Post-graduate theses
Current Record: 52 of 833
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Identifier |
000452895 |
Title |
Genisys, a resource management and placement mechanism for HPC and datacenter applications under Kubernetes |
Alternative Title |
Genisys, ένας μηχανισμός διαχείρισης πόρων και τοποθέτησης εφαρμογών υψηλών επιδόσεων κάτω από το σύστημα Kubernetes |
Author
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Ζέρβας, Γεώργιος Μ.
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Thesis advisor
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Μπίλας, Άγγελος
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Reviewer
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Μαγκούτης, Κωνσταντίνος
Πρατικάκης, Πολύβιος
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Abstract |
Today, Cloud and HPC workloads tend to use different approaches for managing
resources. However, as more and more applications require a mixture of both high-
performance and data processing computation, convergence of Cloud and HPC
resource management is becoming a necessity. Cloud-oriented resource management
strives to share physical resources across applications to improve infrastructure
efficiency. On the other hand, the HPC community prefers to rely on job queueing
mechanisms to coordinate among tasks, favoring dedicated use of physical resources
by each application.
In this work, we design a combined Slurm-Kubernetes system that is able to run
unmodified HPC workloads under Kubernetes, alongside other, non-HPC applications.
First, we containerize the whole HPC execution environment into a virtual cluster,
giving each user a private HPC context, with common libraries and utilities built-in, like
the Slurm job scheduler. Second, we design a custom Slurm-Kubernetes protocol that
allows Slurm to dynamically request resources from Kubernetes. Essentially, in our
system the Slurm controller delegates placement and scheduling decisions to
Kubernetes, thus establishing a centralized resource management endpoint for all
available resources. Third, our custom Kubernetes scheduler applies different
placement policies depending on the workload type.
We evaluate the performance of our system compared to statically partitioned
Kubernetes and Slurm-based HPC clusters and demonstrate its ability to allow the
joint execution of applications with seemingly conflicting requirements on the same
infrastructure with minimal interference.
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Language |
English |
Subject |
Cloud |
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Docker |
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Genisys |
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Integration |
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Scheduler |
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Slurm |
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Virtual-clusters |
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Υπολογιστικό νέφος |
Issue date |
2022-12-02 |
Collection
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School/Department--School of Sciences and Engineering--Department of Computer Science--Post-graduate theses
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Type of Work--Post-graduate theses
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Permanent Link |
https://elocus.lib.uoc.gr//dlib/9/8/0/metadata-dlib-1671113251-970786-6061.tkl
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Views |
491 |