remove CUDA 11.6 builds (#1366)

* remove CUDA 11.6 builds

* remove more 11.6 builds

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

@@ -28,7 +28,7 @@ jobs:
     runs-on: ubuntu-22.04
     strategy:
       matrix:
-        cuda_version: ["11.8", "11.7", "11.6"]
+        cuda_version: ["11.8", "11.7"]
     env:
       GPU_ARCH_TYPE: cuda
       GPU_ARCH_VERSION: ${{ matrix.cuda_version }}

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

@@ -30,7 +30,7 @@ jobs:
     runs-on: ubuntu-22.04
     strategy:
       matrix:
-        cuda_version: ["11.8", "11.7", "11.6"]
+        cuda_version: ["11.8", "11.7"]
     env:
       GPU_ARCH_TYPE: cuda
       GPU_ARCH_VERSION: ${{ matrix.cuda_version }}

CUDA_UPGRADE_GUIDE.MD

@@ -9,8 +9,8 @@ Here is the supported matrix for CUDA and CUDNN
 
 | CUDA | CUDNN | additional details |
 | --- | --- | --- |
-| 11.6 | 8.3.2.44 | Stable CUDA Release |
-| 11.7 | 8.5.0.96 | Latest CUDA Release |
+| 11.7 | 8.5.0.96 | Stable CUDA Release |
+| 11.8 | 8.7.0.84 | Latest CUDA Release |
 
 
 ### B. Check the package availability

common/install_cuda.sh

@@ -2,27 +2,6 @@
 
 set -ex
 
-function install_116 {
-    echo "Installing CUDA 11.6 and CuDNN 8.3"
-    rm -rf /usr/local/cuda-11.6 /usr/local/cuda
-    # install CUDA 11.6.2 in the same container
-    wget -q https://developer.download.nvidia.com/compute/cuda/11.6.2/local_installers/cuda_11.6.2_510.47.03_linux.run
-    chmod +x cuda_11.6.2_510.47.03_linux.run
-    ./cuda_11.6.2_510.47.03_linux.run --toolkit --silent
-    rm -f cuda_11.6.2_510.47.03_linux.run
-    rm -f /usr/local/cuda && ln -s /usr/local/cuda-11.6 /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/redist/cudnn/v8.3.2/local_installers/11.5/cudnn-linux-x86_64-8.3.2.44_cuda11.5-archive.tar.xz -O cudnn-linux-x86_64-8.3.2.44_cuda11.5-archive.tar.xz
-    tar xf cudnn-linux-x86_64-8.3.2.44_cuda11.5-archive.tar.xz
-    cp -a cudnn-linux-x86_64-8.3.2.44_cuda11.5-archive/include/* /usr/local/cuda/include/
-    cp -a cudnn-linux-x86_64-8.3.2.44_cuda11.5-archive/lib/* /usr/local/cuda/lib64/
-    cd ..
-    rm -rf tmp_cudnn
-    ldconfig
-}
-
 function install_117 {
     echo "Installing CUDA 11.7 and CuDNN 8.5 and NCCL 2.14"
     rm -rf /usr/local/cuda-11.7 /usr/local/cuda
@@ -116,37 +95,6 @@ function install_121 {
     ldconfig
 }
 
-function prune_116 {
-    echo "Pruning CUDA 11.6 and CuDNN"
-    #####################################################################################
-    # CUDA 11.6 prune static libs
-    #####################################################################################
-    export NVPRUNE="/usr/local/cuda-11.6/bin/nvprune"
-    export CUDA_LIB_DIR="/usr/local/cuda-11.6/lib64"
-
-    export GENCODE="-gencode arch=compute_35,code=sm_35 -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"
-    export GENCODE_CUDNN="-gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -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"
-
-    if [[ -n "$OVERRIDE_GENCODE" ]]; then
-        export GENCODE=$OVERRIDE_GENCODE
-    fi
-
-    # all CUDA libs except CuDNN and CuBLAS (cudnn and cublas need arch 3.7 included)
-    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 11.6 prune visual tools
-    #####################################################################################
-    export CUDA_BASE="/usr/local/cuda-11.6/"
-    rm -rf $CUDA_BASE/libnvvp $CUDA_BASE/nsightee_plugins $CUDA_BASE/nsight-compute-2022.1.1 $CUDA_BASE/nsight-systems-2021.5.2
-}
-
 function prune_117 {
     echo "Pruning CUDA 11.7 and CuDNN"
     #####################################################################################
@@ -172,7 +120,7 @@ function prune_117 {
     $NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublasLt_static.a -o $CUDA_LIB_DIR/libcublasLt_static.a
 
     #####################################################################################
-    # CUDA 11.6 prune visual tools
+    # CUDA 11.7 prune visual tools
     #####################################################################################
     export CUDA_BASE="/usr/local/cuda-11.7/"
     rm -rf $CUDA_BASE/libnvvp $CUDA_BASE/nsightee_plugins $CUDA_BASE/nsight-compute-2022.2.0 $CUDA_BASE/nsight-systems-2022.1.3
@@ -244,8 +192,6 @@ function prune_121 {
 while test $# -gt 0
 do
     case "$1" in
-    11.6) install_116; prune_116
-	        ;;
     11.7) install_117; prune_117
 	        ;;
     11.8) install_118; prune_118

conda/Dockerfile

@@ -48,10 +48,6 @@ ENV CUDA_HOME=/usr/local/cuda-${CUDA_VERSION}
 # Make things in our path by default
 ENV PATH=/usr/local/cuda-${CUDA_VERSION}/bin:$PATH
 
-FROM cuda as cuda11.6
-RUN bash ./install_cuda.sh 11.6
-ENV DESIRED_CUDA=11.6
-
 FROM cuda as cuda11.7
 RUN bash ./install_cuda.sh 11.7
 ENV DESIRED_CUDA=11.7
@@ -70,7 +66,6 @@ ADD ./common/install_mnist.sh install_mnist.sh
 RUN bash ./install_mnist.sh
 
 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

conda/build_pytorch.sh

@@ -271,9 +271,6 @@ else
     elif [[ "$desired_cuda" == "11.7" ]]; then
         export CONDA_CUDATOOLKIT_CONSTRAINT="    - pytorch-cuda >=11.7,<11.8 # [not osx]"
         export MAGMA_PACKAGE="    - magma-cuda117 # [not osx and not win]"
-    elif [[ "$desired_cuda" == "11.6" ]]; then
-        export CONDA_CUDATOOLKIT_CONSTRAINT="    - pytorch-cuda >=11.6,<11.7 # [not osx]"
-        export MAGMA_PACKAGE="    - magma-cuda116 # [not osx and not win]"
     else
         echo "unhandled desired_cuda: $desired_cuda"
         exit 1

conda/pytorch-cuda/conda_build_config.yaml

@@ -1,5 +1,4 @@
 version:
-    - 11.6
     - 11.7
     - 11.8
 target_platform:

conda/pytorch-cuda/meta.yaml

@@ -12,14 +12,6 @@
 # https://conda.anaconda.org/pytorch/noarch/
 # https://conda.anaconda.org/pytorch/noarch/repodata.json
 {% set build = 3 %}
-{% set cuda_constraints=">=11.6,<11.7" %}
-{% set libcufft_constraints=">=10.7.0.55,<10.7.2.50" %}
-{% set libcublas_constraints=">=11.8.1.74,<11.10.1.25" %}
-{% set libcusolver_constraints=">=11.3.2.55,<11.3.5.50" %}
-{% set libcusparse_constraints=">=11.7.1.55,<11.7.3.50" %}
-{% set libnpp_constraints=">=11.6.0.55,<11.7.3.21" %}
-{% set libnvjpeg_constraints=">=11.6.0.55,<11.7.2.34" %}
-{% if version == '11.7' %}
 {% set cuda_constraints=">=11.7,<11.8" %}
 {% set libcufft_constraints=">=10.7.2.50,<10.9.0.58" %}
 {% set libcublas_constraints=">=11.10.1.25,<11.11.3.6" %}

conda/pytorch-nightly/bld.bat

@@ -21,12 +21,6 @@ set CUDA_PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v%desired_cuda%
 set CUDA_BIN_PATH=%CUDA_PATH%\bin
 set TORCH_NVCC_FLAGS=-Xfatbin -compress-all
 set TORCH_CUDA_ARCH_LIST=3.7+PTX;5.0;6.0;6.1;7.0;7.5;8.0;8.6
-if "%desired_cuda%" == "11.5" (
-    set TORCH_NVCC_FLAGS=-Xfatbin -compress-all --threads 2
-)
-if "%desired_cuda%" == "11.6" (
-    set TORCH_NVCC_FLAGS=-Xfatbin -compress-all --threads 2
-)
 if "%desired_cuda%" == "11.7" (
     set TORCH_NVCC_FLAGS=-Xfatbin -compress-all --threads 2
 )

conda/pytorch-nightly/build.sh

@@ -55,14 +55,7 @@ if [[ -n "$build_with_cuda" ]]; then
     TORCH_CUDA_ARCH_LIST="3.7+PTX;5.0"
     export USE_STATIC_CUDNN=1 # links cudnn statically (driven by tools/setup_helpers/cudnn.py)
 
-    if [[ $CUDA_VERSION == 11.6* ]]; then
-        TORCH_CUDA_ARCH_LIST="$TORCH_CUDA_ARCH_LIST;6.0;6.1;7.0;7.5;8.0;8.6"
-        #for cuda 11.5 we use cudnn 8.3.2.44 https://docs.nvidia.com/deeplearning/cudnn/release-notes/rel_8.html
-        #which does not have single static libcudnn_static.a deliverable to link with
-        export USE_STATIC_CUDNN=0
-        #for cuda 11.5 include all dynamic loading libraries
-        DEPS_LIST=(/usr/local/cuda/lib64/libcudnn*.so.8 /usr/local/cuda-11.6/extras/CUPTI/lib64/libcupti.so.11.6)
-    elif [[ $CUDA_VERSION == 11.7* ]]; then
+    if [[ $CUDA_VERSION == 11.7* ]]; then
         TORCH_CUDA_ARCH_LIST="$TORCH_CUDA_ARCH_LIST;6.0;6.1;7.0;7.5;8.0;8.6"
         #for cuda 11.7 we use cudnn 8.5
         #which does not have single static libcudnn_static.a deliverable to link with

libtorch/Dockerfile

@@ -44,10 +44,6 @@ ADD ./common/install_conda.sh install_conda.sh
 RUN bash ./install_conda.sh && rm install_conda.sh
 RUN /opt/conda/bin/conda install -y cmake=3.18
 
-FROM cuda as cuda11.6
-RUN bash ./install_cuda.sh 11.6
-RUN bash ./install_magma.sh 11.6
-
 FROM cuda as cuda11.7
 RUN bash ./install_cuda.sh 11.7
 RUN bash ./install_magma.sh 11.7

libtorch/build_all_docker.sh

@@ -4,7 +4,7 @@ set -eou pipefail
 
 TOPDIR=$(git rev-parse --show-toplevel)
 
-for cuda_version in 11.8 11.7 11.6; do
+for cuda_version in 11.8 11.7; do
     GPU_ARCH_TYPE=cuda GPU_ARCH_VERSION="${cuda_version}" "${TOPDIR}/libtorch/build_docker.sh"
 done
 

manywheel/build_all_docker.sh

@@ -9,7 +9,7 @@ MANYLINUX_VERSION=2014 GPU_ARCH_TYPE=cpu "${TOPDIR}/manywheel/build_docker.sh"
 
 GPU_ARCH_TYPE=cpu-cxx11-abi "${TOPDIR}/manywheel/build_docker.sh"
 
-for cuda_version in 11.7 11.6; do
+for cuda_version in 11.8 11.7; do
     GPU_ARCH_TYPE=cuda GPU_ARCH_VERSION="${cuda_version}" "${TOPDIR}/manywheel/build_docker.sh"
     MANYLINUX_VERSION=2014 GPU_ARCH_TYPE=cuda GPU_ARCH_VERSION="${cuda_version}" "${TOPDIR}/manywheel/build_docker.sh"
 done

manywheel/build_cuda.sh

@@ -108,41 +108,7 @@ elif [[ "$OS_NAME" == *"Ubuntu"* ]]; then
     LIBGOMP_PATH="/usr/lib/x86_64-linux-gnu/libgomp.so.1"
 fi
 
-if [[ $CUDA_VERSION == "11.6" ]]; then
-export USE_STATIC_CUDNN=0
-DEPS_LIST=(
-    "/usr/local/cuda/lib64/libcudart.so.11.0"
-    "/usr/local/cuda/lib64/libnvToolsExt.so.1"
-    "/usr/local/cuda/lib64/libnvrtc.so.11.2"    # this is not a mistake for 11.6
-    "/usr/local/cuda/lib64/libnvrtc-builtins.so.11.6"
-    "/usr/local/cuda/lib64/libcudnn_adv_infer.so.8"
-    "/usr/local/cuda/lib64/libcudnn_adv_train.so.8"
-    "/usr/local/cuda/lib64/libcudnn_cnn_infer.so.8"
-    "/usr/local/cuda/lib64/libcudnn_cnn_train.so.8"
-    "/usr/local/cuda/lib64/libcudnn_ops_infer.so.8"
-    "/usr/local/cuda/lib64/libcudnn_ops_train.so.8"
-    "/usr/local/cuda/lib64/libcudnn.so.8"
-    "/usr/local/cuda/lib64/libcublas.so.11"
-    "/usr/local/cuda/lib64/libcublasLt.so.11"
-    "$LIBGOMP_PATH"
-)
-DEPS_SONAME=(
-    "libcudart.so.11.0"
-    "libnvToolsExt.so.1"
-    "libnvrtc.so.11.2"
-    "libnvrtc-builtins.so.11.6"
-    "libcudnn_adv_infer.so.8"
-    "libcudnn_adv_train.so.8"
-    "libcudnn_cnn_infer.so.8"
-    "libcudnn_cnn_train.so.8"
-    "libcudnn_ops_infer.so.8"
-    "libcudnn_ops_train.so.8"
-    "libcudnn.so.8"
-    "libcublas.so.11"
-    "libcublasLt.so.11"
-    "libgomp.so.1"
-)
-elif [[ $CUDA_VERSION == "11.7" || $CUDA_VERSION == "11.8" ]]; then
+if [[ $CUDA_VERSION == "11.7" || $CUDA_VERSION == "11.8" ]]; then
     export USE_STATIC_CUDNN=0
     # Try parallelizing nvcc as well
     export TORCH_NVCC_FLAGS="-Xfatbin -compress-all --threads 2"

windows/internal/cuda_install.bat

@@ -19,40 +19,12 @@ set CUDNN_LIB_FOLDER="lib\x64"
 :: Skip all of this if we already have cuda installed
 if exist "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v%CUDA_VERSION_STR%\bin\nvcc.exe" goto set_cuda_env_vars
 
-if %CUDA_VER% EQU 116 goto cuda116
 if %CUDA_VER% EQU 117 goto cuda117
 if %CUDA_VER% EQU 118 goto cuda118
 
 echo CUDA %CUDA_VERSION_STR% is not supported
 exit /b 1
 
-:cuda116
-
-set CUDA_INSTALL_EXE=cuda_11.6.0_511.23_windows.exe
-if not exist "%SRC_DIR%\temp_build\%CUDA_INSTALL_EXE%" (
-    curl -k -L "https://ossci-windows.s3.amazonaws.com/%CUDA_INSTALL_EXE%" --output "%SRC_DIR%\temp_build\%CUDA_INSTALL_EXE%"
-    if errorlevel 1 exit /b 1
-    set "CUDA_SETUP_FILE=%SRC_DIR%\temp_build\%CUDA_INSTALL_EXE%"
-    set "ARGS=thrust_11.6 nvcc_11.6 cuobjdump_11.6 nvprune_11.6 nvprof_11.6 cupti_11.6 cublas_11.6 cublas_dev_11.6 cudart_11.6 cufft_11.6 cufft_dev_11.6 curand_11.6 curand_dev_11.6 cusolver_11.6 cusolver_dev_11.6 cusparse_11.6 cusparse_dev_11.6 npp_11.6 npp_dev_11.6 nvrtc_11.6 nvrtc_dev_11.6 nvml_dev_11.6"
-)
-
-set CUDNN_FOLDER=cudnn-windows-x86_64-8.3.2.44_cuda11.5-archive
-set CUDNN_LIB_FOLDER="lib"
-set "CUDNN_INSTALL_ZIP=%CUDNN_FOLDER%.zip"
-if not exist "%SRC_DIR%\temp_build\%CUDNN_INSTALL_ZIP%" (
-    curl -k -L "http://s3.amazonaws.com/ossci-windows/%CUDNN_INSTALL_ZIP%" --output "%SRC_DIR%\temp_build\%CUDNN_INSTALL_ZIP%"
-    if errorlevel 1 exit /b 1
-    set "CUDNN_SETUP_FILE=%SRC_DIR%\temp_build\%CUDNN_INSTALL_ZIP%"
-)
-
-@REM Cuda 8.3+ required zlib to be installed on the path
-echo Installing ZLIB dlls
-curl -k -L "http://s3.amazonaws.com/ossci-windows/zlib123dllx64.zip" --output "%SRC_DIR%\temp_build\zlib123dllx64.zip"
-7z x "%SRC_DIR%\temp_build\zlib123dllx64.zip" -o"%SRC_DIR%\temp_build\zlib"
-xcopy /Y "%SRC_DIR%\temp_build\zlib\dll_x64\*.dll" "C:\Windows\System32"
-
-goto cuda_common
-
 :cuda117
 
 set CUDA_INSTALL_EXE=cuda_11.7.0_516.01_windows.exe

windows/internal/smoke_test.bat

@@ -65,9 +65,6 @@ set "CONDA_HOME=%CD%\conda"
 set "tmp_conda=%CONDA_HOME%"
 set "miniconda_exe=%CD%\miniconda.exe"
 set "CONDA_EXTRA_ARGS=cpuonly -c pytorch-nightly"
-if "%CUDA_VERSION%" == "116" (
-    set "CONDA_EXTRA_ARGS=pytorch-cuda=11.6 -c nvidia -c pytorch-nightly"
-)
 if "%CUDA_VERSION%" == "117" (
     set "CONDA_EXTRA_ARGS=pytorch-cuda=11.7 -c nvidia -c pytorch-nightly"
 )