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Mapping Multi-Level Loop Nests onto CGRAs Using Polyhedral Optimizations
Dajiang LIU Shouyi YIN Leibo LIU Shaojun WEI
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 2015/07/01
Online ISSN: 1745-1337
Type of Manuscript: Special Section PAPER (Special Section on Design Methodologies for System on a Chip)
coarse-grained reconfigurable architecture, loops, polyhedral model, mapping,
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The coarse-grained reconfigurable architecture (CGRA) is a promising computing platform that provides both high performance and high power-efficiency. The computation-intensive portions of an application (e.g. loop nests) are often mapped onto CGRA for acceleration. However, mapping loop nests onto CGRA efficiently is quite a challenge due to the special characteristics of CGRA. To optimize the mapping of loop nests onto CGRA, this paper makes three contributions: i) Establishing a precise performance model of mapping loop nests onto CGRA, ii) Formulating the loop nests mapping as a nonlinear optimization problem based on polyhedral model, iii) Extracting an efficient heuristic algorithm and building a complete flow of mapping loop nests onto CGRA (PolyMAP). Experiment results on most kernels of the PolyBench and real-life applications show that our proposed approach can improve the performance of the kernels by 27% on average, as compared to the state-of-the-art methods. The runtime complexity of our approach is also acceptable.