The disparity between the processing speed and the data access rates presents a serious bottleneck in pipelined/vector processors. The memory bank conflict in interleaved system can be alleviated by skewing, for scientific computations performing functions on varieties of submatrices. So far uniskewing involving periodic and linear functions have been studied. Several difficulties encountered in such schemes are that they require a prime number of memory modules, may create wasted memory space, or addressing functions and the alignment network become complex. We present a new technique, termed multiskewing, which applies multiple functions on different sections of the array. Each of these functions may be as simple as a linear shift. We show that some of the advantages are that it does not require a prime number of memory, memory utilization factor is 100%, maintains the logical structure of the array, and allows optimal memory access of a large class of submatrices.