Term tag: GPU Computing

CUDA

NVIDIA's software layer for GPUs — the programming model that turned graphics cards into AI hardware, and the real reason rivals with comparable silicon lose.

GPU Computing

Why a graphics chip runs AI: a GPU spends its transistors on arithmetic instead of on making one thread fast — and what that trade wins and costs.

High Bandwidth Memory (HBM)

Stacked DRAM bonded beside the GPU die — the scarce component that gates AI accelerator supply, and why bandwidth rather than capacity is the constraint.

Memory Wall

Why LLM inference waits on memory rather than maths — arithmetic intensity, the roofline, and the one fact that explains HBM scarcity and the price of a token.

NVIDIA GPU for AI

Why AI training runs on NVIDIA rather than cheaper silicon — tensor cores, NVLink, and the software that decides how much of the datasheet you actually get.

Tensor Operations

The array manipulations — elementwise math, matrix multiplication, reshaping, broadcasting, reduction — that every neural network is built out of.