The exponential growth in AI model complexity has driven parameter counts from millions to trillions, requiring unprecedented computational resources that require clusters of GPUs to accommodate. The adoption of mixture-of-experts (MoE) architectures and AI reasoning with test-time scaling increases compute demands even more. To efficiently deploy inference, AI systems have evolved toward large-scale parallelization strategies, … Continue reading Scaling AI Inference Performance and Flexibility with NVIDIA NVLink and NVLink Fusion