An Efficient Data Reuse Strategy for Multi-Pattern Data Access

Memory partitioning has been widely adopted to increase the memory bandwidth. Data reuse is a hardware-efficient way to improve data access throughput by exploiting locality in memory access patterns. We found that for many applications in image and video processing, a global data reuse scheme can be shared by multiple patterns. In this paper, we propose an efficient data reuse strategy for multi-pattern data access. Firstly, a heuristic algorithm is proposed to extract the reuse information as well as find the non-reusable data elements of each pattern. Then the non-reusable elements are partitioned into several memory banks by an efficient memory partitioning algorithm. Moreover, the reuse information is utilized to generate the global data reuse logic shared by the multi-pattern. We design a novel algorithm to minimize the number of registers required by the data reuse logic. Experimental results show that compared with the state-of-the-art approach, our proposed method can reduce the number of required BRAMs by 62.2% on average, with the average reduction of 82.1% in SLICE, 87.1% in LUTs, 71.6% in Flip-Flops, 73.1% in DSP48Es, 83.8% in SRLs, 46.7% in storage overhead, 79.1% in dynamic power consumption, and 82.6% in execution time of memory partitioning. Besides, the performance is improved by 14.4%.