Serving trillion-parameter models to millions of concurrent users is a high-stakes operational challenge where memory bandwidth is the primary bottleneck. The Inference Engine Handbook is an uncompromising manual for MLOps and infrastructure architects.
Key Coverage:
- Optimizing Time to First Token (TTFT), KV Cache memory management, and PagedAttention.
- Model quantization techniques (FP8, INT8, AWQ) to double hardware throughput.
- Cluster orchestration using Multi-Instance GPU (MIG) partitioning, Kubernetes, and Ray Serve.
