Scientific Programming Speed Comparisons

• R vs. Python vs. Julia: How easy it is to write efficient code? (2021) by Daniel Moura

• Analysis of the performance of evaluating the density gradient employing various language implementations (C++/Fortran/Rust/Julia)

• NetworkDynamics.jl -- Composing and simulating complex networks in Julia (2021) by Michael Lindner et al. Discussed here. Network Dynamics Benchmarks comparing Fortran, Julia and Python here

• Performance comparison R, Julia, Fortran for Bayesian binary probit (2021) by Dries Benoit

• The Quest for Speed - An Indicative Survey in Improving Performance (2021) by Bryn Noel Ubald

• A Comparative Study on the Efficiency of Compiled Languages ‎and MATLAB/Simulink for Simulation of Highly Nonlinear ‎Automotive Systems(2020) by Amir Hossein Pasdar, Shahram Azadi, and Reza Kazemi, Journal of Applied and Computational Mechanics. Discussed here

• Basic Comparison of Various Computing Languages: Python, Julia, Matlab, IDL, R, Java, Scala, C, Fortran (2020) by Jules Kouatchou and Alexander Medema

• The Linear Algebra Mapping Problem (2019) by Christos Psarras, et al

• A Comparison of Programming Languages in Economics: An Update (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

• The Need for Speed Part 2: C++ vs. Fortran vs. C(2018) by Avi. Part 1

• Energy efficiency across programming languages: how do energy, time, and memory relate? (2017) by Rui Pereira et al.

• Comparison of performance: Python NumPy and Numba, MATLAB, and Fortran(2017) by Charles Jekel