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  • Evaluation of performance and productivity metrics of potential programming languages in the HPC environment (Florian Wilkens), Bachelor's Thesis, School: Universität Hamburg, 2015-04-28
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Abstract

This thesis aims to analyze new programming languages in the context of high-performance computing (HPC). In contrast to many other evaluations the focus is not only on performance but also on developer productivity metrics. The two new languages Go and Rust are compared with C as it is one of the two commonly used languages in HPC next to Fortran. The base for the evaluation is a shortest path calculation based on real world geographical data which is parallelized for shared memory concurrency. An implementation of this concept was written in all three languages to compare multiple productivity and performance metrics like execution time, tooling support, memory consumption and development time across different phases. Although the results are not comprehensive enough to invalidate C as a leading language in HPC they clearly show that both Rust and Go offer tremendous productivity gain compared to C with similar performance. Additional work is required to further validate these results as future reseach topics are listed at the end of the thesis.

BibTeX

@misc{EOPAPMOPPL15,
	author	 = {Florian Wilkens},
	title	 = {{Evaluation of performance and productivity metrics of potential programming languages in the HPC environment}},
	advisors	 = {Michael Kuhn and Sandra Schröder},
	year	 = {2015},
	month	 = {04},
	school	 = {Universität Hamburg},
	type	 = {Bachelor's Thesis},
	abstract	 = {This thesis aims to analyze new programming languages in the context of high-performance computing (HPC). In contrast to many other evaluations the focus is not only on performance but also on developer productivity metrics. The two new languages Go and Rust are compared with C as it is one of the two commonly used languages in HPC next to Fortran. The base for the evaluation is a shortest path calculation based on real world geographical data which is parallelized for shared memory concurrency. An implementation of this concept was written in all three languages to compare multiple productivity and performance metrics like execution time, tooling support, memory consumption and development time across different phases. Although the results are not comprehensive enough to invalidate C as a leading language in HPC they clearly show that both Rust and Go offer tremendous productivity gain compared to C with similar performance. Additional work is required to further validate these results as future reseach topics are listed at the end of the thesis.},
}

publication.txt · Last modified: 2019-01-23 10:26 by 127.0.0.1

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