  Generalised matrix-matrix multiplication forms the kernel of many
mathematical algorithms. A faster matrix-matrix multiply immediately benefits
these algorithms. In this paper we implement efficient matrix multiplication
for large matrices using the floating point Intel Pentium SIMD (Single
Instruction Multiple Data) architecture. A description of the issues and our
solution is presented, paying attention to all levels of the memory hierarchy.
Our results demonstrate an average performance of 2.09 times faster than the
leading public domain matrix-matrix multiply routines.

Performance;Machine Learning