PARALLEL ALGORITHM FOR MULTI-DIMENSIONAL MATRIX MULTIPLICATION Research Paper

PARALLEL ALGORITHM FOR MULTI-DIMENSIONAL MATRIX times OPERATIONS REPRESENTATION USING KARNAUGH MAP - Research Paper ExampleThe basic concept EKMR is to transmogrify the multi-dimensional line up in to a set of two-dimensional arrays. EKMR scheme implies Karnaugh Map which is a technique utilize to reduce a Boolean expression. It is commonly represented with the help of a rectangular map which holds every last(predicate) the possible values of the Boolean expression. Then the efficient data parallel algorithms for multi-dimensional matrix multiplication surgery using EKMR are presented in this study which outperformed those data parallel algorithms for multi-dimensional matrix multiplication operation which utilize the TMR scheme. The study encourages designing data parallel algorithms for multi-dimensional dense and sparse multi-dimensional arrays for other operations as puff up using the EKMR scheme since this scheme produces the efficient performance for all dimensions and for all operations of the arrays.Multi-dimensional arrays which are besides referred as tensors or n-ways arrays are usefully applied to a wide range of studies or methods such as climate modeling, finite element analysis (FEA), molecular dynamic and many more unless still many issues have been encountered regarding efficient operations of these multi-dimensional arrays. Most of the proposed methods are successful in movement of two-dimensional arrays which do not show accurate results when applied to the extended form of tensors. This occurred due to the traditional matrix representation (TMR) which is an array representation scheme that is commonly used to represent the multi-dimensional dense or sparse array. Dense and sparse are the two categories of the array form which are provided through the several(a) data parallel programming languages 2 for instance, Vienna Fortran, High Performance Fortran, etc. If all or intimately of the array elements are non-zero values then it is called a dense array. On the other hand, if most of the elements of the array are zero then it is called a sparse array. When an operation is applied