Appendix C — Referencias

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Referencias

Dowle, Matt, and Arun Srinivasan. 2021. Data.table: Extension of ‘Data.frame‘. https://CRAN.R-project.org/package=data.table.
Eddelbuettel, Dirk. 2013. Seamless R and C++ Integration with Rcpp. Springer. https://doi.org/10.1007/978-1-4614-6868-4.
Eddelbuettel, Dirk, and James Joseph Balamuta. 2018. “Extending extitR with extitC++: A Brief Introduction to extitRcpp.” The American Statistician 72 (1): 28–36. https://doi.org/10.1080/00031305.2017.1375990.
Eddelbuettel, Dirk, and Romain François. 2011. “Rcpp: Seamless R and C++ Integration.” Journal of Statistical Software 40 (8): 1–18. https://doi.org/10.18637/jss.v040.i08.
LUMI consortium. 2023. Documentation - Distribution and Binding. https://docs.lumi-supercomputer.eu/runjobs/scheduled-jobs/distribution-binding/.
R Core Team. 2023. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. https://www.R-project.org/.
Rue-Albrecht, Kevin, Daniela Cassol, Johannes Rainer, and Lori Shepherd. n.d. Welcome | Bioconductor Packages: Development, Maintenance, and Peer Review.
Vega Yon, George, and Paul Marjoram. 2019. “slurmR: A Lightweight Wrapper for HPC with Slurm.” The Journal of Open Source Software 4 (39). https://doi.org/10.21105/joss.01493.
Vega Yon, George, and Paul Marjoram. 2022. slurmR: A Lightweight Wrapper for ’Slurm’. https://github.com/USCbiostats/slurmR.
Yoo, Andy B., Morris A. Jette, and Mark Grondona. 2003. “SLURM: Simple Linux Utility for Resource Management.” In Job Scheduling Strategies for Parallel Processing, edited by Dror Feitelson, Larry Rudolph, and Uwe Schwiegelshohn, vol. 2862. Lecture Notes in Computer Science. Springer Berlin Heidelberg. https://doi.org/10.1007/10968987_3.

Recursos Adicionales

Libros Recomendados

  • Advanced R por Hadley Wickham
  • Efficient R Programming por Colin Gillespie y Robin Lovelace
  • Parallel R por Q. Ethan McCallum y Stephen Weston
  • Seamless R and C++ Integration with Rcpp por Dirk Eddelbuettel

Sitios Web y Documentación

Paquetes Relevantes

  • parallel: Computación paralela básica
  • foreach: Bucles paralelos
  • future: Framework unificado para computación paralela
  • Rcpp: Integración R/C++
  • data.table: Procesamiento eficiente de datos
  • bench: Benchmarking de código