PGPointNovo is an improved implementation of PointNovo that enables parallel processing on multiple GPUs. This version includes several model enhancements, such as the rectified Adam learning rate scheduler , a lookahead strategy that uses two sets of model weights to reduce the need for extensive hyperparameter tuning , and a technique called gradient centralization that regularizes the learned weight vectors to improve generalization performance.