What Is GPU Cluster?
A GPU cluster is a high-performance computing system consisting of multiple GPUs (Graphics Processing Units) interconnected via high-speed networks, working in parallel to train and serve large AI models that require more memory and compute than any single GPU can provide.
How GPU Cluster Works
Training frontier AI models like GPT-4 requires thousands of GPUs working together for months. A GPU cluster connects these GPUs with high-bandwidth interconnects (like NVIDIA NVLink and InfiniBand) so they can share data and gradients efficiently during distributed training. Modern AI clusters use NVIDIA H100 or H200 GPUs, each costing $25,000-40,000, and a cluster for training a frontier model can cost hundreds of millions of dollars. The cluster must also handle challenges like synchronizing computations, managing failures, and optimizing data movement. GPU clusters have become the most valuable strategic asset in AI, with cloud providers and AI labs investing billions in their construction.
Real-World Examples
Meta training LLaMA 3 on a cluster of 16,384 NVIDIA H100 GPUs connected with high-speed InfiniBand networking
A startup renting a 64-GPU cluster on AWS to train a specialized language model over two weeks
Google building custom TPU pods with thousands of chips to train Gemini models at massive scale