A hierarchical adaptive multi-task reinforcement learning framework for multiplier circuit design

Z Wang, J Wang, D Zuo, J Yunjie, X ** for coarse-grained reconfigurable architectures with reinforcement learning and monte-carlo tree search
X Kong, Y Huang, J Zhu, X Man, Y Liu, C Feng… - Proceedings of the 50th …, 2023 - dl.acm.org
Coarse-grained reconfigurable architecture (CGRA) has become a promising candidate for
data-intensive computing due to its flexibility and high energy efficiency. CGRA compilers …

Lisa: Graph neural network based portable map** on spatial accelerators

Z Li, D Wu, D Wijerathne, T Mitra - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
Spatial accelerators, such as Coarse-Grained Reconfigurable Arrays (CGRA), provide a
promising pathway to scale the performance and power efficiency of computing systems …

Opencgra: Democratizing coarse-grained reconfigurable arrays

C Tan, NB Agostini, J Zhang, M Minutoli… - 2021 IEEE 32nd …, 2021 - ieeexplore.ieee.org
Reconfigurable architectures are today experiencing a renewed interest for their ability to
provide specialization without sacrificing the capability to adapt to disparate workloads …

ML-CGRA: An integrated compilation framework to enable efficient machine learning acceleration on CGRAs

Y Luo, C Tan, NB Agostini, A Li… - 2023 60th ACM/IEEE …, 2023 - ieeexplore.ieee.org
Coarse-Grained Reconfigurable Arrays (CGRAs) can achieve higher energy-efficiency than
general-purpose processors and accelerators or fine-grained reconfigurable devices, while …

Twenty years of automated methods for map** applications on CGRA

KJM Martin - 2022 IEEE international parallel and distributed …, 2022 - ieeexplore.ieee.org
Coarse-Grained Reconfigurable Architectures (CGRAs) emerged about 30 years ago. The
very first CGRAs were programmed manually. Fortunately, some compilation approaches …