recipe bioconductor-gpumagic

An openCL compiler with the capacity to compile R functions and run the code on GPU






The package aims to help users write openCL code with little or no effort. It is able to compile an user-defined R function and run it on a device such as a CPU or a GPU. The user can also write and run their openCL code directly by calling .kernel function.

package bioconductor-gpumagic

(downloads) docker_bioconductor-gpumagic



depends bioconductor-biocgenerics:


depends bioconductor-biocgenerics:


depends libblas:


depends libgcc-ng:


depends liblapack:


depends libstdcxx-ng:


depends ocl-icd:


depends r-base:


depends r-deriv:

depends r-desctools:

depends r-digest:

depends r-pryr:

depends r-rcpp:

depends r-stringr:



You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install bioconductor-gpumagic

and update with::

   mamba update bioconductor-gpumagic

To create a new environment, run:

mamba create --name myenvname bioconductor-gpumagic

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

   docker pull<tag>

(see `bioconductor-gpumagic/tags`_ for valid values for ``<tag>``)

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