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Computer Science > Distributed, Parallel, and Cluster Computing

Title: On the Convergence of Malleability and the HPC PowerStack: Exploiting Dynamism in Over-Provisioned and Power-Constrained HPC Systems

Abstract: Recent High-Performance Computing (HPC) systems are facing important challenges, such as massive power consumption, while at the same time significantly under-utilized system resources. Given the power consumption trends, future systems will be deployed in an over-provisioned manner where more resources are installed than they can afford to power simultaneously. In such a scenario, maximizing resource utilization and energy efficiency, while keeping a given power constraint, is pivotal. Driven by this observation, in this position paper we first highlight the recent trends of resource management techniques, with a particular focus on malleability support (i.e., dynamically scaling resource allocations/requirements for a job), co-scheduling (i.e., co-locating multiple jobs within a node), and power management. Second, we consider putting them together, assess their relationships/synergies, and discuss the functionality requirements in each software component for future over-provisioned and power-constrained HPC systems. Third, we briefly introduce our ongoing efforts on the integration of software tools, which will ultimately lead to the convergence of malleability and power management, as it is designed in the HPC PowerStack initiative.
Subjects: Distributed, Parallel, and Cluster Computing (cs.DC)
Journal reference: High Performance Computing. ISC High Performance 2022 International Workshops. ISC High Performance 2022. Lecture Notes in Computer Science, vol 13387. Springer, Cham
DOI: 10.1007/978-3-031-23220-6_14
Cite as: arXiv:2405.03847 [cs.DC]
  (or arXiv:2405.03847v1 [cs.DC] for this version)

Submission history

From: Eishi Arima [view email]
[v1] Mon, 6 May 2024 20:51:59 GMT (851kb)

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