header file can be used for AVX emulation on Intel CPUs/processors without h/w AVX support

Introduction Intel® Advanced Vector Extensions (Intel® AVX) extends the capabilities of Intel® Streaming SIMD Extensions (Intel® SSE), especially for floating point data and operations. Intel® AVX ess ...