The unsigned to double casting in the Intel C++ compiler 11.1 to produces correct result when vectoring. The compiler version 11.0 produces wrong result.
This white paper proposes an implementation for the Infinite Impulse Response (IIR) Gaussian blur filter using Intel® Advanced Vector Extensions (Intel® AVX) instructions. For a 2048x2048 image size, the AVX implementation is ~2X faster than the SSE code.
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.
The Intel® SDK for OpenCL* Applications features an implicit vectorization module which boosts application performance. The implicit vectorization module uses state-of-the-art vectorization algorithms based on up-to-date compiler research
This presentation is for C, C++, and Fortran developers, and will help you get started understanding and evaluating vectorization using new technologies such as Intel® Cilk Plus, pragma SIMD and the Intel Compiler’s Guided Auto Parallelization report.
Intel Vectorization Toolkit: 4. Get Advice Using the Intel Compiler GAP Report and Toolkit ResourcesIntel Vectorization Toolkit: 4. Get Advice Using the Intel Compiler GAP Report and Toolkit Resources
Intel Vectorization Toolkit :5. Implement GAP Advice, Other Suggestions (such as pragma simd and/or array notations)
Intel Vectorization Toolkit: 2. Determine Hotspots Using Intel® VTune™ Amplifier XE