Mapping-Aware Kernel Partitioning Method for CGRAs Assisted by Deep Learning

Author:

Kojima TakuyaORCID,Ohwada Ayaka,Amano Hideharu

Funder

JSPS KAKENHI

JST CREST

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Hardware and Architecture,Signal Processing

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. An Architecture-Agnostic Dataflow Mapping Framework on CGRA;2024 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW);2024-05-27

2. HierCGRA: A Novel Framework for Large-scale CGRA with Hierarchical Modeling and Automated Design Space Exploration;ACM Transactions on Reconfigurable Technology and Systems;2024-05-10

3. Data Flow Graph Partitioning Method for CGRA Temporal Mapping Based on Bayesian Optimization;2024 Conference of Science and Technology for Integrated Circuits (CSTIC);2024-03-17

4. EEG SIGNAL-DRIVEN HUMAN–COMPUTER INTERACTION EMOTION RECOGNITION MODEL USING AN ATTENTIONAL NEURAL NETWORK ALGORITHM;Journal of Mechanics in Medicine and Biology;2023-08-31

5. APPEND: Rethinking ASIP Synthesis in the Era of AI;2023 60th ACM/IEEE Design Automation Conference (DAC);2023-07-09

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