Solving Bottlenecks on the Data Input Pipeline with PyTorch Profiler and TensorBoard

PyTorch Model Performance Analysis and Optimization — Part 4

This is the fourth post in our series of posts on the topic of performance analysis and optimization of GPU-based PyTorch workloads. Our focus in this post will be on the training data input pipeline. In a typical training application, the host’s CPUs load, pre-process, and collate data before feeding it into the GPU for training. Bottlenecks in the input pipeline occur when the …

analysis data deep learning focus gpu hands-on-tutorials optimization part performance performance analysis performance-optimization pipeline pytorch series tensorboard training training data workloads