Keysight AI Data Center Fabric Test Methodology
Application Notes
During Large Language Model (LLM) training, massive data transmissions between GPU nodes can lead to bottlenecks and slow down the training process. A well-designed network fabric is crucial to enable efficient data movement, reduce latency, and facilitate faster training times. This black book aims to prescribe a consistent and repeatable test process to provide measurable metrics with quantifiable KPIs (key performance indicator) that can be used to benchmark various implementations and ensure that data center operators optimize infrastructures for AI workloads. Following the methodologies presented here enables an organization to have better performance, scalability, and fault tolerance within AI data centers.