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Optimising the computational footprint in precision particle physics
<!--HTML-->During 2020, I was working on a grant proposal in precision particle physics, on so-called matching and merging strategies, for the widely used Pythia event generator. For complex processes, these types of calculations can be quite resource-intensive. That same summer, my home count...
Autores principales: | , |
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Lenguaje: | eng |
Publicado: |
2022
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Materias: | |
Acceso en línea: | http://cds.cern.ch/record/2826382 |
Sumario: | <!--HTML-->During 2020, I was working on a grant proposal in precision particle physics, on so-called matching and merging strategies, for the widely used Pythia event generator. For complex processes, these types of calculations can be quite resource-intensive. That same summer, my home country of Australia had experienced catastrophic bush fires. It made me reconsider what I was doing, proposing calculations that would take immense computing resources to perform. I rewrote the grant with a central focus on reducing the computational footprint necessary to do these calculations - but still pushing the state of the art. The grant was awarded and we are now beginning to work in this direction. It was the first grant proposal I have written in which reduction of computational footprint in itself had been an explicit goal. |
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