Add 12.1 workflow for docker image build

.github/workflows/build-conda-images.yml

@@ -26,7 +26,7 @@ jobs:
     runs-on: ubuntu-22.04
     strategy:
       matrix:
-        cuda_version: ["11.6", "11.7", "11.8", "cpu"]
+        cuda_version: ["11.7", "11.8", "12.1", "cpu"]
     env:
       CUDA_VERSION: ${{ matrix.cuda_version }}
     steps:

common/install_cuda.sh

@@ -85,6 +85,37 @@ function install_118 {
     ldconfig
 }
 
+function install_121 {
+    echo "Installing CUDA 12.1 and cuDNN 8.8 and NCCL 2.17.1"
+    rm -rf /usr/local/cuda-12.1 /usr/local/cuda
+    # install CUDA 12.1.0 in the same container
+    wget -q https://developer.download.nvidia.com/compute/cuda/12.1.0/local_installers/cuda_12.1.0_530.30.02_linux.run
+    chmod +x cuda_12.1.0_530.30.02_linux.run
+    ./cuda_12.1.0_530.30.02_linux.run --toolkit --silent
+    rm -f cuda_12.1.0_530.30.02_linux.run
+    rm -f /usr/local/cuda && ln -s /usr/local/cuda-12.1 /usr/local/cuda
+
+    # cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
+    mkdir tmp_cudnn && cd tmp_cudnn
+    wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/cudnn-linux-x86_64-8.8.1.3_cuda12-archive.tar.xz -O cudnn-linux-x86_64-8.8.1.3_cuda12-archive.tar.xz
+    tar xf cudnn-linux-x86_64-8.8.1.3_cuda12-archive.tar.xz
+    cp -a cudnn-linux-x86_64-8.8.1.3_cuda12-archive/include/* /usr/local/cuda/include/
+    cp -a cudnn-linux-x86_64-8.8.1.3_cuda12-archive/lib/* /usr/local/cuda/lib64/
+    cd ..
+    rm -rf tmp_cudnn
+    ldconfig
+
+    # NCCL license: https://docs.nvidia.com/deeplearning/nccl/#licenses
+    mkdir tmp_nccl && cd tmp_nccl
+    wget -q https://developer.download.nvidia.com/compute/redist/nccl/v2.17.1/nccl_2.17.1-1+cuda12.1_x86_64.txz
+    tar xf nccl_2.17.1-1+cuda12.1_x86_64.txz
+    cp -a nccl_2.17.1-1+cuda12.1_x86_64/include/* /usr/local/cuda/include/
+    cp -a nccl_2.17.1-1+cuda12.1_x86_64/lib/* /usr/local/cuda/lib64/
+    cd ..
+    rm -rf tmp_nccl
+    ldconfig
+}
+
 function prune_116 {
     echo "Pruning CUDA 11.6 and CuDNN"
     #####################################################################################
@@ -178,6 +209,37 @@ function prune_118 {
     rm -rf $CUDA_BASE/libnvvp $CUDA_BASE/nsightee_plugins $CUDA_BASE/nsight-compute-2022.3.0 $CUDA_BASE/nsight-systems-2022.4.2/
 }
 
+function prune_121 {
+  echo "Pruning CUDA 12.1"
+  #####################################################################################
+  # CUDA 12.1 prune static libs
+  #####################################################################################
+    export NVPRUNE="/usr/local/cuda-12.1/bin/nvprune"
+    export CUDA_LIB_DIR="/usr/local/cuda-12.1/lib64"
+
+    export GENCODE="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
+    export GENCODE_CUDNN="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
+
+    if [[ -n "$OVERRIDE_GENCODE" ]]; then
+        export GENCODE=$OVERRIDE_GENCODE
+    fi
+
+    # all CUDA libs except CuDNN and CuBLAS
+    ls $CUDA_LIB_DIR/ | grep "\.a" | grep -v "culibos" | grep -v "cudart" | grep -v "cudnn" | grep -v "cublas" | grep -v "metis"  \
+      | xargs -I {} bash -c \
+                "echo {} && $NVPRUNE $GENCODE $CUDA_LIB_DIR/{} -o $CUDA_LIB_DIR/{}"
+
+    # prune CuDNN and CuBLAS
+    $NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublas_static.a -o $CUDA_LIB_DIR/libcublas_static.a
+    $NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublasLt_static.a -o $CUDA_LIB_DIR/libcublasLt_static.a
+
+    #####################################################################################
+    # CUDA 12.1 prune visual tools
+    #####################################################################################
+    export CUDA_BASE="/usr/local/cuda-12.1/"
+    rm -rf $CUDA_BASE/libnvvp $CUDA_BASE/nsightee_plugins $CUDA_BASE/nsight-compute-2023.1.0 $CUDA_BASE/nsight-systems-2023.1.2/
+}
+
 # idiomatic parameter and option handling in sh
 while test $# -gt 0
 do
@@ -188,6 +250,8 @@ do
 	        ;;
     11.8) install_118; prune_118
 	        ;;
+    12.1) install_121; prune_121
+	        ;;
 	*) echo "bad argument $1"; exit 1
 	   ;;
     esac

conda/Dockerfile

@@ -60,6 +60,10 @@ FROM cuda as cuda11.8
 RUN bash ./install_cuda.sh 11.8
 ENV DESIRED_CUDA=11.8
 
+FROM cuda as cuda12.1
+RUN bash ./install_cuda.sh 12.1
+ENV DESIRE_CUDA=12.1
+
 # Install MNIST test data
 FROM base as mnist
 ADD ./common/install_mnist.sh install_mnist.sh
@@ -69,6 +73,7 @@ FROM base as all_cuda
 COPY --from=cuda11.6  /usr/local/cuda-11.6 /usr/local/cuda-11.6
 COPY --from=cuda11.7  /usr/local/cuda-11.7 /usr/local/cuda-11.7
 COPY --from=cuda11.8  /usr/local/cuda-11.8 /usr/local/cuda-11.8
+COPY --from=cuda12.1  /usr/local/cuda-12.1 /usr/local/cuda-12.1
 
 FROM ${BASE_TARGET} as final
 # Install LLVM

conda/build_all_docker.sh

@@ -4,6 +4,6 @@ set -eou pipefail
 
 TOPDIR=$(git rev-parse --show-toplevel)
 
-for CUDA_VERSION in 11.8 11.7 11.6 cpu; do
+for CUDA_VERSION in 12.1 11.8 11.7 cpu; do
   CUDA_VERSION="${CUDA_VERSION}" conda/build_docker.sh
 done