Tips and techniques on using the Intel® Compilers to maximize your application performance.
Information about Intel® Integrated Performance Primitives (Intel® IPP) memory functions
The purpose of this document is to help developers determine which FFT, Intel® MKL or Intel® IPP is best suited for their application.
How to configure OpenMP in the Intel IPP library to maximize multi-threaded performance of the Intel IPP primitives.
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)
compiler reports "unable to do dynamic initialization" when compiling code that use the GNU* vector_size attribute.
Examples of vectorizing Fortran applications
Vectorization Essentials: Vectorizing the outer loop can be profitable
Vectorization Essentials: Efficient vectorization involves making full use of the vector-hardware in the kernel-vector loop.