https://github.com/wlandau/fbseqcuda
CUDA-accelerated backend of fbseq for the MCMC.
https://github.com/wlandau/fbseqcuda
Last synced: about 1 month ago
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CUDA-accelerated backend of fbseq for the MCMC.
- Host: GitHub
- URL: https://github.com/wlandau/fbseqcuda
- Owner: wlandau
- Created: 2015-10-26T17:07:49.000Z (over 9 years ago)
- Default Branch: main
- Last Pushed: 2020-10-27T16:17:56.000Z (over 4 years ago)
- Last Synced: 2025-02-14T13:15:38.060Z (3 months ago)
- Language: C
- Homepage:
- Size: 162 KB
- Stars: 3
- Watchers: 6
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
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# Purpose
The [`fbseqCUDA` package](https://github.com/wlandau/fbseqCUDA) is an internal backend of [`fbseq` package](https://github.com/wlandau/fbseq) that runs the Markov chain Monte Carlo (MCMC) procedure behind the scenes. It is implemented with [CUDA](http://www.nvidia.com/object/cuda_home_new.html) for acceleration with parallel computing. For installation, CUDA must be installed. To use [`fbseqCUDA` package](https://github.com/wlandau/fbseqCUDA) in an MCMC, [`fbseq` package](https://github.com/wlandau/fbseq) must be installed, and a CUDA-capable general-purpose graphics processing unit (GPU) must be installed on your machine.
# System requirements
- The R version and R packages listed in the "Depends", "Imports", and "Suggests" fields of the "package's [DESCRIPTION](https://github.com/wlandau/fbseqCUDA/blob/master/DESCRIPTION) file.
- A [CUDA](http://www.nvidia.com/object/cuda_home_new.html)-capable [NVIDIA graphics processing unit (GPU)](https://developer.nvidia.com/cuda-gpus) with compute capability 2.0 or greater.
- [CUDA](http://www.nvidia.com/object/cuda_home_new.html) version 6.0 or greater. More information about CUDA is available through [NVIDIA](http://www.nvidia.com/).
- Optional: the code uses double precision values for computation, so GPUs that natively support double precision will be much faster than ones that do not.
# Installation
## Option 1: install a stable release (recommended).
Navigate to a [list of stable releases](https://github.com/wlandau/fbseqCUDA/releases) on the project's [GitHub page](https://github.com/wlandau/fbseqCUDA). Download the desired `tar.gz` bundle, then install it either with `install.packages(..., repos = NULL, type="source")` from within R `R CMD INSTALL` from the Unix/Linux command line.
## Option 2: use `install_github` to install the development version.
For this option, you need the `devtools` package, available from CRAN or GitHub. Open R and run
```
library(devtools)
install_github("wlandau/fbseqCUDA")
```
## Option 3: build the development version from the source.
Open a command line program such as Terminal in Mac/Linux and enter the following commands.
```
git clone [email protected]:wlandau/fbseqCUDA.git
R CMD build fbseqCUDA
R CMD INSTALL ...
```
where `...` is replaced by the name of the tarball produced by `R CMD build`.
## Troubleshooting
If CUDA is not found, open `fbseqCUDA/src/Makevars` in a text editor. The top line reads
```
CUDA_HOME = /usr/local/cuda
```
but this may not be correct for your system. Replace `/usr/local/cuda` with the correct path to the installation of CUDA on your computer.