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Data Movement-Aware GPU Sharing for Data-Intensive Systems

Summary: Introduces GUST, a GPU scheduler that treats PCIe as a first-class schedulable resource and classifies kernels as transfer- or device-intensive to interleave analytics (PCIe-heavy) and inference (compute-heavy) workloads. Prototype colocating four mixed workloads reduces performance degradation vs dedicated GPUs from 3.9–7x to 2.8x. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
573
Venue
CIDR
Year
2026
Pagerank
4.1945683e-05
Overall Rank
9,971 | 30.64%
DOI
-

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