sst-integration: use self-hosted runner to run image build

.github/workflows/docker-publish.yml

@@ -17,7 +17,7 @@ jobs:
   push_to_registry:
     if: github.repository == 'accel-sim/Dockerfile'
     name: Push Docker image to Docker Hub
-    runs-on: ubuntu-latest
+    runs-on: tgrogers-raid
     steps:
       - name: Check out the repo
         uses: actions/checkout@v4

Dockerfile

@@ -1,4 +1,4 @@
-FROM tgrogers/accel-sim_regress:Ubuntu-22.04-cuda-11.7
+FROM ubuntu:22.04
 
 SHELL ["/bin/bash", "-c"]
 
@@ -9,6 +9,19 @@ ENV CUDA_INSTALL_PATH /usr/local/cuda-11.7
 ENV PTXAS_CUDA_INSTALL_PATH /usr/local/cuda-11.7
 ENV GPUAPPS_ROOT /accel-sim/gpu-app-collection
 
+# Setup GPGPU-Sim dependencies and CUDA 11.7
+RUN apt-get update \
+&& apt-get install -y wget build-essential xutils-dev bison zlib1g-dev flex \
+      libglu1-mesa-dev git g++ libssl-dev libxml2-dev libboost-all-dev git g++ \
+      libxml2-dev vim python-setuptools python3-pip cmake \
+&& apt-get clean \
+&& pip3 install pyyaml plotly psutil \
+&& wget https://developer.download.nvidia.com/compute/cuda/11.7.0/local_installers/cuda_11.7.0_515.43.04_linux.run \
+&& sh cuda_11.7.0_515.43.04_linux.run --silent --toolkit \
+&& rm cuda_11.7.0_515.43.04_linux.run \
+&& rm -rf /usr/local/cuda-11.7/nsight-compute-2022.2.0 \
+&& rm -rf /usr/local/cuda-11.7/nsight-systems-2022.1.3
+
 # Build LLVM 18.1.8
 RUN git clone https://github.com/llvm/llvm-project.git \
 && mkdir llvm-install \