Engineering Insights
How to Fix PyTorch GPU Starvation for Faster RNN Training
Auto-regressive sequence generation can notoriously drag GPU utilization to near zero. In a recent enterprise translation project, we encountered severe PyTorch bottlenecks during LSTM decoding. Here is how we bypassed Python loop overhead, implemented sequence-level vectorization, and saturated our GPUs for dramatically faster training.
