Showing 5 of total 5 results (show query)
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.
33.0 match 2 stars 7.11 score 179 scripts 3 dependents
cran
Rmpi:Interface (Wrapper) to MPI (Message-Passing Interface)
An interface (wrapper) to MPI. It also provides interactive R manager and worker environment.
Maintained by Hao Yu. Last updated 2 months ago.
33.0 match 5 stars 4.76 score 5 dependentssnoweye
pbdSLAP:Programming with Big Data -- Scalable Linear Algebra Packages
Utilizing scalable linear algebra packages mainly including 'BLACS', 'PBLAS', and 'ScaLAPACK' in double precision via 'pbdMPI' based on 'ScaLAPACK' version 2.0.2.
Maintained by Wei-Chen Chen. Last updated 4 months ago.
33.0 match 4.30 score 4 scripts
paciorek
bigGP:Distributed Gaussian Process Calculations
Distributes Gaussian process calculations across nodes in a distributed memory setting, using Rmpi. The bigGP class provides high-level methods for maximum likelihood with normal data, prediction, calculation of uncertainty (i.e., posterior covariance calculations), and simulation of realizations. In addition, bigGP provides an API for basic matrix calculations with distributed covariance matrices, including Cholesky decomposition, back/forwardsolve, crossproduct, and matrix multiplication.
Maintained by Christopher Paciorek. Last updated 2 years ago.
33.0 match 2.02 score 21 scriptssnoweye
pmclust:Parallel Model-Based Clustering using Expectation-Gathering-Maximization Algorithm for Finite Mixture Gaussian Model
Aims to utilize model-based clustering (unsupervised) for high dimensional and ultra large data, especially in a distributed manner. The code employs 'pbdMPI' to perform a expectation-gathering-maximization algorithm for finite mixture Gaussian models. The unstructured dispersion matrices are assumed in the Gaussian models. The implementation is default in the single program multiple data programming model. The code can be executed through 'pbdMPI' and MPI' implementations such as 'OpenMPI' and 'MPICH'. See the High Performance Statistical Computing website <https://snoweye.github.io/hpsc/> for more information, documents and examples.
Maintained by Wei-Chen Chen. Last updated 2 years ago.
0.5 match 5 stars 3.70 score 4 scripts