# ARC-V: Vertical Resource Adaptivity for HPC Workloads in Containerized Environments

arXiv: https://arxiv.org/abs/2505.02964 · HTML: https://mlsanity.com/paper/2505.02964/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 May 2025.

## Built on by (most cited first, 1 of 1)

- [MAS-H2: A Hierarchical Multi-Agent System for Holistic Cloud-Native Autoscaling](https://mlsanity.com/paper/2603.07607/) (2026)

## Abstract (arXiv)

Existing state-of-the-art vertical autoscalers for containerized environments are traditionally built for cloud applications, which might behave differently than HPC workloads with their dynamic resource consumption. In these environments, autoscalers may create an inefficient resource allocation. This work analyzes nine representative HPC applications with different memory consumption patterns. Our results identify the limitations and inefficiencies of the Kubernetes Vertical Pod Autoscaler (VPA) for enabling memory elastic execution of HPC applications. We propose, implement, and evaluate ARC-V. This policy leverages both in-flight resource updates of pods in Kubernetes and the knowledge of memory consumption patterns of HPC applications for achieving elastic memory resource provisioning at the node level. Our results show that ARC-V can effectively save memory while eliminating out-of-memory errors compared to the standard Kubernetes VPA.