Research
Helium: Workflow-Aware LLM Serving Achieves 1.56x Speedup Over State-of-the-Art Agent Systems
Agentic workflows consist of interdependent LLM calls with overlapping prompts and intermediate results that existing systems like vLLM ignore, treating each call in isolation. Helium (arXiv:2603.16104) models agentic workloads as query plans with LLM invocations as first-class operators, adding proactive KV cache pre-warming for static prefixes and a cost-based, cache-aware scheduling algorithm using a templated radix tree. Achieves up to 1.56x speedup over state-of-the-art agent serving systems with no model changes required.
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