GPU architecture, inference systems, and ML algorithms — decoded from silicon to system to algorithm. Written for engineers who already know what RAG is.
Beyond the spec sheet: deriving actual cost per million tokens for each generation, accounting for memory capacity, bandwidth, rack power, and cooling — the numbers that determine your infrastructure decision.
NVLink, NVSwitch, InfiniBand, and RoCE — the bandwidth and latency numbers that determine whether your distributed training job scales or stalls.
Why memory bandwidth — not FLOPs — is the binding constraint for most LLM workloads, and how H100's five-level hierarchy determines what your kernels can actually achieve.