fc5e23c5c7
This dockerfile creates an image that installs the software stack needed to run both machine learning and non-machine learning applications using the GCN3 gpu model, while also applying patches to the software stack to optimize machine learning applications, as well as APUs, which is the current type of GPU in the GCN3 GPU model. Change-Id: If36c2df1c00c895e27e9d741027fd10c17bf224e Reviewed-on: https://gem5-review.googlesource.com/c/public/gem5/+/29192 Reviewed-by: Matt Sinclair <mattdsinclair@gmail.com> Reviewed-by: Jason Lowe-Power <power.jg@gmail.com> Maintainer: Bobby R. Bruce <bbruce@ucdavis.edu> Tested-by: kokoro <noreply+kokoro@google.com>
gcn3-gpu dockerfile
This dockerfile contains all the dependences necessary to run GPU applications in gem5 using the gcn3 APU model
Building the image
docker build -t <image_name> .
Building gem5 using the image
The following command assumes the gem5 directory is a subdirectory of your current directory
docker run --rm -v $PWD/gem5:/gem5 -w /gem5 <image_name> scons -sQ -j$(nproc) build/GCN3_X86/gem5.opt
Test gem5 using a prebuilt application
wget http://dist.gem5.org/dist/current/test-progs/hip_sample_bins/MatrixTranspose
docker run --rm -v $PWD/MatrixTranspose:/MatrixTranspose -v $PWD/public_gem5:/gem5 -w /gem5 \
<image_name> build/GCN3_X86/gem5.opt configs/example/apu_se.py -n2 --benchmark-root=/ -cMatrixTranspose
Notes
- When using the
-vflag, the path to the input file/directory needs to be the absolute path; symlinks don't work - Currently linking in an AFS volume is not supported, as it uses ACLs instead of owner/group IDs
ToDo
- Add square to gem5-resources github, add directions for building and running an application