Monomorphism-based CGRA Mapping via Space and Time Decoupling
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866918228533444608 |
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| author | Tirelli, Cristian Otoni, Rodrigo Pozzi, Laura |
| author_facet | Tirelli, Cristian Otoni, Rodrigo Pozzi, Laura |
| contents | Coarse-Grain Reconfigurable Arrays (CGRAs) provide flexibility and energy efficiency in accelerating compute-intensive loops. Existing compilation techniques often struggle with scalability, unable to map code onto large CGRAs. To address this, we propose a novel approach to the mapping problem where the time and space dimensions are decoupled and explored separately. We leverage an SMT formulation to traverse the time dimension first, and then perform a monomorphism-based search to find a valid spatial solution. Experimental results show that our approach achieves the same mapping quality of state-of-the-art techniques while significantly reducing compilation time, with this reduction being particularly tangible when compiling for large CGRAs. We achieve approximately $10^5\times$ average compilation speedup for the benchmarks evaluated on a $20\times 20$ CGRA. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_02859 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Monomorphism-based CGRA Mapping via Space and Time Decoupling Tirelli, Cristian Otoni, Rodrigo Pozzi, Laura Hardware Architecture Coarse-Grain Reconfigurable Arrays (CGRAs) provide flexibility and energy efficiency in accelerating compute-intensive loops. Existing compilation techniques often struggle with scalability, unable to map code onto large CGRAs. To address this, we propose a novel approach to the mapping problem where the time and space dimensions are decoupled and explored separately. We leverage an SMT formulation to traverse the time dimension first, and then perform a monomorphism-based search to find a valid spatial solution. Experimental results show that our approach achieves the same mapping quality of state-of-the-art techniques while significantly reducing compilation time, with this reduction being particularly tangible when compiling for large CGRAs. We achieve approximately $10^5\times$ average compilation speedup for the benchmarks evaluated on a $20\times 20$ CGRA. |
| title | Monomorphism-based CGRA Mapping via Space and Time Decoupling |
| topic | Hardware Architecture |
| url | https://arxiv.org/abs/2512.02859 |