I am training graphormer-slim on a custom dataset with 5K graphs and the loss is coming down nicely. However, the GPU utilization is close to zero while the CPU processes (16) are very busy, which means that the CPU is the bottleneck and I could be training much faster...
Is there anyway to make the CPU side faster?
details:
graphs in DGL format
50-100 nodes per graph
1-3 edges per node
I am training graphormer-slim on a custom dataset with 5K graphs and the loss is coming down nicely. However, the GPU utilization is close to zero while the CPU processes (16) are very busy, which means that the CPU is the bottleneck and I could be training much faster...
Is there anyway to make the CPU side faster?
details: graphs in DGL format 50-100 nodes per graph 1-3 edges per node