December 2024 PaddleNLP monthly summary: Delivered an end-to-end documentation update for running Llama 2 13b on Hygon DCU with PaddleNLP usage guide. The guide covers environment setup, data preparation, fine-tuning, pre-training, and high-performance inference, and highlights the advantages of Hygon DCU with PaddleNLP (4D hybrid parallel training and optimized operators). Major bugs fixed: none reported this month. Overall impact: accelerates customer onboarding and deployment of Llama 2 13b on DCU, improves cross-hardware interoperability, and establishes a repeatable reference workflow for DCU deployments. Technologies/skills demonstrated: technical documentation, hardware-software integration, PaddleNLP workflows, and performance-oriented optimization.

October 2024: Strengthened distributed training reliability and test coverage in PaddlePaddle. Implemented targeted test coverage for hybrid parallel execution and recompute paths, refactored tests, and updated build configuration to ensure coverage across GPU/ROCm-enabled platforms. Enabled and validated test_dygraph_recompute across supported environments, laying groundwork for more robust distributed training scenarios and faster issue detection.