Ready Cohorts: Bounding GPU Opportunity and Avoiding Host Round Trips in LLM-Agent Control
LLM-agent services repeatedly execute small deterministic transitions between model and tool calls: route an outcome, update state, and emit the next effect. We ask when this control path exposes enough concurrent work for GPU execution, and what changes when a GPU-computed route decision remains on device. We formalize the ready-cohort boundary using fixed-partition share F, exact offline share P*, local upper bound U, and online achieved share A. Under zero service time, unlimited capacity, an
Record details
Published: 11 August 2026
Source: HuggingFace Daily Papers
Category: Research
Topics: Agents & autonomy
Retrieved: 14 August 2026
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ethics.ai (11 August 2026), “Ready Cohorts: Bounding GPU Opportunity and Avoiding Host Round Trips in LLM-Agent Control,” evidence record 19149, https://ethics.ai/record/19149 (originally published by HuggingFace Daily Papers).
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