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Home/Glossary/Expert parallelism

Parallelism

Expert parallelism

What it is

Expert parallelism places mixture-of-experts feed-forward experts on different devices. Each token is routed to selected experts, then expert outputs return to the token's execution path.

Why it moves cost and latency

Distribution spreads expert parameters and compute, but token exchange can become communication-heavy. Uneven routing leaves some devices busy while others wait.

What it looks like in practice

Deployments choose expert placement, routing capacity, and communication groups around the available topology. Operators track load skew, dropped or rerouted work, and collective time.

Related terms

  • Tensor parallelism->
  • Pipeline parallelism->
  • Mixture-of-experts serving->
  • NVLink->

Questions this definition answers

What does Expert parallelism mean in inference serving?

Expert parallelism places mixture-of-experts feed-forward experts on different devices. Each token is routed to selected experts, then expert outputs return to the token's execution path. Deployments choose expert placement, routing capacity, and communication groups around the available topology. Operators track load skew, dropped or rerouted work, and collective time.

Why can Expert parallelism move cost or latency?

Distribution spreads expert parameters and compute, but token exchange can become communication-heavy. Uneven routing leaves some devices busy while others wait.

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