b6852778ff
Add magma build for CUDA 13.0 after almalinux docker is available https://github.com/pytorch/pytorch/issues/159779 Pull Request resolved: https://github.com/pytorch/pytorch/pull/160770 Approved by: https://github.com/atalman Co-authored-by: Andrey Talman <atalman@fb.com> Co-authored-by: Wei Wang <weiwan@nvidia.com>
Magma
This folder contains the scripts and configurations to build magma, statically linked for various versions of CUDA.
Building
Look in the Makefile for available targets to build. To build any target, for example magma-cuda118, run
# Using `docker`
make magma-cuda118
# Using `podman`
DOCKER_CMD=podman make magma-cuda118
This spawns a pytorch/manylinux-cuda<version> docker image, which has the required devtoolset and CUDA versions installed.
Within the docker image, it runs build_magma.sh with the correct environment variables set, which package the necessary files
into a tarball, with the following structure:
.
├── include # header files
├── lib # libmagma.a
├── info
│ ├── licenses # license file
│ └── recipe # build script and patches
More specifically, build_magma.sh copies over the relevant files from the package_files directory depending on the CUDA version.
Outputted binaries should be in the output folder.
Pushing
Packages can be uploaded to an S3 bucket using:
aws s3 cp output/*/magma-cuda*.bz2 <bucket-with-path>
If you do not have upload permissions, please ping @seemethere or @soumith to gain access
New versions
New CUDA versions can be added by creating a new make target with the next desired version. For CUDA version NN.n, the target should be named magma-cudaNNn.
Make sure to edit the appropriate environment variables (e.g., DESIRED_CUDA, CUDA_ARCH_LIST) in the Makefile accordingly. Remember also to check build_magma.sh to ensure the logic for copying over the files remains correct.
New patches can be added by editing Makefile andbuild_magma.sh the same way getrf_nbparam.patch is implemented.