https://github.com/beliavsky/scientific-programming-speed-comparisons
Links to speed comparisons of languages used in scientific omputing
https://github.com/beliavsky/scientific-programming-speed-comparisons
benchmarks cpp fortran julia language-comparison matlab performance python r scientific-computing scientific-programming
Last synced: 9 months ago
JSON representation
Links to speed comparisons of languages used in scientific omputing
- Host: GitHub
- URL: https://github.com/beliavsky/scientific-programming-speed-comparisons
- Owner: Beliavsky
- Created: 2021-05-24T17:54:42.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2021-05-25T12:57:41.000Z (over 4 years ago)
- Last Synced: 2025-01-30T07:42:45.381Z (11 months ago)
- Topics: benchmarks, cpp, fortran, julia, language-comparison, matlab, performance, python, r, scientific-computing, scientific-programming
- Homepage:
- Size: 8.79 KB
- Stars: 3
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Scientific Programming Speed Comparisons
* [R vs. Python vs. Julia: How easy it is to write efficient code?](https://towardsdatascience.com/r-vs-python-vs-julia-90456a2bcbab) (2021) by Daniel Moura
* [Analysis of the performance of evaluating the density gradient employing various language implementations (C++/Fortran/Rust/Julia)](https://github.com/zyth0s/bench_density_gradient_wfn)
* [NetworkDynamics.jl -- Composing and simulating complex networks in Julia](https://arxiv.org/abs/2012.12696) (2021) by Michael Lindner et al. Discussed [here](https://fortran-lang.discourse.group/t/research-articles-using-fortran/1101/6?u=beliavsky). Network Dynamics Benchmarks comparing Fortran, Julia and Python [here](https://github.com/PIK-ICoN/NetworkDynamicsBenchmarks)
* [Performance comparison R, Julia, Fortran for Bayesian binary probit](https://github.com/driesbenoit/benchmark_R_Julia_Fortran) (2021) by Dries Benoit
* [The Quest for Speed - An Indicative Survey in Improving Performance](https://discourse.equadratures.org/t/the-quest-for-speed-an-indicative-survey-in-improving-performance/144) (2021) by Bryn Noel Ubald
* [A Comparative Study on the Efficiency of Compiled Languages and MATLAB/Simulink for Simulation of Highly Nonlinear Automotive Systems](https://jacm.scu.ac.ir/article_15549.html)(2020) by Amir Hossein Pasdar, Shahram Azadi, and Reza Kazemi, Journal of Applied and Computational Mechanics. Discussed [here](https://fortran-lang.discourse.group/t/research-articles-using-fortran/1101/5?u=beliavsky)
* [Basic Comparison of Various Computing Languages: Python, Julia, Matlab, IDL, R, Java, Scala, C, Fortran](https://github.com/JulesKouatchou/basic_language_comparison) (2020) by Jules Kouatchou and Alexander Medema
* [The Linear Algebra Mapping Problem](https://arxiv.org/pdf/1911.09421v1.pdf) (2019) by Christos Psarras, et al
* [A Comparison of Programming Languages in Economics: An Update](https://www.sas.upenn.edu/~jesusfv/Update_March_23_2018.pdf) (2018) by S. Boragan Aruoba and
Jesus Fernandez-Villaverde. [original paper] (https://www.nber.org/system/files/working_papers/w20263/w20263.pdf) [code at GitHub](https://github.com/jesusfv/Comparison-Programming-Languages-Economics)
* [The Need for Speed Part 2: C++ vs. Fortran vs. C](https://www.r-bloggers.com/2018/12/the-need-for-speed-part-2-c-vs-fortran-vs-c/)(2018) by Avi. [Part 1](https://www.avrahamadler.com/2018/12/09/the-need-for-speed-part-1-building-an-r-package-with-fortran/)
* [Energy efficiency across programming languages: how do energy, time, and memory relate?](https://greenlab.di.uminho.pt/wp-content/uploads/2017/10/sleFinal.pdf) (2017) by Rui Pereira et al.
* [Comparison of performance: Python NumPy and Numba, MATLAB, and Fortran](https://jekel.me/2017/Python-with-Numba-faster-than-fortran/)(2017) by Charles Jekel