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Found 4 papers, 2 papers with code
HGNAS: Hardware-Aware Graph Neural Architecture Search for Edge Devices
To the best of our knowledge, HGNAS is the first automated GNN design framework for edge devices, and also the first work to achieve hardware awareness of GNNs across different platforms.
Lossy and Lossless (L$^2$) Post-training Model Size Compression
Then, a dedicated differentiable counter is introduced to guide the optimization of lossy compression to arrive at a more suitable point for later lossless compression.
Hardware-Aware Graph Neural Network Automated Design for Edge Computing Platforms
Moreover, HGNAS achieves hardware awareness during the GNN architecture design by leveraging a hardware performance predictor, which could balance the GNN model accuracy and efficiency corresponding to the characteristics of targeted devices.
Lossy and Lossless (L2) Post-training Model Size Compression
Then, a dedicated differentiable counter is introduced to guide the optimization of lossy compression to arrive at a more suitable point for later lossless compression.
