Publication details
- A Multi-purpose Framework for Efficient Parallelized Execution of Charged Particle Tracking (Georgiana Mania), PhD Thesis, School: Universität Hamburg, 2023-07-12
Publication details – URL
Abstract
Complex particle tracking software used in High Energy Physics experiments already pushes the edges of computing resources with demanding requirements for speed and memory throughput, but the future experiments pose an even greater challenge. Although many supercomputers already reached petascale capacities using many-core architectures and accelerators, many scientific applications still need to efficiently make use of the new resources. This research work is focused on investigating the parallelization potential of the particle reconstruction flow and ultimately, on developing a prototype of a framework which could contribute to a smooth transition to a platform-agnostic code base which avoids duplicating implementations for different architectures, while ensuring improved performance.
BibTeX
@phdthesis{AMFFEPEOCP23,
author = {Georgiana Mania},
title = {{A Multi-purpose Framework for Efficient Parallelized Execution of Charged Particle
Tracking}},
advisors = {Thomas Ludwig},
year = {2023},
month = {07},
school = {Universität Hamburg},
howpublished = {{Online \url{https://ediss.sub.uni-hamburg.de/bitstream/ediss/10482/2/GeorgianaMania_PhD_Thesis_revised.pdf}}},
type = {PhD Thesis},
abstract = {Complex particle tracking software used in High Energy Physics experiments already
pushes the edges of computing resources with demanding requirements for speed and memory
throughput, but the future experiments pose an even greater challenge. Although many
supercomputers already reached petascale capacities using many-core architectures and
accelerators, many scientific applications still need to efficiently make use of the new
resources. This research work is focused on investigating the parallelization potential of the
particle reconstruction flow and ultimately, on developing a prototype of a framework which
could contribute to a smooth transition to a platform-agnostic code base which avoids
duplicating implementations for different architectures, while ensuring improved performance.},
url = {https://ediss.sub.uni-hamburg.de/handle/ediss/10482},
}