中文摘要：

粗粒度可重构体系结构为数据密集型应用提供了灵活性和高效的解决方法，而应用中的核心循环消耗了程序的大量执行时间，满足核心循环在CGRAs上实现的性能／开销的严格约束仍旧是个重大难题．针对已有工作在研究映射核心循环到CGRAs上的不足，文中提出一种新颖的核心循环自动流水映射到粗粒度可重构体系结构上的方法．文中形式化了核心循环到CGRAs的流水映射问题，阐述了CGRAs的资源共享和流水方法，定义了其循环自流水CGRAs体系结构模板，并给出核心循环流水映射方法．实验结果表明，与已有的先进的方法相比，文中方法的资源占用率降低16．3％、吞吐量提高169．1％．

英文摘要：

Coarse-grained reconfigurable architectures provide flexible and efficient solution for data-intensive applications. Loop kernels of these applications always consume much execution time of the whole program. However, mapping loop kernels onto CGRAs is still hard for meeting performance/cost constraints. This paper proposes a novel approach for mapping loop kernels on- to CGRAs with loop self-pipelining to solve the existing problems. The problem formulation is shown first. Then the resource sharing and pipelining of lspCGRAs are presented, together with its template standard. A field specific application driven mapping flow is described. Besides, a loop kernel pipelining mapping algorithm is proposed. The conclusions show that the proposed approach gains less resource utilization by 16.3% times and more throughputs by 169.1% times than previous advanced SPKM.