A Scalable Design Approach to Efficiently Map Applications on CGRAs

Abstract

Coarse-Grained Reconfigurable Architectures (CGRAs) are promising high-performance and power-efficient platforms. However, their uses are still limited because of the current capability of the mapping tools. This paper presents a new scalable efficient design flow to map applications written in high level language on CGRAs. This approach leverages on simultaneous scheduling and binding steps respectively based on a heuristic and an exact method stochastically degenerated. The formal graph model of the application, obtained after compilation, is backward traversed and dynamically transformed when needed to allow for a better exploration of the design space. Results show that our approach is scalable, finds most of the time the best solutions i.e. the mappings with the shortest latencies, achieves lowest failure rate in carrying out solutions, provides lower computation time and explores more efficiently the solution space than the state of the art methods.