starvz: R-Based Visualization Techniques for Task-Based Applications

Performance analysis workflow that combines the power of the R language (and the tidyverse realm) and many auxiliary tools to provide a consistent, flexible, extensible, fast, and versatile framework for the performance analysis of task-based applications that run on top of the StarPU runtime (with its MPI (Message Passing Interface) layer for multi-node support). Its goal is to provide a fruitful prototypical environment to conduct performance analysis hypothesis-checking for task-based applications that run on heterogeneous (multi-GPU, multi-core) multi-node HPC (High-performance computing) platforms.

Version: 0.4.0
Depends: R (≥ 3.6.0)
Imports: methods, grDevices, stats, utils, magrittr, dplyr, ggplot2, tibble, rlang, tidyr, patchwork, purrr, readr, stringr, yaml, lpSolve, gtools, data.tree, RColorBrewer, zoo, car, arrow (≥ 0.17.0)
LinkingTo: Rcpp, BH
Suggests: testthat
Published: 2020-09-01
Author: Lucas Mello Schnorr ORCID iD [aut, ths], Vinicius Garcia Pinto ORCID iD [aut], Lucas Leandro Nesi ORCID iD [aut, cre], Marcelo Cogo Miletto ORCID iD [aut], Guilherme Alles [ctb], Arnaud Legrand [ctb], Luka Stanisic [ctb], Rémy Drouilhet [ctb]
Maintainer: Lucas Leandro Nesi <lucas.nesi at>
License: GPL-3
NeedsCompilation: yes
SystemRequirements: C++, bash, StarPU
CRAN checks: starvz results


Reference manual: starvz.pdf
Package source: starvz_0.4.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: starvz_0.4.0.tgz, r-oldrel: starvz_0.4.0.tgz


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