Albireo overlaps non-scalable overheads with compute in tensor-parallel LLM inference to raise the empirical optimal TP degree, delivering up to 1.9x throughput and 48% lower latency versus vLLM.
Preserve: Prefetching model weights and kv-cache in distributed llm serving.arXiv preprint arXiv:2501.08192, 2025
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Scaling LLM Inference Beyond Amdahl`s Limits via Eliminating Non-Scalable Overheads
Albireo overlaps non-scalable overheads with compute in tensor-parallel LLM inference to raise the empirical optimal TP degree, delivering up to 1.9x throughput and 48% lower latency versus vLLM.