Towards Elastic Resource Management

Isaías A. Comprés Ureña () and Michael Gerndt
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Isaías A. Comprés Ureña: Technical University of Munich (TUM)
Michael Gerndt: Technical University of Munich (TUM)

A chapter in Tools for High Performance Computing 2017, 2019, pp 105-127 from Springer

Abstract: Abstract A new paradigm for HPC Resource Management, called Elastic Computing, is under development at the Invasive Computing Transregional Collaborative Research Center. An extension to MPI for programming elastic applications and a resource manager were implemented. The resource manager is an extension of the SLURM batch scheduler. Resource elasticity allows the resource manager to dictate changes in the resource allocations of running applications based on scheduler decisions. These resource allocation changes are decided by the scheduler based on performance feedback from the applications. The collection of performance feedback from running applications poses unique challenges for the runtime system. In this document, our current performance feedback system is presented.

Keywords: Resource management; MPI; Performance monitoring (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/978-3-030-11987-4_7

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