Title :
Optimizing Spatial Mapping of Nested Loop for Coarse-Grained Reconfigurable Architectures
Author :
Dajiang Liu ; Shouyi Yin ; Yu Peng ; Leibo Liu ; Shaojun Wei
Author_Institution :
Inst. of Microelectron., Tsinghua Univ., Beijing, China
Abstract :
Coarse-grained reconfigurable architectures (CGRAs) have drawn increasing attention due to their flexibility and efficiency. Loops in applications are often mapped onto CGRAs for acceleration, and the mapping of loops onto CGRA is quite a challenging work due to the parallel execution paradigm and constrained hardware resource. To map loops onto CGRAs efficiently, it is important to transform loops into pieces that obey hardware resource constraints with less overhead (e.g., communication and configuration overhead). In this paper, we tackle this problem by establishing a performance optimization problem, including loop transformation and back- end placing and routing. A novel searching strategy is also designed to find the optimal result efficiently. Finally, we built a complete flow of mapping loop nests onto CGRA. Experiment results on most kernels of the Polybench show that our proposed approach can improve the performance of the kernels by 42% on average, as compared with the state-of-the-art methods. The runtime complexity of our approach is also acceptable.
Keywords :
computational complexity; reconfigurable architectures; CGRA; Polybench; back-end placing; back-end routing; coarse-grained reconfigurable architectures; constrained hardware resource; hardware resource constraints; loop nest mapping; loop transformation; nested loop spatial mapping; parallel execution paradigm; performance optimization problem; runtime complexity; Arrays; Context; Hardware; Optimization; Power demand; Vectors; Affine transformation; coarse-grained reconfigurable architecture (CGRA); loop nests; polyhedral model; polyhedral model.;
Journal_Title :
Very Large Scale Integration (VLSI) Systems, IEEE Transactions on
DOI :
10.1109/TVLSI.2014.2371854