R Observatory: Metrics for h2o4gpu version 0.3.3

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

h2o4gpu

0.3.3Package record

Interface to 'H2O4GPU'

0packages depend

2.9Kdownloads / year

0.0%test coverage

0/13flavors OK

Overview

About

Maintained by Navdeep GillCRAN page ↗GitHub ↗Issues ↗Declared funder: H2O.ai

Interface to 'H2O4GPU' https://github.com/h2oai/h2o4gpu, a collection of 'GPU' solvers for machine learning algorithms.

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("h2o4gpu", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("h2oai/h2o4gpu")

Development version from h2oai/h2o4gpu. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-h2o4gpu

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-h2o4gpu

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-h2o4gpu

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13NOTE

Check messages

NOTERd filesr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-x86_64, r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64, r-patched-linux-x86_64, r-release-linux-x86_64, r-release-macos-arm64, r-release-macos-x86_64, r-release-windows-x86_64

checkRd: (-1) h2o4gpu.gradient_boosting_classifier.Rd:62: Lost braces; missing escapes or markup?
62 | \item{tree_method}{The tree construction algorithm used in XGBoost Distributed and external memory version only support approximate algorithm. Choices: {‘auto’, ‘exact’, ‘approx’, ‘hist’, ‘gpu_exact’, ‘gpu_hist’} ‘auto’: Use heuristic to choose faster one. - For small to medium dataset, exact greedy will be used. - For very large-dataset, approximate algorithm will be chosen. - Because old behavior is always use exact greedy in single machine, - user will get a message when approximate algorithm is chosen to notify this choice. ‘exact’: Exact greedy algorithm. ‘approx’: Approximate greedy algorithm using sketching and histogram. ‘hist’: Fast histogram optimized approximate greedy algorithm. It uses some performance improvements such as bins caching. ‘gpu_exact’: GPU implementation of exact algorithm. ‘gpu_hist’: GPU implementation of hist algorithm.}
|
...[truncated]...
ee construction algorithm used in XGBoost Distributed and external memory version only support approximate algorithm. Choices: {‘auto’, ‘exact’, ‘approx’, ‘hist’, ‘gpu_exact’, ‘gpu_hist’} ‘auto’: Use heuristic to choose faster one. - For small to medium dataset, exact greedy will be used. - For very large-dataset, approximate algorithm will be chosen. - Because old behavior is always use exact greedy in single machine, - user will get a message when approximate algorithm is chosen to notify this choice. ‘exact’: Exact greedy algorithm. ‘approx’: Approximate greedy algorithm using sketching and histogram. ‘hist’: Fast histogram optimized approximate greedy algorithm. It uses some performance improvements such as bins caching. ‘gpu_exact’: GPU implementation of exact algorithm. ‘gpu_hist’: GPU implementation of hist algorithm.}
| ^

NOTER code for possible problemsr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-x86_64

Found calls to structure() using deprecated special names:
  h2o4gpu/tests/testthat/helper-utils.R (.Dim: 1)
'.Dim' should be changed to 'dim'.

CRAN check page ↗

Slowest check: 2.9 min · r-release-windows-x86_64

Status changes

NOTE13 NOTENow
NOTE14 NOTE2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 0.3.3

READMEYes · 591 wordsVignettesYes · 1 · staticNEWSYes · 100% structured · does not mention 0.3.3Citation fileNo

Help pages: 15 (1 internal)includes a package overview page
Examples that run: 0%4 never run
Exported functions with examples: 0%
Documented parameters: 100%
Return-value docs: 0%
Help pages citing references: 0%

Vignettes (1)

H2O4GPU: Machine Learning with GPUs in R HTML

How these are measured

Downloads

2.9K

CRAN downloads in the past year

Rank #15,459 · ~8/day · ~246/mo

Releases R versions

Daily download trend is not available in this view yet.

31830 days

77990 days

2.9K1 year

Compare downloads with other packages →

Also on62 r2u5 autocran

How downloads are counted

Repository

h2oai/h2o4gpu ↗Organization: h2oai

468Stars

96Forks

146Open issues

12Open PRs

8Releases

2,301Commits

31Commit identities

gpuglmpythoncudac-plus-pluscpulassoelastic-net

License file reads as Apache-2.0 · 2,301 commits · Last activity 2026-10-16 · 0% stars, 30d

Responsiveness

How these are sampled

PRs merged (all time): 83%
Median days to close, 50 most recently updated closed issues: 166
Median days to close, 50 most recently updated closed PRs: 4

Stars over time

2025-08-08 · 4632026-09-29 · 468

How these are measured

PracticesBeta

8 development-tooling and community-health practices detected across 5 families in the upstream repository

Checks run against github.com/h2oai/h2o4gpu on 2026-10-11.

Continuous integration (1)

GitHub Actions

Governance and community (4)

Code of conductContributing guideIssue templatesPR template

Docs source (1)

GitHub Pages site last deployed 2017-08-22

Reproducibility and dev environment (1)

Makefile

Show all practicesHide 1 practice

Git structural (1)

Submodules

How this is detected·Detection ruleset v3 (2026-09-26)

AI coding toolsBeta

This repository shows signs of AI coding tools.

Claude Codefirst seen 2026-06-10
Seen in the repository: CLAUDE.md
Commits: at least 26 crediting it in the message

Models named in its commits

Claude Opus 4.826 commits · Jun to Jul 2026

Counts are commits, not lines of code. Commits by a tool's accounts count once across all of its accounts. Commits crediting it are the largest count among its credit lines, a minimum.How this is detected·Detection ruleset v4 (updated 2026-09-27)

Dependencies

Declared dependencies

5 external dependencies (excludes base and recommended)

Installing h2o4gpu adds 11 packages (8 with compiled code, 5.8 MB of source tarballs). Heaviest: Rcpp 1.8 MB, reticulate 1.6 MB, jsonlite 1.0 MB.

Depends (1)

R >= 3.1

Imports (3)

utilsmagrittr reticulate

LinkingTo (0)

none

Suggests (4)

testthat knitr rmarkdownMatrix

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

How these are counted

Code & Tests

People & History

People (5)

Navdeep Gill

Author, Maintainer since 0.3.3 (2021)

Erin LeDell

Author

Vladimir Ovsyannikov

Author · added in 0.3.3

Yuan Tang

Author

H2O.ai

Copyright holder, Funder

Previously maintained by Yuan Tang (0.2.0).

Releases (2)

Pick two releases to compare their code metrics.

R
R 4.6.0 released · 2026-04-24
R
R 4.5.0 released · 2025-04-11
R
R 4.4.0 released · 2024-04-24
R
R 4.3.0 released · 2023-04-21
R
R 4.2.0 released · 2022-04-22
0.3.3Latest
record
2021-05-18 · current release · diff ↗
R
R 4.1.0 released · 2021-05-18
R
R 4.0.0 released · 2020-04-24
R
R 3.6.0 released · 2019-04-26
R
R 3.5.0 released · 2018-04-23
0.2.0
record
2018-03-23
R
R 3.4.0 released · 2017-04-21

Package metadata

First published: 2018-03-23
Total releases: 2 / 8 yrs
License: Apache License 2.0 OSI
Minimum R: ≥ 3.1
Download size: 45 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("h2o4gpu")

Format

Gill, N., H2O.ai, LeDell, E., Ovsyannikov, V., & Tang, Y. (2021). h2o4gpu: Interface to 'H2O4GPU' (Version 0.3.3) [Computer software]. https://doi.org/10.32614/CRAN.package.h2o4gpu

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for h2o4gpu version 0.3.3 [Data set]. HJJB, LLC. Data release v2026-10-18. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-18, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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