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Beaver: Elastic GPU Sharing between ML and Latency-Critical vRAN Workloads

Yao, Yuncheng et al.
arXiv (All) · Papers
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Within the shared industry vision of AI-RAN, AI-and-RAN seeks to co-locate virtualized radio access network (vRAN) workloads and AI services on shared GPUs. This sharing is inherently asymmetric: vRAN workload is latency-critical, whereas the machine learning (ML) workload is a throughput-oriented,
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