PaddlePaddle 2.3.1 introduces official support for CUDA 11.6, significant upgrades to quantization workflows including AMP support, and performance improvements in attention and linear operators.
PaddlePaddle 2.3.2 addresses CUDA 11.7 compatibility issues, improves quantization workflows, and expands inference support for ONNX Runtime and TensorRT.
PaddlePaddle 2.4.2 introduces Cutlass-based kernel fusion for sparse convolutions and fixes critical bugs in distributed training and mixed-precision inference.
PaddlePaddle 2.6.0 introduces a new Intermediate Representation (PIR) and integrates the CINN compiler to enhance extensibility and performance. The update focuses on large model support through Auto Parallelism, advanced distributed training strategies, and optimized inference capabilities.
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.
Baidu’s PaddlePaddle framework receives version 2.2.2, introducing the Mish activation function, expanded TensorRT support, and numerous bug fixes for training and inference workflows.
