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4 changes: 3 additions & 1 deletion .github/scripts/fbgemm_gpu_build.bash
Original file line number Diff line number Diff line change
Expand Up @@ -192,7 +192,9 @@ __configure_fbgemm_gpu_build_cuda () {
cuda_version_nvcc=$(conda run -n "${env_name}" nvcc --version)
echo "[BUILD] Using the default architectures for CUDA $cuda_version_nvcc ..."

if [[ $cuda_version_nvcc == *"V12.1"* ]] || [[ $cuda_version_nvcc == *"V12.4"* ]]; then
if [[ $cuda_version_nvcc == *"V12.1"* ]] ||
[[ $cuda_version_nvcc == *"V12.4"* ]] ||
[[ $cuda_version_nvcc == *"V12.6"* ]]; then
# sm_90 and sm_90a are only available for CUDA 12.1+
# NOTE: CUTLASS kernels for Hopper require sm_90a to be enabled
# See:
Expand Down
2 changes: 1 addition & 1 deletion .github/scripts/fbgemm_gpu_install.bash
Original file line number Diff line number Diff line change
Expand Up @@ -182,7 +182,7 @@ install_fbgemm_gpu_pip () {
echo " ${FUNCNAME[0]} build_env 0.8.0 cpu # Install the CPU variant, specific version from release channel"
echo " ${FUNCNAME[0]} build_env release cuda/12.4.1 # Install the CUDA variant, latest version from release channel"
echo " ${FUNCNAME[0]} build_env test/0.8.0 cuda/12.4.1 # Install the CUDA 12.4 variant, specific version from test channel"
echo " ${FUNCNAME[0]} build_env nightly rocm/6.1 # Install the ROCM 6.1 variant, latest version from nightly channel"
echo " ${FUNCNAME[0]} build_env nightly rocm/6.2 # Install the ROCM 6.2 variant, latest version from nightly channel"
return 1
else
echo "################################################################################"
Expand Down
3 changes: 1 addition & 2 deletions .github/scripts/fbgemm_gpu_test.bash
Original file line number Diff line number Diff line change
Expand Up @@ -332,7 +332,7 @@ test_setup_conda_environment () {
if [ "$pytorch_variant_type" == "" ]; then
echo "Usage: ${FUNCNAME[0]} ENV_NAME COMPILER PYTHON_VERSION PYTORCH_INSTALLER PYTORCH_CHANNEL[/VERSION] PYTORCH_VARIANT_TYPE [PYTORCH_VARIANT_VERSION]"
echo "Example(s):"
echo " ${FUNCNAME[0]} build_env clang 3.12 pip test/0.8.0 cuda 12.1.0 # Setup environment with pytorch-test 0.8.0 for Clang + Python 3.12 + CUDA 12.1.0"
echo " ${FUNCNAME[0]} build_env clang 3.12 pip test/0.8.0 cuda 12.4.1 # Setup environment with pytorch-test 0.8.0 for Clang + Python 3.12 + CUDA 12.4.1"
return 1
else
echo "################################################################################"
Expand Down Expand Up @@ -494,7 +494,6 @@ test_fbgemm_gpu_setup_and_pip_install () {
if [ "$variant_type" == "cuda" ] || [ "$variant_type" == "genai" ]; then
local variant_versions=(
11.8.0
12.1.1
12.4.1
)
elif [ "$variant_type" == "rocm" ]; then
Expand Down
4 changes: 2 additions & 2 deletions .github/scripts/test_torchrec.bash
Original file line number Diff line number Diff line change
Expand Up @@ -29,10 +29,10 @@ usage () {
echo " e.g., torchrec needs fbgemm-gpu while torchrec_nightly needs fbgemm-gpu-nightly"
echo "PYTHON_VERSION : Python version (e.g., 3.10)"
echo "PYTORCH_CHANNEL_NAME: PyTorch's channel name (e.g., pytorch-nightly, pytorch-test (=pre-release), pytorch (=stable release))"
echo "CUDA_VERSION : PyTorch's CUDA version (e.g., 12.1)"
echo "CUDA_VERSION : PyTorch's CUDA version (e.g., 12.4)"
echo "FBGEMM_WHEEL_PATH : path to FBGEMM_GPU's wheel file"
echo "MINICONDA_PREFIX : path to install Miniconda (default: \$HOME/miniconda)"
echo "Example: Python 3.10 + PyTorch nightly (CUDA 12.1), install miniconda at \$HOME/miniconda, using dist/fbgemm_gpu_nightly.whl"
echo "Example: Python 3.10 + PyTorch nightly (CUDA 12.4), install miniconda at \$HOME/miniconda, using dist/fbgemm_gpu_nightly.whl"
# shellcheck disable=SC2086
echo " bash $(basename ${BASH_SOURCE[0]}) -v -o torchrec_nightly -p 3.10 -P pytorch-nightly -c 11.7 -w dist/fbgemm_gpu_nightly.whl"
}
Expand Down
21 changes: 15 additions & 6 deletions .github/scripts/utils_build.bash
Original file line number Diff line number Diff line change
Expand Up @@ -109,14 +109,18 @@ __conda_install_gcc () {
# shellcheck disable=SC2155
local env_prefix=$(env_name_or_prefix "${env_name}")

# NOTE: g++ 10.x is installed by default instead of 11.x+ becaue 11.x+ builds
# binaries that reference GLIBCXX_3.4.29, which may not be available on
# systems with older versions of libstdc++.so.6 such as CentOS Stream 8 and
# Ubuntu 20.04. However, if libfolly is used, GLIBCXX_3.4.30+ will be
# required, which will require 11.x+.
# NOTE: Previously, g++ 10.x is installed by default instead of 11.x+ because
# 11.x+ builds binaries that reference GLIBCXX_3.4.29, which may not be
# available on systems with older versions of libstdc++.so.6 such as CentOS
# Stream 8 and Ubuntu 20.04.
#
# However, since https://github.com/pytorch/pytorch/pull/141035 landed, g++
# 11.1+ became a requirement, since std::bit_cast is only available with
# libstdc++ 11.1+. See for details:
# https://gcc.gnu.org/onlinedocs/libstdc++/manual/status.html#manual.intro.status.iso
#
# shellcheck disable=SC2155
local gcc_version="${GCC_VERSION:-10.4.0}"
local gcc_version="${GCC_VERSION:-11.4.0}"

echo "[INSTALL] Installing GCC (${gcc_version}, ${archname}) through Conda ..."
# shellcheck disable=SC2086
Expand Down Expand Up @@ -169,6 +173,11 @@ __conda_install_clang () {
# shellcheck disable=SC2155,SC2086
local cxx_path=$(conda run ${env_prefix} which clang++)

# shellcheck disable=SC2086
print_exec conda env config vars set ${env_prefix} CC="${cc_path}"
# shellcheck disable=SC2086
print_exec conda env config vars set ${env_prefix} CXX="${cxx_path}"

# Set the symlinks, override if needed
print_exec ln -sf "${cc_path}" "$(dirname "$cc_path")/cc"
print_exec ln -sf "${cc_path}" "$(dirname "$cc_path")/gcc"
Expand Down
1 change: 1 addition & 0 deletions .github/scripts/utils_cuda.bash
Original file line number Diff line number Diff line change
Expand Up @@ -163,6 +163,7 @@ install_cudnn () {
["118"]="https://developer.download.nvidia.com/compute/redist/cudnn/v8.7.0/local_installers/11.8/cudnn-${PLATFORM_NAME_LC}-8.7.0.84_cuda11-archive.tar.xz"
["121"]="https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/cudnn-linux-x86_64-8.9.2.26_cuda12-archive.tar.xz"
["124"]="https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/cudnn-linux-x86_64-8.9.2.26_cuda12-archive.tar.xz"
["126"]="https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/cudnn-linux-x86_64-9.5.1.17_cuda12-archive.tar.xz"
)

# Split version string by dot into array, i.e. 11.7.1 => [11, 7, 1]
Expand Down
10 changes: 5 additions & 5 deletions .github/scripts/utils_pip.bash
Original file line number Diff line number Diff line change
Expand Up @@ -41,7 +41,7 @@ __export_package_channel_info () {
__export_package_variant_info () {
local package_variant_type_version="$1"

local FALLBACK_VERSION_CUDA="12.1.1"
local FALLBACK_VERSION_CUDA="12.4.1"
local FALLBACK_VERSION_ROCM="6.0.2"

if [ "$package_variant_type_version" == "cuda" ]; then
Expand All @@ -60,7 +60,7 @@ __export_package_variant_info () {
local variant_version=""

else
# Split along '/', e.g. cuda/12.1.0
# Split along '/', e.g. cuda/12.4.0
# shellcheck disable=SC2207
local package_variant_type_version_arr=($(echo "${package_variant_type_version}" | tr '/' '\n'))
local variant_type="${package_variant_type_version_arr[0]}"
Expand All @@ -71,7 +71,7 @@ __export_package_variant_info () {
local cuda_version="${variant_version:-${FALLBACK_VERSION_CUDA}}"
# shellcheck disable=SC2206
local cuda_version_arr=(${cuda_version//./ })
# Convert, i.e. cuda 12.1.0 => cu121
# Convert, i.e. cuda 12.4.0 => cu124
local variant_type="cu"
local variant_version="${cuda_version_arr[0]}${cuda_version_arr[1]}"

Expand Down Expand Up @@ -204,7 +204,7 @@ install_from_pytorch_pip () {
echo "Example(s):"
echo " ${FUNCNAME[0]} build_env torch 1.11.0 cpu # Install the CPU variant, specific version from release channel"
echo " ${FUNCNAME[0]} build_env torch release cpu # Install the CPU variant, latest version from release channel"
echo " ${FUNCNAME[0]} build_env fbgemm_gpu test/0.8.0 cuda/12.1.0 # Install the CUDA 12.1 variant, specific version from test channel"
echo " ${FUNCNAME[0]} build_env fbgemm_gpu test/0.8.0 cuda/12.4.0 # Install the CUDA 12.4 variant, specific version from test channel"
echo " ${FUNCNAME[0]} build_env fbgemm_gpu nightly rocm/6.1 # Install the ROCM 6.1 variant, latest version from nightly channel"
echo " ${FUNCNAME[0]} build_env pytorch_triton 1.11.0 # Install specific version from release channel"
echo " ${FUNCNAME[0]} build_env pytorch_triton release # Install latest version from release channel"
Expand Down Expand Up @@ -249,7 +249,7 @@ download_from_pytorch_pip () {
echo "Example(s):"
echo " ${FUNCNAME[0]} build_env torch 1.11.0 cpu # Download the CPU variant, specific version from release channel"
echo " ${FUNCNAME[0]} build_env torch release cpu # Download the CPU variant, latest version from release channel"
echo " ${FUNCNAME[0]} build_env fbgemm_gpu test/0.8.0 cuda/12.1.0 # Download the CUDA 12.1 variant, specific version from test channel"
echo " ${FUNCNAME[0]} build_env fbgemm_gpu test/0.8.0 cuda/12.4.0 # Download the CUDA 12.4 variant, specific version from test channel"
echo " ${FUNCNAME[0]} build_env fbgemm_gpu nightly rocm/6.1 # Download the ROCM 6.1 variant, latest version from nightly channel"
return 1
else
Expand Down
2 changes: 1 addition & 1 deletion .github/scripts/utils_pytorch.bash
Original file line number Diff line number Diff line change
Expand Up @@ -112,7 +112,7 @@ install_pytorch_pip () {
echo "Example(s):"
echo " ${FUNCNAME[0]} build_env test/2.1.0 cpu # Install the CPU variant for a specific version"
echo " ${FUNCNAME[0]} build_env release cpu # Install the CPU variant, latest release version"
echo " ${FUNCNAME[0]} build_env test cuda/12.1.0 # Install the CUDA 12.1 variant, latest test version"
echo " ${FUNCNAME[0]} build_env test cuda/12.4.0 # Install the CUDA 12.4 variant, latest test version"
echo " ${FUNCNAME[0]} build_env nightly rocm/6.1 # Install the ROCM 6.1 variant, latest nightly version"
return 1
else
Expand Down
2 changes: 1 addition & 1 deletion .github/scripts/utils_torchrec.bash
Original file line number Diff line number Diff line change
Expand Up @@ -26,7 +26,7 @@ install_torchrec_pip () {
echo "Example(s):"
echo " ${FUNCNAME[0]} build_env test/2.1.0rc0 cpu # Install the CPU variant for a specific version"
echo " ${FUNCNAME[0]} build_env release cpu # Install the CPU variant, latest release version"
echo " ${FUNCNAME[0]} build_env nightly/0.9.0.dev20240716 cuda/12.1.0 # Install the CUDA 12.1 variant, nightly version"
echo " ${FUNCNAME[0]} build_env nightly/0.9.0.dev20240716 cuda/12.4.0 # Install the CUDA 12.4 variant, nightly version"
return 1
else
echo "################################################################################"
Expand Down
2 changes: 1 addition & 1 deletion .github/workflows/fbgemm_ci.yml
Original file line number Diff line number Diff line change
Expand Up @@ -144,7 +144,7 @@ jobs:
run: . $PRELUDE; create_conda_environment $BUILD_ENV 3.12

- name: Install C/C++ Compilers
run: . $PRELUDE; install_cxx_compiler $BUILD_ENV ${{ matrix.compiler }}
run: . $PRELUDE; GCC_VERSION=10.4.0 install_cxx_compiler $BUILD_ENV ${{ matrix.compiler }}

- name: Install Build Tools
run: . $PRELUDE; install_build_tools $BUILD_ENV
Expand Down
4 changes: 2 additions & 2 deletions .github/workflows/fbgemm_gpu_ci_cuda.yml
Original file line number Diff line number Diff line change
Expand Up @@ -67,7 +67,7 @@ jobs:
{ arch: x86, instance: "linux.24xlarge" },
]
python-version: [ "3.9", "3.10", "3.11", "3.12" ]
cuda-version: [ "11.8.0", "12.1.1", "12.4.1" ]
cuda-version: [ "11.8.0", "12.4.1" ]
compiler: [ "gcc", "clang" ]

steps:
Expand Down Expand Up @@ -150,7 +150,7 @@ jobs:
# { arch: x86, instance: "linux.gcp.a100" },
]
python-version: [ "3.9", "3.10", "3.11", "3.12" ]
cuda-version: [ "11.8.0", "12.1.1", "12.4.1" ]
cuda-version: [ "11.8.0", "12.4.1" ]
# Specify exactly ONE CUDA version for artifact publish
cuda-version-publish: [ "12.4.1" ]
compiler: [ "gcc", "clang" ]
Expand Down
4 changes: 2 additions & 2 deletions .github/workflows/fbgemm_gpu_ci_genai.yml
Original file line number Diff line number Diff line change
Expand Up @@ -67,7 +67,7 @@ jobs:
{ arch: x86, instance: "linux.24xlarge" },
]
python-version: [ "3.9", "3.10", "3.11", "3.12" ]
cuda-version: [ "11.8.0", "12.1.1", "12.4.1" ]
cuda-version: [ "11.8.0", "12.4.1" ]
compiler: [ "gcc", "clang" ]

steps:
Expand Down Expand Up @@ -149,7 +149,7 @@ jobs:
# { arch: x86, instance: "linux.gcp.a100" },
]
python-version: [ "3.9", "3.10", "3.11", "3.12" ]
cuda-version: [ "11.8.0", "12.1.1", "12.4.1" ]
cuda-version: [ "11.8.0", "12.4.1" ]
# Specify exactly ONE CUDA version for artifact publish
cuda-version-publish: [ "12.4.1" ]
compiler: [ "gcc", "clang" ]
Expand Down
4 changes: 2 additions & 2 deletions .github/workflows/fbgemm_gpu_ci_genai_generic_infra.yml
Original file line number Diff line number Diff line change
Expand Up @@ -54,7 +54,7 @@ jobs:
{ arch: x86, instance: "ubuntu-latest" },
]
python-version: [ "3.9", "3.10", "3.11", "3.12" ]
cuda-version: [ "11.8.0", "12.1.1", "12.4.1" ]
cuda-version: [ "11.8.0", "12.4.1" ]
compiler: [ "gcc", "clang" ]

steps:
Expand Down Expand Up @@ -141,7 +141,7 @@ jobs:
{ arch: x86, instance: "ubuntu-latest" },
]
python-version: [ "3.9", "3.10", "3.11", "3.12" ]
cuda-version: [ "11.8.0", "12.1.1", "12.4.1" ]
cuda-version: [ "11.8.0", "12.4.1" ]
# Specify exactly ONE CUDA version for artifact publish
cuda-version-publish: [ "12.4.1" ]
compiler: [ "gcc", "clang" ]
Expand Down
8 changes: 4 additions & 4 deletions .github/workflows/fbgemm_gpu_ci_rocm.yml
Original file line number Diff line number Diff line change
Expand Up @@ -64,9 +64,9 @@ jobs:
host-machine: [
{ arch: x86, instance: "linux.24xlarge" },
]
container-image: [ "ubuntu:20.04" ]
container-image: [ "ubuntu:22.04" ]
python-version: [ "3.9", "3.10", "3.11", "3.12" ]
rocm-version: [ "6.1" ]
rocm-version: [ "6.1", "6.2" ]
compiler: [ "gcc", "clang" ]

steps:
Expand Down Expand Up @@ -129,7 +129,7 @@ jobs:
if: ${{ github.repository_owner == 'pytorch' }}
runs-on: ${{ matrix.host-machine.instance }}
container:
image: "rocm/dev-ubuntu-20.04:${{ matrix.rocm-version }}-complete"
image: "rocm/dev-ubuntu-22.04:${{ matrix.rocm-version }}-complete"
options: --user root --device=/dev/kfd --device=/dev/dri --ipc=host --shm-size 16G --group-add video --cap-add=SYS_PTRACE --security-opt seccomp=unconfined
defaults:
run:
Expand All @@ -147,7 +147,7 @@ jobs:
]
# ROCm machines are limited, so we only test a subset of Python versions
python-version: [ "3.12" ]
rocm-version: [ "6.1" ]
rocm-version: [ "6.2" ]
compiler: [ "gcc", "clang" ]
needs: build_artifact

Expand Down
6 changes: 3 additions & 3 deletions .github/workflows/fbgemm_gpu_pip.yml
Original file line number Diff line number Diff line change
Expand Up @@ -121,7 +121,7 @@ jobs:
{ instance: "linux.g5.4xlarge.nvidia.gpu" },
]
python-version: [ "3.9", "3.10", "3.11", "3.12" ]
cuda-version: [ "11.8.0", "12.1.1", "12.4.1" ]
cuda-version: [ "11.8.0", "12.4.1" ]

steps:
# Cannot upgrade to actions/checkout@v4 yet because GLIBC on the instance is too old
Expand Down Expand Up @@ -168,7 +168,7 @@ jobs:
if: ${{ github.repository_owner == 'pytorch' && (github.event_name == 'schedule' || (github.event_name == 'workflow_dispatch' && github.event.inputs.fbgemm_gpu_variant_type == 'rocm')) }}
runs-on: ${{ matrix.host-machine.instance }}
container:
image: "rocm/dev-ubuntu-20.04:${{ matrix.rocm-version }}-complete"
image: "rocm/dev-ubuntu-22.04:${{ matrix.rocm-version }}-complete"
options: --user root --device=/dev/kfd --device=/dev/dri --ipc=host --shm-size 16G --group-add video --cap-add=SYS_PTRACE --security-opt seccomp=unconfined
defaults:
run:
Expand All @@ -186,7 +186,7 @@ jobs:
]
# ROCm machines are limited, so we only test a subset of Python versions
python-version: [ "3.11", "3.12" ]
rocm-version: [ "6.1" ]
rocm-version: [ "6.2" ]

steps:
- name: Setup Build Container
Expand Down
6 changes: 3 additions & 3 deletions .github/workflows/fbgemm_gpu_release_cuda.yml
Original file line number Diff line number Diff line change
Expand Up @@ -34,7 +34,7 @@ on:
description: CUDA Version to Use for Building Artifact
type: choice
required: false
options: [ "11.8.0", "12.1.1", "12.4.1" ]
options: [ "11.8.0", "12.4.1" ]
default: "12.4.1"
publish_to_pypi:
description: Publish Artifact to PyPI
Expand Down Expand Up @@ -71,7 +71,7 @@ jobs:
{ arch: x86, instance: "linux.24xlarge" },
]
python-version: [ "3.9", "3.10", "3.11", "3.12" ]
cuda-version: [ "11.8.0", "12.1.1", "12.4.1" ]
cuda-version: [ "11.8.0", "12.4.1" ]

steps:
- name: Setup Build Container
Expand Down Expand Up @@ -144,7 +144,7 @@ jobs:
{ arch: x86, instance: "linux.g5.4xlarge.nvidia.gpu" },
]
python-version: [ "3.9", "3.10", "3.11", "3.12" ]
cuda-version: [ "11.8.0", "12.1.1", "12.4.1" ]
cuda-version: [ "11.8.0", "12.4.1" ]
needs: build_artifact

steps:
Expand Down
6 changes: 3 additions & 3 deletions .github/workflows/fbgemm_gpu_release_genai.yml
Original file line number Diff line number Diff line change
Expand Up @@ -34,7 +34,7 @@ on:
description: CUDA Version to Use for Building Artifact
type: choice
required: false
options: [ "11.8.0", "12.1.1", "12.4.1" ]
options: [ "11.8.0", "12.4.1" ]
default: "12.4.1"
publish_to_pypi:
description: Publish Artifact to PyPI
Expand Down Expand Up @@ -71,7 +71,7 @@ jobs:
{ arch: x86, instance: "linux.24xlarge" },
]
python-version: [ "3.9", "3.10", "3.11", "3.12" ]
cuda-version: [ "11.8.0", "12.1.1", "12.4.1" ]
cuda-version: [ "11.8.0", "12.4.1" ]

steps:
- name: Setup Build Container
Expand Down Expand Up @@ -144,7 +144,7 @@ jobs:
{ arch: x86, instance: "linux.g5.4xlarge.nvidia.gpu" },
]
python-version: [ "3.9", "3.10", "3.11", "3.12" ]
cuda-version: [ "11.8.0", "12.1.1", "12.4.1" ]
cuda-version: [ "11.8.0", "12.4.1" ]
needs: build_artifact

steps:
Expand Down
2 changes: 1 addition & 1 deletion fbgemm_gpu/README.md
Original file line number Diff line number Diff line change
Expand Up @@ -9,7 +9,7 @@ PyTorch GPU operator libraries for training and inference. The library provides
efficient table batched embedding bag, data layout transformation, and
quantization supports.

FBGEMM_GPU is currently tested with CUDA 12.1 and 11.8 in CI, and with PyTorch
FBGEMM_GPU is currently tested with CUDA 12.4 and 11.8 in CI, and with PyTorch
packages (2.1+) that are built against those CUDA versions.

See the full [Documentation](https://pytorch.org/FBGEMM) for more information
Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -117,7 +117,7 @@ Install the full CUDA package through Conda, which includes
.. code:: sh

# See https://anaconda.org/nvidia/cuda for all available versions of CUDA
cuda_version=12.1.0
cuda_version=12.4.1

# Install the full CUDA package
conda install -n ${env_name} -y cuda -c "nvidia/label/cuda-${cuda_version}"
Expand Down Expand Up @@ -177,10 +177,10 @@ desired ROCm version:

.. code:: sh

# Run for ROCm 6.1.2
docker run -it --entrypoint "/bin/bash" rocm/rocm-terminal:6.1.2
# Run for ROCm 6.2.0
docker run -it --entrypoint "/bin/bash" rocm/rocm-terminal:6.2.0

While the `full ROCm Docker image <https://hub.docker.com/r/rocm/dev-ubuntu-20.04>`__
While the `full ROCm Docker image <https://hub.docker.com/r/rocm/dev-ubuntu-22.04>`__
comes with all ROCm packages pre-installed, it results in a very large Docker
container, and so for this reason, the minimal image is recommended for building
and running FBGEMM_GPU.
Expand Down
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