website: update GCN3 webpage
This commit makes two major updates to the GCN3 webpage:
1. Removes the majority of the examples and instead points to the
examples in gem5-resources, which are both more up-to-date and
more numerous. This eliminates the need to update documentation
in two places, and should reduce confusion moving forward.
2. Updates the GCN3 information to reflect that ROCm 4.0 is now
supported instead of ROCm 1.6, as well as removing the ROCm libraries
that are no longer needed with ROCm 4.0.
Change-Id: I5421f3c1982c01d3b346cc91ec404e186345e4d6
Reviewed-on: https://gem5-review.googlesource.com/c/public/gem5-website/+/50907
Reviewed-by: Jason Lowe-Power <power.jg@gmail.com>
Reviewed-by: Matthew Poremba <matthew.poremba@amd.com>
Maintainer: Jason Lowe-Power <power.jg@gmail.com>
Tested-by: Jason Lowe-Power <power.jg@gmail.com>
diff --git a/_pages/documentation/general_docs/gpu_models/gcn3.md b/_pages/documentation/general_docs/gpu_models/gcn3.md
index 7ca36bf..76e300f 100644
--- a/_pages/documentation/general_docs/gpu_models/gcn3.md
+++ b/_pages/documentation/general_docs/gpu_models/gcn3.md
@@ -18,13 +18,11 @@
## **Using the model**
-Currently, the GCN3 GPU model in gem5 is only supported on the develop branch.
-Thus, you should use the develop branch when running the GCN3 model.
-We expect this support to be integrated into the gem5-v21.0 release.
+Currently, the GCN3 GPU model in gem5 is supported on the stable and develop branch.
The [gem5 repository](https://gem5.goooglesource.com/public/gem5) comes with a dockerfile located in `util/dockerfiles/gcn-gpu/`. This dockerfile contains the drivers and libraries needed to run the GPU model. A pre-built version of the docker image is hosted at `gcr.io/gem5-test/gcn-gpu`.
-The [gem5-resources repository](https://gem5.googlesource.com/public/gem5-resources/) also comes with a sample application (square) that can be used to verify that the model runs correctly.
+The [gem5-resources repository](https://gem5.googlesource.com/public/gem5-resources/) also comes with a number of sample applications that can be used to verify that the model runs correctly. We recommend users start with [square](https://resources.gem5.org/resources/square), as it is a simple, heavily tested application that should run relatively quickly.
#### Using the image
The docker image can either be built or pulled from gcr.io
@@ -42,27 +40,10 @@
You can also put `gcr.io/gem5-test/gcn-gpu` as the image in the docker run command without pulling beforehand and it will be pulled automatically.
#### 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
-```
+See square in [gem5 resources](https://resources.gem5.org/resources/square) for an example of how to build gem5 in the docker. Note: these directions assume you are pulling the latest image automatically.
-#### Building a GPU application using the image
-The following command assumes the gem5-resources directory is a subdirectory of your current directory
-```
-docker run --rm -v $PWD/gem5-resources:$PWD/gem5-resources -w $PWD/gem5-resources/src/square <image_name> make gfx8-apu
-```
-
-#### Running the sample application
-The following command assumes that gem5 and gem5-resources are subdirectories of your current directory
-
-```
-docker run --rm -v $PWD/gem5:/gem5 -v $PWD/gem5-resources:/gem5-resources \
- -w /gem5 <image_name> \
- build/GCN3_X86/gem5.opt configs/example/apu_se.py -n3 \
- --benchmark-root=/gem5-resources/src/gpu/square/bin \
- -c square
-```
+#### Building & running a GPU application using the image
+See [gem5 resources](https://resources.gem5.org/) for examples of how to build and run GPU applications in the docker.
## **ROCm**
@@ -82,7 +63,7 @@
The `src/dev/hsa/kfd_ioctl.h` header must match the `kfd_ioctl.h` header that comes with ROCt. The emulated driver relies on that file to interpret the `ioctl()` codes the thunk uses.
#### ROCm toolchain and software stack
-The GCN3 model supports ROCm version 1.6
+The GCN3 model supports ROCm version 4.0.
The following ROCm components are required:
* [Heterogeneous Compute Compiler (HCC)](https://github.com/RadeonOpenCompute/hcc)
@@ -93,7 +74,6 @@
The following additional components are used to build and run machine learning programs:
* [hipBLAS](https://github.com/ROCmSoftwarePlatform/hipBLAS/)
* [rocBLAS](https://github.com/ROCmSoftwarePlatform/rocBLAS/)
-* [MIOpenGEMM](https://github.com/ROCmSoftwarePlatform/MIOpenGEMM/)
* [MIOpen](https://github.com/ROCmSoftwarePlatform/MIOpen/)
* [rocm-cmake](https://github.com/RadeonOpenCompute/rocm-cmake/)
