R-universe search: hpc

mllg

batchtools:Tools for Computation on Batch Systems

As a successor of the packages 'BatchJobs' and 'BatchExperiments', this package provides a parallel implementation of the Map function for high performance computing systems managed by schedulers 'IBM Spectrum LSF' (<https://www.ibm.com/products/hpc-workload-management>), 'OpenLava' (<https://www.openlava.org/>), 'Univa Grid Engine'/'Oracle Grid Engine' (<https://www.univa.com/>), 'Slurm' (<https://slurm.schedmd.com/>), 'TORQUE/PBS' (<https://adaptivecomputing.com/cherry-services/torque-resource-manager/>), or 'Docker Swarm' (<https://docs.docker.com/engine/swarm/>). A multicore and socket mode allow the parallelization on a local machines, and multiple machines can be hooked up via SSH to create a makeshift cluster. Moreover, the package provides an abstraction mechanism to define large-scale computer experiments in a well-organized and reproducible way.

Maintained by Michel Lang. Last updated 2 years ago.

batchexperiments batchjobs docker-swarm high-performance-computing hpc hpc-clusters lsf openlava parallel-computing reproducibility sge slurm torque

19.0 match 175 stars 11.39 score 772 scripts 14 dependents

wrathematics

float:32-Bit Floats

R comes with a suite of utilities for linear algebra with "numeric" (double precision) vectors/matrices. However, sometimes single precision (or less!) is more than enough for a particular task. This package extends R's linear algebra facilities to include 32-bit float (single precision) data. Float vectors/matrices have half the precision of their "numeric"-type counterparts but are generally faster to numerically operate on, for a performance vs accuracy trade-off. The internal representation is an S4 class, which allows us to keep the syntax identical to that of base R's. Interaction between floats and base types for binary operators is generally possible; in these cases, type promotion always defaults to the higher precision. The package ships with copies of the single precision 'BLAS' and 'LAPACK', which are automatically built in the event they are not available on the system.

Maintained by Drew Schmidt. Last updated 6 days ago.

float-matrix hpc linear-algebra matrix fortran openblas openmp

11.0 match 46 stars 10.53 score 228 scripts 42 dependents

philchalmers

SimDesign:Structure for Organizing Monte Carlo Simulation Designs

Provides tools to safely and efficiently organize and execute Monte Carlo simulation experiments in R. The package controls the structure and back-end of Monte Carlo simulation experiments by utilizing a generate-analyse-summarise workflow. The workflow safeguards against common simulation coding issues, such as automatically re-simulating non-convergent results, prevents inadvertently overwriting simulation files, catches error and warning messages during execution, implicitly supports parallel processing with high-quality random number generation, and provides tools for managing high-performance computing (HPC) array jobs submitted to schedulers such as SLURM. For a pedagogical introduction to the package see Sigal and Chalmers (2016) <doi:10.1080/10691898.2016.1246953>. For a more in-depth overview of the package and its design philosophy see Chalmers and Adkins (2020) <doi:10.20982/tqmp.16.4.p248>.

Maintained by Phil Chalmers. Last updated 5 days ago.

monte-carlo-simulation simulation simulation-framework

7.2 match 62 stars 13.35 score 253 scripts 46 dependents

uscbiostats

slurmR:A Lightweight Wrapper for 'Slurm'

'Slurm', Simple Linux Utility for Resource Management <https://slurm.schedmd.com/>, is a popular 'Linux' based software used to schedule jobs in 'HPC' (High Performance Computing) clusters. This R package provides a specialized lightweight wrapper of 'Slurm' with a syntax similar to that found in the 'parallel' R package. The package also includes a method for creating socket cluster objects spanning multiple nodes that can be used with the 'parallel' package.

Maintained by George Vega Yon. Last updated 1 years ago.

bioinformatics hpc slurm

11.5 match 59 stars 8.06 score 216 scripts 1 dependents

jcrodriguez1989

rco:The R Code Optimizer

Automatically apply different strategies to optimize R code. 'rco' functions take R code as input, and returns R code as output.

Maintained by Juan Cruz Rodriguez. Last updated 4 months ago.

compiler fast gcc hpc optimization optimizer

11.0 match 82 stars 6.73 score

henrikbengtsson

aroma.affymetrix:Analysis of Large Affymetrix Microarray Data Sets

A cross-platform R framework that facilitates processing of any number of Affymetrix microarray samples regardless of computer system. The only parameter that limits the number of chips that can be processed is the amount of available disk space. The Aroma Framework has successfully been used in studies to process tens of thousands of arrays. This package has actively been used since 2006.

Maintained by Henrik Bengtsson. Last updated 1 years ago.

infrastructure proprietaryplatforms exonarray microarray onechannel gui dataimport datarepresentation preprocessing qualitycontrol visualization reportwriting acgh copynumbervariants differentialexpression geneexpression snp transcription affymetrix analysis copy-number dna expression hpc large-scale notebook reproducibility rna

11.0 match 10 stars 5.79 score 112 scripts 3 dependents

miraisolutions

rTRNG:Advanced and Parallel Random Number Generation via 'TRNG'

Embeds sources and headers from Tina's Random Number Generator ('TRNG') C++ library. Exposes some functionality for easier access, testing and benchmarking into R. Provides examples of how to use parallel RNG with 'RcppParallel'. The methods and techniques behind 'TRNG' are illustrated in the package vignettes and examples. Full documentation is available in Bauke (2021) <https://github.com/rabauke/trng4/blob/v4.23.1/doc/trng.pdf>.

Maintained by Riccardo Porreca. Last updated 1 years ago.

hpc parallel rcpp trng cpp

11.0 match 19 stars 5.63 score 15 scripts

laplacesdemonr

LaplacesDemon:Complete Environment for Bayesian Inference

Provides a complete environment for Bayesian inference using a variety of different samplers (see ?LaplacesDemon for an overview).

Maintained by Henrik Singmann. Last updated 12 months ago.

4.5 match 93 stars 13.45 score 1.8k scripts 60 dependents

henrikbengtsson

port4me:Get the Same, Personal, Free 'TCP' Port over and over

An R implementation of the cross-platform, language-independent "port4me" algorithm (<https://github.com/HenrikBengtsson/port4me>), which (1) finds a free Transmission Control Protocol ('TCP') port in [1024,65535] that the user can open, (2) is designed to work in multi-user environments, (3), gives different users, different ports, (4) gives the user the same port over time with high probability, (5) gives different ports for different software tools, and (6) requires no configuration.

Maintained by Henrik Bengtsson. Last updated 1 years ago.

bash cli high-performance-computing hpc multi-tenant multi-user port pypi-package python r-language r-programming tcp utility

11.0 match 13 stars 5.11 score 5 scripts

mlr-org

mlr3batchmark:Batch Experiments for 'mlr3'

Extends the 'mlr3' package with a connector to the package 'batchtools'. This allows to run large-scale benchmark experiments on scheduled high-performance computing clusters.

Maintained by Marc Becker. Last updated 1 years ago.

batchtools cluster-computing high-performance-computing hpc mlr3

11.0 match 5 stars 4.85 score 57 scripts

snoweye

pbdMPI:R Interface to MPI for HPC Clusters (Programming with Big Data Project)

A simplified, efficient, interface to MPI for HPC clusters. It is a derivation and rethinking of the Rmpi package. pbdMPI embraces the prevalent parallel programming style on HPC clusters. Beyond the interface, a collection of functions for global work with distributed data and resource-independent RNG reproducibility is included. It is based on S4 classes and methods.

Maintained by Wei-Chen Chen. Last updated 6 months ago.

openmpi

5.1 match 2 stars 7.11 score 179 scripts 3 dependents

mschubert

clustermq:Evaluate Function Calls on HPC Schedulers (LSF, SGE, SLURM, PBS/Torque)

Evaluate arbitrary function calls using workers on HPC schedulers in single line of code. All processing is done on the network without accessing the file system. Remote schedulers are supported via SSH.

Maintained by Michael Schubert. Last updated 24 days ago.

cluster high-performance-computing lsf sge slurm ssh zeromq3 cpp

3.3 match 149 stars 10.23 score 253 scripts

cran

bnlearn:Bayesian Network Structure Learning, Parameter Learning and Inference

Bayesian network structure learning, parameter learning and inference. This package implements constraint-based (PC, GS, IAMB, Inter-IAMB, Fast-IAMB, MMPC, Hiton-PC, HPC), pairwise (ARACNE and Chow-Liu), score-based (Hill-Climbing and Tabu Search) and hybrid (MMHC, RSMAX2, H2PC) structure learning algorithms for discrete, Gaussian and conditional Gaussian networks, along with many score functions and conditional independence tests. The Naive Bayes and the Tree-Augmented Naive Bayes (TAN) classifiers are also implemented. Some utility functions (model comparison and manipulation, random data generation, arc orientation testing, simple and advanced plots) are included, as well as support for parameter estimation (maximum likelihood and Bayesian) and inference, conditional probability queries, cross-validation, bootstrap and model averaging. Development snapshots with the latest bugfixes are available from <https://www.bnlearn.com/>.

Maintained by Marco Scutari. Last updated 2 months ago.

openblas

3.8 match 57 stars 7.72 score 32 dependents

topepo

AppliedPredictiveModeling:Functions and Data Sets for 'Applied Predictive Modeling'

A few functions and several data set for the Springer book 'Applied Predictive Modeling'.

Maintained by Max Kuhn. Last updated 2 years ago.

3.8 match 37 stars 6.89 score 1.2k scripts

mrc-ide

didehpc:DIDE HPC Support

Previous DIDE HPC support. Don't use this, use hipercow instead.

Maintained by Rich FitzJohn. Last updated 4 months ago.

cluster infrastructure

3.9 match 10 stars 3.94 score 58 scripts

dkaschek

dMod:Dynamic Modeling and Parameter Estimation in ODE Models

The framework provides functions to generate ODEs of reaction networks, parameter transformations, observation functions, residual functions, etc. The framework follows the paradigm that derivative information should be used for optimization whenever possible. Therefore, all major functions produce and can handle expressions for symbolic derivatives.

Maintained by Daniel Kaschek. Last updated 9 days ago.

1.7 match 20 stars 8.35 score 251 scripts

wojcieko

bhmbasket:Bayesian Hierarchical Models for Basket Trials

Provides functions for the evaluation of basket trial designs with binary endpoints. Operating characteristics of a basket trial design are assessed by simulating trial data according to scenarios, analyzing the data with Bayesian hierarchical models (BHMs), and assessing decision probabilities on stratum and trial-level based on Go / No-go decision making. The package is build for high flexibility regarding decision rules, number of interim analyses, number of strata, and recruitment. The BHMs proposed by Berry et al. (2013) <doi:10.1177/1740774513497539> and Neuenschwander et al. (2016) <doi:10.1002/pst.1730>, as well as a model that combines both approaches are implemented. Functions are provided to implement Bayesian decision rules as for example proposed by Fisch et al. (2015) <doi:10.1177/2168479014533970>. In addition, posterior point estimates (mean/median) and credible intervals for response rates and some model parameters can be calculated. For simulated trial data, bias and mean squared errors of posterior point estimates for response rates can be provided.

Maintained by Stephan Wojciekowski. Last updated 3 years ago.

jags cpp

4.6 match 1 stars 2.78 score 5 scripts 1 dependents

agandy

simctest:Safe Implementation of Monte Carlo Tests

Algorithms for the implementation and evaluation of Monte Carlo tests, as well as for their use in multiple testing procedures.

Maintained by Axel Gandy. Last updated 4 months ago.

3.3 match 3.85 score 39 scripts 2 dependents

ggseg

ggsegGlasser:Glasser datasets for the ggseg-plotting tool

This is a support package for the ggseg, and ggseg3d packages. It contains the Glasser atlases to plot using functions from those two packages.

Maintained by Athanasia Mo Mowinckel. Last updated 3 years ago.

3.4 match 6 stars 3.44 score 92 scripts

ropensci

nlrx:Setup, Run and Analyze 'NetLogo' Model Simulations from 'R' via 'XML'

Setup, run and analyze 'NetLogo' (<https://ccl.northwestern.edu/netlogo/>) model simulations in 'R'. 'nlrx' experiments use a similar structure as 'NetLogos' Behavior Space experiments. However, 'nlrx' offers more flexibility and additional tools for running and analyzing complex simulation designs and sensitivity analyses. The user defines all information that is needed in an intuitive framework, using class objects. Experiments are submitted from 'R' to 'NetLogo' via 'XML' files that are dynamically written, based on specifications defined by the user. By nesting model calls in future environments, large simulation design with many runs can be executed in parallel. This also enables simulating 'NetLogo' experiments on remote high performance computing machines. In order to use this package, 'Java' and 'NetLogo' (>= 5.3.1) need to be available on the executing system.

Maintained by Sebastian Hanss. Last updated 6 months ago.

agent-based-modeling individual-based-modelling netlogo peer-reviewed

1.3 match 78 stars 8.86 score 195 scripts

mrc-ide

hipercow.windows:DIDE HPC Support for Windows

Driver for using the DIDE windows cluster, via the hipercow package. Typically the user will install that package directly and this once they are requested to.

Maintained by Rich FitzJohn. Last updated 11 days ago.

3.1 match 1 stars 3.32 score 2 scripts

jrmccombs

RHPCBenchmark:Benchmarks for High-Performance Computing Environments

Microbenchmarks for determining the run time performance of aspects of the R programming environment and packages relevant to high-performance computation. The benchmarks are divided into three categories: dense matrix linear algebra kernels, sparse matrix linear algebra kernels, and machine learning functionality.

Maintained by James McCombs. Last updated 8 years ago.

3.3 match 3.02 score 21 scripts

mrcieu

gwasglue:GWAS summary data sources connected to analytical tools

Many tools exist that use GWAS summary data for colocalisation, fine mapping, Mendelian randomization, visualisation, etc. This package is a conduit that connects R packages that can retrieve GWAS summary data to various tools for analysing those data.

Maintained by Gibran Hemani. Last updated 3 years ago.

1.9 match 132 stars 4.78 score 91 scripts

fellstat

ipc:Tools for Message Passing Between Processes

Provides tools for passing messages between R processes. Shiny examples are provided showing how to perform useful tasks such as: updating reactive values from within a future, progress bars for long running async tasks, and interrupting async tasks based on user input.

Maintained by Ian E. Fellows. Last updated 2 years ago.

1.3 match 56 stars 6.50 score 38 scripts 1 dependents

nsaph-software

CausalGPS:Matching on Generalized Propensity Scores with Continuous Exposures

Provides a framework for estimating causal effects of a continuous exposure using observational data, and implementing matching and weighting on the generalized propensity score. Wu, X., Mealli, F., Kioumourtzoglou, M.A., Dominici, F. and Braun, D., 2022. Matching on generalized propensity scores with continuous exposures. Journal of the American Statistical Association, pp.1-29.

Maintained by Naeem Khoshnevis. Last updated 9 months ago.

cpp openmp

1.1 match 24 stars 7.67 score 39 scripts

bioc

h5vc:Managing alignment tallies using a hdf5 backend

This package contains functions to interact with tally data from NGS experiments that is stored in HDF5 files.

Maintained by Paul Theodor Pyl. Last updated 2 months ago.

curl bzip2 xz-utils zlib cpp

1.6 match 4.48 score 2 scripts

bbbruce

nncc:Nearest Neighbors Matching of Case-Control Data

Provides nearest-neighbors matching and analysis of case-control data. Cui, Z., Marder, E. P., Click, E. S., Hoekstra, R. M., & Bruce, B. B. (2022) <doi:10.1097/EDE.0000000000001504>.

Maintained by Beau Bruce. Last updated 1 years ago.

2.5 match 2.70 score 3 scripts

thomaschln

nlpembeds:Natural Language Processing Embeddings

Provides efficient methods to compute co-occurrence matrices, pointwise mutual information (PMI) and singular value decomposition (SVD). In the biomedical and clinical settings, one challenge is the huge size of databases, e.g. when analyzing data of millions of patients over tens of years. To address this, this package provides functions to efficiently compute monthly co-occurrence matrices, which is the computational bottleneck of the analysis, by using the 'RcppAlgos' package and sparse matrices. Furthermore, the functions can be called on 'SQL' databases, enabling the computation of co-occurrence matrices of tens of gigabytes of data, representing millions of patients over tens of years. Partly based on Hong C. (2021) <doi:10.1038/s41746-021-00519-z>.

Maintained by Thomas Charlon. Last updated 24 days ago.

1.3 match 4.98 score

drwolf85

spMC:Continuous-Lag Spatial Markov Chains

A set of functions is provided for 1) the stratum lengths analysis along a chosen direction, 2) fast estimation of continuous lag spatial Markov chains model parameters and probability computing (also for large data sets), 3) transition probability maps and transiograms drawing, 4) simulation methods for categorical random fields. More details on the methodology are discussed in Sartore (2013) <doi:10.32614/RJ-2013-022> and Sartore et al. (2016) <doi:10.1016/j.cageo.2016.06.001>.

Maintained by Luca Sartore. Last updated 2 years ago.

openblas openmp

1.8 match 3 stars 2.92 score 55 scripts

cran

varitas:Variant Calling in Targeted Analysis Sequencing Data

Multi-caller variant analysis pipeline for targeted analysis sequencing (TAS) data. Features a modular, automated workflow that can start with raw reads and produces a user-friendly PDF summary and a spreadsheet containing consensus variant information.

Maintained by Adam Mills. Last updated 4 years ago.

1.7 match 2.30 score

drwolf85

HRTnomaly:Historical, Relational, and Tail Anomaly-Detection Algorithms

The presence of outliers in a dataset can substantially bias the results of statistical analyses. To correct for outliers, micro edits are manually performed on all records. A set of constraints and decision rules is typically used to aid the editing process. However, straightforward decision rules might overlook anomalies arising from disruption of linear relationships. Computationally efficient methods are provided to identify historical, tail, and relational anomalies at the data-entry level (Sartore et al., 2024; <doi:10.6339/24-JDS1136>). A score statistic is developed for each anomaly type, using a distribution-free approach motivated by the Bienaymé-Chebyshev's inequality, and fuzzy logic is used to detect cellwise outliers resulting from different types of anomalies. Each data entry is individually scored and individual scores are combined into a final score to determine anomalous entries. In contrast to fuzzy logic, Bayesian bootstrap and a Bayesian test based on empirical likelihoods are also provided as studied by Sartore et al. (2024; <doi:10.3390/stats7040073>). These algorithms allow for a more nuanced approach to outlier detection, as it can identify outliers at data-entry level which are not obviously distinct from the rest of the data. --- This research was supported in part by the U.S. Department of Agriculture, National Agriculture Statistics Service. The findings and conclusions in this publication are those of the authors and should not be construed to represent any official USDA, or US Government determination or policy.

Maintained by Luca Sartore. Last updated 18 days ago.

openmp

1.8 match 2.00 score

cran

varjmcm:Estimations for the Covariance of Estimated Parameters in Joint Mean-Covariance Models

The goal of the package is to equip the 'jmcm' package (current version 0.2.1) with estimations of the covariance of estimated parameters. Two methods are provided. The first method is to use the inverse of estimated Fisher's information matrix, see M. Pourahmadi (2000) <doi:10.1093/biomet/87.2.425>, M. Maadooliat, M. Pourahmadi and J. Z. Huang (2013) <doi:10.1007/s11222-011-9284-6>, and W. Zhang, C. Leng, C. Tang (2015) <doi:10.1111/rssb.12065>. The second method is bootstrap based, see Liu, R.Y. (1988) <doi:10.1214/aos/1176351062> for reference.

Maintained by Naimin Jing. Last updated 5 years ago.

1.7 match 1.70 score 5 scripts

s-u

OpenCL:Interface allowing R to use OpenCL

This package provides an interface to OpenCL, allowing R to leverage computing power of GPUs and other HPC accelerator devices.

Maintained by Simon Urbanek. Last updated 1 years ago.

0.5 match 15 stars 5.12 score 29 scripts

schnorr

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.

Maintained by Lucas Leandro Nesi. Last updated 5 months ago.

cpp

0.5 match 13 stars 4.94 score 27 scripts

chingchuan-chen

RcppBlaze:'Rcpp' Integration for the 'Blaze' High-Performance 'C++' Math Library

Blaze is an open-source, high-performance 'C++' math library for dense and sparse arithmetic. With its state-of-the-art Smart Expression Template implementation Blaze combines the elegance and ease of use of a domain-specific language with HPC-grade performance, making it one of the most intuitive and fastest 'C++' math libraries available. The 'RcppBlaze' package includes the header files from the 'Blaze' library with disabling some functionalities related to link to the thread and system libraries which make 'RcppBlaze' be a header-only library. Therefore, users do not need to install 'Blaze'.

Maintained by Ching-Chuan Chen. Last updated 10 months ago.

openblas cpp openmp

0.5 match 16 stars 4.86 score 2 scripts 1 dependents

cran

hpcwld:High Performance Cluster Models Based on Kiefer-Wolfowitz Recursion

Probabilistic models describing the behavior of workload and queue on a High Performance Cluster and computing GRID under FIFO service discipline basing on modified Kiefer-Wolfowitz recursion. Also sample data for inter-arrival times, service times, number of cores per task and waiting times of HPC of Karelian Research Centre are included, measurements took place from 06/03/2009 to 02/30/2011. Functions provided to import/export workload traces in Standard Workload Format (swf). Stability condition of the model may be verified either exactly, or approximately. Stability analysis: see Rumyantsev and Morozov (2017) <doi:10.1007/s10479-015-1917-2>, workload recursion: see Rumyantsev (2014) <doi:10.1109/PDCAT.2014.36>.

Maintained by Alexander Rumyantsev. Last updated 3 years ago.

0.5 match 1 stars 1.00 score 10 scripts