В Sun, 16 Feb 2025 13:00:55 +0000 Wolfgang Rolke via R-package-devel <r-package-devel@r-project.org> пишет:
> I am currently working on a project that requires calculations on > large matrices, for example calculating pairwise distances of points > in higher dimensions. How large are the matrices? Are CPU-side calculations (possibly done in special-purpose parallel code written in C/C++/Fortran/Rust) out of question? What are your performance goals? > So my question is, how should I implement a GPU based calculation in > a package that will eventually be acceptable for CRAN? How about OpenCL [1]? Pros: * The 'OpenCL' package is already on CRAN, making it possible to write and run "kernels" straight from R. * Unlike CUDA, OpenCL is an open standard, relatively portable between video card vendors. It is even possible to use a CPU-only "installable client driver" that would (probably very slowly) run the kernels on the processor when no compatible video card is present. Cons: * Additional user setup is required. The OpenCL package will fail to load if the OpenCL runtime is not installed; installing it from source will also require the OpenCL SDK with headers. * Your code will also fail to run if OpenCL cannot find a working "platform", so any examples and tests will need to check for length(oclPlatforms) > 0 [2]. -- Best regards, Ivan [1] https://www.khronos.org/opencl/ [2] https://www.r-project.org/nosvn/R.check/r-release-windows-x86_64/OpenCL-00check.html ______________________________________________ R-package-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-package-devel
