I recently had a question from a customer who had introduced a succesful optimization to a hot function in his application, but did not see as much improvement in the overall application as he expe
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 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.
A toolkit that gives 6 Steps to Increase Performance Through Vectorization in Your Application
Intel Vectorization Toolkit: 3. Vectorization report for loop candidates
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)
Which applications are most likely to benefit from recompilation for Intel® Advanced Vector Extensions (Intel® AVX)?Applications containing vectorizable, floating-point loops or calls to performance libraries are the most likely to see significant performance gains from rebuilding for the Intel® Advanced Vector Extensions (Intel® AVX)
A tutorial on how to use #pragma simd and SIMD-enabled function features in Intel® Cilk™ Plus.
A simple introduction on how use Array Notations feature in Intel® Cilk™ Plus.