Featured projects Training state-of-the-art large language models (LLMs) with billions of parameters requires distributed training across hundreds or thousands of GPUs. At this scale, hardware failures are not exceptional events—they are expected. A single GPU memory error, network partition, or node crash can bring down an entire training run that has been progressing for days or weeks. While our...