LLMOPS & AI INFRASTRUCTURE • 287 / 397
Operate AI like production: serving, GPUs, latency, capacity, routing and reliability.
Pipeline Parallelism
Pipeline parallelism places different groups of model layers on different devices and passes activations between them.
Think of it like
Think of Pipeline 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 Pipeline Parallelism to keep cost and latency under control.
SRE lens
It creates pipeline-stage coordination and latency considerations.
Remember thisPipeline parallelism places different groups of model layers on different devices and passes activations between them.