A Locality Optimizing Algorithm for Developing Stream Programs in Imagine

In this paper, we explore a novel locality optimizing algorithm for developing stream programs in Imagine to sustain high computational ability. Our specific contributions include that we formulate the relationship between streams and kernels as a Data&Computation Matrix (D&C Matrix), and present the key techniques for locality enhancement based on this matrix. The experimental results on five representative scientific applications show that our algorithm can effectively improve the computational intensiveness and avoid the utilization of index streams to achieve high locality in LRF and SRF.