The Intel® Math Kernel Library has been optimized by exploiting both processor and system features and capabilities. Special care has been given to those routines that most profit from cache-management techniques. These especially include matrix-matrix operation routines such as dgemm().
In addition, code optimization techniques have been applied to minimize dependencies of scheduling integer and floating-point units on the results within the processor.
The major optimization techniques used throughout the library include:
Loop unrolling to minimize loop management costs
Blocking of data to improve data reuse opportunities
Copying to reduce chances of data eviction from cache
Data prefetching to help hide memory latency
Multiple simultaneous operations (for example, dot products in dgemm) to eliminate stalls due to arithmetic unit pipelines
Use of hardware features such as the SIMD arithmetic units, where appropriate
These are techniques from which the arithmetic code benefits the most.
Intel's compilers may or may not optimize to the same degree for non-Intel microprocessors for optimizations that are not unique to Intel microprocessors. These optimizations include SSE2, SSE3, and SSSE3 instruction sets and other optimizations. Intel does not guarantee the availability, functionality, or effectiveness of any optimization on microprocessors not manufactured by Intel. Microprocessor-dependent optimizations in this product are intended for use with Intel microprocessors. Certain optimizations not specific to Intel microarchitecture are reserved for Intel microprocessors. Please refer to the applicable product User and Reference Guides for more information regarding the specific instruction sets covered by this notice.
Notice revision #20110804