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: 12 August 2026
Source: arXiv cs.AI
Category: Research
Topics: Agents & autonomy
Retrieved: 13 August 2026
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ethics.ai (12 August 2026), “Ready Cohorts: Bounding GPU Opportunity and Avoiding Host Round Trips in LLM-Agent Control,” evidence record 19036, https://ethics.ai/record/19036 (originally published by arXiv cs.AI).
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