Tips and techniques on using the Intel® Compilers to maximize your application performance.
Vectorization is one of many optimizations that are enabled by default in the latest Intel compilers. In order to be vectorized, loops must obey certain conditions, listed below. Some additional ways to help the compiler to vectorize loops are described.
A toolkit that gives 6 Steps to Increase Performance Through Vectorization in Your Application
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.
compiler reports "unable to do dynamic initialization" when compiling code that use the GNU* vector_size attribute.
This is the AOBench example associated with the "Intel® Cilk™ Plus – The Simplest Path to Parallelism" how-to article. It shows an Ambient Occlusion algorithm implemented as serial loops, one us
Get tips for common vectorization functions, such as handling user-defined function calls inside vector loops.
This blog contains additional content for the article "Advanced Vectorization" from Parallel Universe #12: