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cs.DC2026
OpScale: Operator-level Provisioning and Autoscaling for LLM Serving
Xingqi Cui, Chieh-Jan Mike Liang, Ziang Tang +2
Achieving cost efficiency while meeting strict user-facing SLOs (e.g., time-to-first-token) remains a fundamental challenge for cloud GPU clusters serving large language models (LL…
cs.DC2026
Characterization-Guided GPU Fault Resilience in NVIDIA MPS
Rixin Liu, Xingqi Cui, Kaijian Wang +4
NVIDIA Multi-Process Service (MPS) enables fine-grained GPU sharing by allowing multiple processes to execute concurrently on the same GPU, making it an important mechanism for imp…
cs.DC2025
From Models to Operators: Rethinking Autoscaling Granularity for Large Generative Models
Xingqi Cui, Chieh-Jan Mike Liang, Jiarong Xing +1
Serving large generative models such as LLMs and multi- modal transformers requires balancing user-facing SLOs (e.g., time-to-first-token, time-between-tokens) with provider goals…