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VERA: Reinforcement Learning for Dynamic Memory Scaling of HPC Workloads in Kubernetes
Memory over-provisioning results in resource underutilization when HPC workloads run on Kubernetes. The default Vertical Pod Autoscaler (VPA) cannot anticipate phase-driven memory spikes for first-run HPC jobs. In this work, we present a reinforcement learning (RL) recommender VERA that formulates v
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