Loop blocking is a combination of strip mining and loop interchange to enhance reuse of local data. It helps the nested loops that manipulate arrays and are too large to fit into the cache. The loop blocking allows reuse of the arrays by transforming the

Explains which Intel Compiler switches to use to target and optimize for a specific platform, cpu or processor.

Description of the various ways you can use Intel® C++ Compilers to enable your applications for multi-core and many-core.

The compiler supports many options that tune or optimize an application for different Intel and non-Intel processors. Differences are explained, and the switches /arch, /Qx..., /Qax... (Windows*) and -m, -x..., -ax... (Linux*, Mac OS* X) are recommended.

Loops with function calls as bounds (such as STL end() calls) may not be compiled into parallel even if OpenMP APIs are explicitly used.

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.

It lists the information where to find the threaded Intel IPP from each release.