GCV-Turbo: End-to-end Acceleration of GNN-based Computer Vision Tasks on FPGA

arXiv:2404.07188v1 Announce Type: cross
Abstract: Graph neural networks (GNNs) have recently empowered various novel computer vision (CV) tasks. In GNN-based CV tasks, a combination of CNN layers and GNN layers or only GNN layers are employed. This paper introduces GCV-Turbo, a domain-specific accelerator on FPGA for end-to-end acceleration of GNN-based CV tasks. GCV-Turbo consists of two key components: (1) a \emph{novel} hardware architecture optimized for the computation kernels in both CNNs and GNNs using the same set of computation resources. …

abstract accelerator arxiv cnn combination computer computer vision cs.cv cs.dc domain eess.iv fpga gnn gnns graph graph neural networks networks neural networks novel paper tasks turbo type vision