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Parameter Server: asynchronous shared parameters with flexible consistency

Contribution grade

Distributed machine-learning infrastructure · Human-designed research method or resource

Reference score175,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Designed a structured shared-vector/matrix parameter-server system with batched asynchronous communication, selectable consistency, elasticity and fault recovery for large learning workloads.

Scientific scope

Designed a structured shared-vector/matrix parameter-server system with batched asynchronous communication, selectable consistency, elasticity and fault recovery for large learning workloads. Source expressly calls this a third-generation implementation, not invention of the parameter-server concept or all distributed learning. Nine original authors across CMU/Baidu/Google; not the separate four-author communication-efficiency paper. Recovery/scale examples are tested-system properties under stated failures, not universal fault or convergence guarantees.

Evidence

The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Source expressly calls this a third-generation implementation, not invention of the parameter-server concept or all distributed learning. Nine original authors across CMU/Baidu/Google; not the separate four-author communication-efficiency paper. Recovery/scale examples are tested-system properties under stated failures, not universal fault or convergence guarantees.

Contributors

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

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