Abstract: Graph Neural Networks (GNNs) have gained popularity as an efficient choice for learning on graph-structured data. However, most methods are node or graph-centered, often overlooking valuable ...
Abstract: Coarse-Grained Reconfigurable Architectures (CGRAs) have been the subject of extensive research due to their balance between performance, energy efficiency, and flexibility. CGRAs must be ...