Baidu recently introduced Baige 4.0, a new version of its AI Heterogeneous Computing Platform, which focuses on enhancing cluster stability and efficiency.
One of the standout features of Baige 4.0 is its ability to monitor GPU clusters, automatically detecting failures and migrating workloads to prevent disruptions. Furthermore, this system improves fault detection and localisation to address issues quickly and effectively, minimizing costly downtime.
Baige 4.0 also boasts an impressive 99.5% training efficiency for LLMs across tens of thousands of GPUs. This efficiency was achieved through improvements in cluster design, job scheduling, and VRAM optimization, leading to a 30% performance boost compared to industry averages.
The platform is now equipped to handle clusters of up to 100,000 GPUs, pushing the boundaries of AI training infrastructure.
Improved Model Inference and Use Cases
Baige 4.0 has made significant strides in model inference, particularly in long-text inference, where its efficiency has more than doubled. This improvement stems from advanced techniques such …