Author:
Liu Dajiang,Yin Shouyi,Peng Yu,Liu Leibo,Wei Shaojun
Funder
China Major Science and Technology (S&T) Project
National High Technologies Research Program, China
National Natural Science Foundation of China
International S&T Cooperation Project
Tsinghua Indigenous Research Project
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Hardware and Architecture,Software
Cited by
12 articles.
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1. E2EMap: End-to-End Reinforcement Learning for CGRA Compilation via Reverse Mapping;2024 IEEE International Symposium on High-Performance Computer Architecture (HPCA);2024-03-02
2. Towards High-Quality CGRA Mapping with Graph Neural Networks and Reinforcement Learning;Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design;2022-10-30
3. An Analysis of Mapping Polybench Kernels to HPC CGRAs;2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW);2022-05
4. Mapping-Aware Kernel Partitioning Method for CGRAs Assisted by Deep Learning;IEEE Transactions on Parallel and Distributed Systems;2022-05-01
5. OpenCGRA: Democratizing Coarse-Grained Reconfigurable Arrays;2021 IEEE 32nd International Conference on Application-specific Systems, Architectures and Processors (ASAP);2021-07