PaddlePaddle 2.4.0 introduces a new dynamic graph architecture, 55 sparse computing APIs, and a GPU training engine for large-scale graph neural networks, alongside significant enhancements to distributed training and deployment.
Baidu’s PaddlePaddle framework updates to v3.1.1, focusing on robust large model training, FP8 optimization, and new API features.
PaddlePaddle 2.2.0 introduces 100+ new APIs for scientific computing and signal processing, enhances dynamic-to-static graph conversion for mixed precision, and advances distributed training with 4D hybrid parallelism. The release also adds TensorRT 8.x support and dynamic shape auto-configuration for easier deployment.
PaddlePaddle 2.2.1 introduces experimental support for NVIDIA’s CUDA Graphs and new linear algebra APIs, alongside optimizations for training throughput and bug fixes for core tensor operations.
