Use Cases

Real-world applications

Distributed AI Model Training

Scaling machine learning model training across multiple nodes and accelerators to reduce training time.

Multimodal Data Processing

Processing and analyzing large datasets containing images, videos, and audio in parallel.

Large Language Model Serving

Deploying and fine-tuning large language models for inference in production environments.