Dr Ashish Bamania · GPU Architecture Guide

NVIDIA GPUs for AI Engineers

A free explainer on the GPU hardware an AI engineer actually has to reason about: streaming multiprocessors, CUDA and tensor cores, on-chip SRAM against HBM, and the NVIDIA line from Volta and the V100 in 2017 through T4, A100, H100, H200, L40S, B100, B200, B300 and Rubin to Feynman in 2028. It then covers interconnects - PCIe, NVLink 4 to 6, NVSwitch, NVLink-C2C - and scales outward through Spectrum-X Ethernet and Quantum InfiniBand to the node, rack, cluster and facility hierarchy, mapping tensor, data and pipeline parallelism onto it.