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TASKWORK: a cloud-aware runtime system for elastic task-parallel HPC applications

  • With the capability of employing virtually unlimited compute resources, the cloud evolved into an attractive execution environment for applications from the High Performance Computing (HPC) domain. By means of elastic scaling, compute resources can be provisioned and decommissioned at runtime. This gives rise to a new concept in HPC: Elasticity of parallel computations. However, it is still an open research question to which extent HPC applications can benefit from elastic scaling and how to leverage elasticity of parallel computations. In this paper, we discuss how to address these challenges for HPC applications with dynamic task parallelism and present TASKWORK, a cloud-aware runtime system based on our findings. TASKWORK enables the implementation of elastic HPC applications by means of higher level development frameworks and solves corresponding coordination problems based on Apache ZooKeeper. For evaluation purposes, we discuss a development framework for parallel branch-and-bound based on TASKWORK, show how to implement an elastic HPC application, and report on measurements with respect to parallel efficiency and elastic scaling.

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Metadaten
Name:Kehrer, Stefan; Blochinger, Wolfgang
URN:urn:nbn:de:bsz:rt2-opus4-23000
DOI:https://doi.org/10.5220/0007795501980209
Erschienen in:CLOSER 2019 : proceedings of the 9th International Conference on Cloud Computing and Services Science : Heraklion, Crete, Greece, May 2-4, 2019
Publisher:SCITEPRESS
Place of publication:Setúbal, Portugal
Editor:Victor Méndez Muñoz
Document Type:Conference Proceeding
Language:English
Year of Publication:2019
Tag:cloud computing; elasticity of parallel computations; high performance computing; task parallelism
Pagenumber:12
First Page:198
Last Page:209
Dewey Decimal Classification:004 Informatik
Open Access:Ja
Licence (German):License Logo  Creative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International