A Data Prefetch and Reuse Strategy for Coarse-Grained Reconfigurable Architectures

Abstract

The Coarse Grained Reconfigurable Architectures (CGRAs) are proposed as new choices for enhancing the ability of parallel processing. Data transfer throughput between Reconfigurable Cell Array (RCA) and on-chip local memory is usually the main performance bottleneck of CGRAs. In order to release this stress, we propose a novel data transfer strategy that is called Heuristic Data Prefetch and Reuse (HDPR), for the first time in the case of explicit CGRAs. The HDPR strategy provides not only the flexible data access schedule but also the high data throughput needed to realize fast pipelined implementations of various loop kernels. To improve the data utilization efficiency, a dual-bank cache-like data reuse structure is proposed. Furthermore, a heuristic data prefetch is also introduced to decrease the data access latency. Experimental results demonstrate that when compared with conventional explicit data transfer strategies, our work achieves a significant speedup improvement of, on average, 1.73 times at the expense of only 5.86% increase in area.