VQV Signal
Herschel is a system designed for continuous optimization of large language model inference in production by using adaptive, on-demand profiling to balance detailed data collection with overhead. This approach addresses inefficiencies that arise under complex serving conditions which static profili...
Herschel is a system designed for continuous optimization of large language model inference in production by using adaptive, on-demand profiling to balance detailed data collection with overhead. This approach addresses inefficiencies that arise under complex serving conditions which static profili...
AI-assisted summary based on the listed source.
Model-as-a-service platforms call for continuous optimization as complex serving conditions expose inefficiencies missed before deployment. Detailed always-on profiling can incur substantial overhead, while lightweight collection omits information needed for diagnosis. We present Herschel, a continuous...
Efficient LLM inference is critical for model-as-a-service platforms to maintain performance and cost-effectiveness. Herschel's method allows ongoing diagnosis and optimization without the high overhead of always-on profiling or the blind spots of lightweight methods.
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VQV surfaced this signal because it is recent, relevant to LLM Inference, connected to arXiv.
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