Juan Cruz Rodriguez es alumno del Doctorado en Ciencias de la Computación de FaMAF-UNC bajo la dirección de Elmer Fernández (UCC). Recientemente dictó junto a CPA-CONICET Marcos Mazzini el curso «R en el CCAD«.
Durante la GSoC 2019 Juan Cruz presentó la propuesta «R Code Optimizer» que fue aceptada y comenzará a trabajar desde el 27 de mayo en el optimizador de código para R.
La propuesta es simple, clara y extremadamente útil para una comunidad cada vez más grande de usuarios.
R is slow compared to other popular languages. “The R interpreter is not fast and execution of large amounts of R code can be unacceptably slow”. This is because “R was purposely designed to make data analysis and statistics easier for you to do. It was not designed to make life easier for your computer”. Although there are several R interpreters that attempt to improve execution speed, “switching interpreters is something to consider carefully”.
“Beyond performance limitations due to design and implementation, it has to be said that a lot of R code is slow simply because it’s poorly written. Few R users have any formal training in programming or software development. This means that it’s relatively easy to make most R code much faster”. “A good deal of work is going into making R more efficient. Much of this work consists of reimplementing interpreted R code”.
The main goal of this project is to provide an R package with functions that allow users to automatically apply strategies to optimize their R code. The developed functions will have as input and output R code so that the resulting code will allow the user to understand what modifications in the code cause its optimization.
Felicitamos a «Cancu» por su logro y esperamos que su contribución sea parte de R y que esto implique un uso más eficiente de los recursos computacionales actuales.
