Publication

Abstract : The high integration density in today's VLSI chips offers enormous computing power to be utilized by the design of parallel computing hardware. The implementation of computationally intensive algorithms represented by n-dimensional (n-D) nested loop algorithms, onto parallel array architecture is termed as mapping. The methodologies adopted for mapping these algorithms onto parallel hardware often use heuristic search that requires a lot of computational effort to obtain near optimal solutions. We propose a new mapping procedure wherein a lower dimensional subspace (of the n-D problem space) of inner loop is identified, in which lies the computational expression that generates the output or outputs of the n-D problem. The processing elements (PE array) are assigned to the identified sub-space and the reuse of the PE array is through the assignment of the PE array to the successive sub-spaces in consecutive clock cycles/periods (CPs) to complete the computational tasks of the n-D problem. The above is used to develop our proposed modified heuristic search to arrive at optimal design and the complexity comparisons are given. The MATLAB results of the new search and the design space trade-off analysis using the high-level synthesis tool are presented for two typical computationally intensive nested loop algorithms--the 6D FSBM and the 4D edge detection alternatively known as the 2D filtering algorithm.