cpp11armadillo：一个使用Armadillo c++库的R包

IF 2.4 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

SoftwareX Pub Date : 2025-02-19 DOI:10.1016/j.softx.2025.102087

Mauricio Vargas Sepulveda , Jonathan Schneider Malamud

{"title":"cpp11armadillo：一个使用Armadillo c++库的R包","authors":"Mauricio Vargas Sepulveda , Jonathan Schneider Malamud","doi":"10.1016/j.softx.2025.102087","DOIUrl":null,"url":null,"abstract":"<div><div>This article introduces ‘cpp11armadillo’, an R package that integrates the highly efficient Armadillo C++ linear algebra library with R through the ‘cpp11’ interface. Designed to offer significant performance improvements for computationally intensive tasks, ‘cpp11armadillo’ simplifies the process of integrating C++ code into R. This package is particularly suited for R users requiring efficient matrix operations, especially in cases where vectorization is not possible. Our benchmarks demonstrate substantial speed gains over native R functions and Rcpp-based setups.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"30 ","pages":"Article 102087"},"PeriodicalIF":2.4000,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"cpp11armadillo: An R package to use the Armadillo C++ library\",\"authors\":\"Mauricio Vargas Sepulveda , Jonathan Schneider Malamud\",\"doi\":\"10.1016/j.softx.2025.102087\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This article introduces ‘cpp11armadillo’, an R package that integrates the highly efficient Armadillo C++ linear algebra library with R through the ‘cpp11’ interface. Designed to offer significant performance improvements for computationally intensive tasks, ‘cpp11armadillo’ simplifies the process of integrating C++ code into R. This package is particularly suited for R users requiring efficient matrix operations, especially in cases where vectorization is not possible. Our benchmarks demonstrate substantial speed gains over native R functions and Rcpp-based setups.</div></div>\",\"PeriodicalId\":21905,\"journal\":{\"name\":\"SoftwareX\",\"volume\":\"30 \",\"pages\":\"Article 102087\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2025-02-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SoftwareX\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352711025000548\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SoftwareX","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352711025000548","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}

引用次数: 0

摘要

本文介绍了一个R包“cpp11armadillo”，它通过“cpp11”接口将高效的Armadillo c++线性代数库与R集成在一起。cpp11armadillo旨在为计算密集型任务提供显著的性能改进，它简化了将c++代码集成到R中的过程。这个包特别适合需要高效矩阵运算的R用户，特别是在无法向量化的情况下。我们的基准测试表明，与本地R函数和基于rcpp的设置相比，速度有了很大的提高。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

cpp11armadillo: An R package to use the Armadillo C++ library

This article introduces ‘cpp11armadillo’, an R package that integrates the highly efficient Armadillo C++ linear algebra library with R through the ‘cpp11’ interface. Designed to offer significant performance improvements for computationally intensive tasks, ‘cpp11armadillo’ simplifies the process of integrating C++ code into R. This package is particularly suited for R users requiring efficient matrix operations, especially in cases where vectorization is not possible. Our benchmarks demonstrate substantial speed gains over native R functions and Rcpp-based setups.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

SoftwareX COMPUTER SCIENCE, SOFTWARE ENGINEERING-

CiteScore

5.50

自引率

2.90%

发文量

184

审稿时长

9 weeks

期刊介绍： SoftwareX aims to acknowledge the impact of software on today''s research practice, and on new scientific discoveries in almost all research domains. SoftwareX also aims to stress the importance of the software developers who are, in part, responsible for this impact. To this end, SoftwareX aims to support publication of research software in such a way that: The software is given a stamp of scientific relevance, and provided with a peer-reviewed recognition of scientific impact; The software developers are given the credits they deserve; The software is citable, allowing traditional metrics of scientific excellence to apply; The academic career paths of software developers are supported rather than hindered; The software is publicly available for inspection, validation, and re-use. Above all, SoftwareX aims to inform researchers about software applications, tools and libraries with a (proven) potential to impact the process of scientific discovery in various domains. The journal is multidisciplinary and accepts submissions from within and across subject domains such as those represented within the broad thematic areas below: Mathematical and Physical Sciences; Environmental Sciences; Medical and Biological Sciences; Humanities, Arts and Social Sciences. Originating from these broad thematic areas, the journal also welcomes submissions of software that works in cross cutting thematic areas, such as citizen science, cybersecurity, digital economy, energy, global resource stewardship, health and wellbeing, etcetera. SoftwareX specifically aims to accept submissions representing domain-independent software that may impact more than one research domain.