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Title: Profiling HPC applications in containerized environments
Author: Sanuy Lostes, Albert
Tutor: Iserte, Sergio  
Others: Jorba, Josep  
Abstract: Scientific studies very often rely on supercomputers to solve difficult problems. However, reproducibility is one of the core principles in any scientific research and it is often expected that the findings of any study can be replicated with a high degree of reliability. Running these applications in containers that have been prepared and curated beforehand can provide the desired reliability, remove unnecessary complexity and reduce the manual interaction to reduce the risk of human errors. The overall goal of this project is to use Docker to create an image that contains a distributed scientific application in addition to the necessary tools that allow profiling the behaviour of the program after its execution with different workloads. The Docker containers will be managed with Singularity , the most widely used container system for HPC. The infrastructure of the HPC cluster used for this study is composed of Raspberries Pi 4 Model B hosted on-premises.
Keywords: cluster computing
scientific applications
Document type: info:eu-repo/semantics/masterThesis
Issue Date: 17-Jun-2022
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