LLMOPS & AI INFRASTRUCTURE • 288 / 397

Operate AI like production: serving, GPUs, latency, capacity, routing and reliability.

Data Parallelism

Data parallelism replicates a model across devices and distributes different inputs to each replica.

Think of it like

Think of Data Parallelism like familiar infrastructure capacity and traffic engineering, except the scarce resources are often tokens, GPU memory and model latency.

Real life

High-scale AI services depend on Data Parallelism to keep cost and latency under control.

SRE lens

Useful for scaling independent training or inference work.

Remember thisData parallelism replicates a model across devices and distributes different inputs to each replica.

Next conceptThroughput

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