PyTorch Day China 2025

Deploying PyTorch in large-scale heterogeneous computing have huge challenges in stability, usability, performance, and quality.

This session will showcase best practices using real-world Huawei Ascend application scenarios and community contributions, demonstrating PyTorch and ecosystem components in large-scale heterogeneous computing.

Through Ascend-optimized technologies and architecture improvements in PyTorch, we have greatly enhanced computing performance in traning and inference, meeting production standards.

We’ve proposed and implemented features for heterogeneous compute and accelerator quality standards in PyTorch. Driving PyTorch’s application in heterogeneous compute, like PyTorch ecosystem projects: DeepSpeed, vLLM.

Finally, we will share real user stories from large-scale training and distributed inference, presenting best practices on the Ascend platform and helping the community address challenges in diverse compute scenarios.