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update readme
Signed-off-by: youkaichao <youkaichao@gmail.com>
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third-party/README.md
vendored
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third-party/README.md
vendored
@ -8,66 +8,19 @@
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## Prerequisites
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1. [GDRCopy](https://github.com/NVIDIA/gdrcopy) (v2.4 and above recommended) is a low-latency GPU memory copy library based on NVIDIA GPUDirect RDMA technology, and *it requires kernel module installation with root privileges.*
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2. Hardware requirements
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- GPUDirect RDMA capable devices, see [GPUDirect RDMA Documentation](https://docs.nvidia.com/cuda/gpudirect-rdma/)
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Hardware requirements:
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- GPUs inside one node needs to be connected by NVLink
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- GPUs across different nodes needs to be connected by RDMA devices, see [GPUDirect RDMA Documentation](https://docs.nvidia.com/cuda/gpudirect-rdma/)
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- InfiniBand GPUDirect Async (IBGDA) support, see [IBGDA Overview](https://developer.nvidia.com/blog/improving-network-performance-of-hpc-systems-using-nvidia-magnum-io-nvshmem-and-gpudirect-async/)
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- For more detailed requirements, see [NVSHMEM Hardware Specifications](https://docs.nvidia.com/nvshmem/release-notes-install-guide/install-guide/abstract.html#hardware-requirements)
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## Installation procedure
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### 1. Install GDRCopy
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GDRCopy requires kernel module installation on the host system. Complete these steps on the bare-metal host before container deployment:
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#### Build and installation
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```bash
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wget https://github.com/NVIDIA/gdrcopy/archive/refs/tags/v2.4.4.tar.gz
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cd gdrcopy-2.4.4/
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make -j$(nproc)
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sudo make prefix=/opt/gdrcopy install
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```
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#### Kernel module installation
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After compiling the software, you need to install the appropriate packages based on your Linux distribution.
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For instance, using Ubuntu 22.04 and CUDA 12.3 as an example:
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```bash
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pushd packages
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CUDA=/path/to/cuda ./build-deb-packages.sh
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sudo dpkg -i gdrdrv-dkms_2.4.4_amd64.Ubuntu22_04.deb \
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libgdrapi_2.4.4_amd64.Ubuntu22_04.deb \
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gdrcopy-tests_2.4.4_amd64.Ubuntu22_04+cuda12.3.deb \
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gdrcopy_2.4.4_amd64.Ubuntu22_04.deb
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popd
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sudo ./insmod.sh # Load kernel modules on the bare-metal system
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```
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#### Container environment notes
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For containerized environments:
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1. Host: keep kernel modules loaded (`gdrdrv`)
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2. Container: install DEB packages *without* rebuilding modules:
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```bash
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sudo dpkg -i gdrcopy_2.4.4_amd64.Ubuntu22_04.deb \
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libgdrapi_2.4.4_amd64.Ubuntu22_04.deb \
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gdrcopy-tests_2.4.4_amd64.Ubuntu22_04+cuda12.3.deb
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```
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#### Verification
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```bash
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gdrcopy_copybw # Should show bandwidth test results
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```
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### 2. Acquiring NVSHMEM source code
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### 1. Acquiring NVSHMEM source code
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Download NVSHMEM v3.2.5 from the [NVIDIA NVSHMEM OPEN SOURCE PACKAGES](https://developer.nvidia.com/downloads/assets/secure/nvshmem/nvshmem_src_3.2.5-1.txz).
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### 3. Apply our custom patch
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### 2. Apply our custom patch
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Navigate to your NVSHMEM source directory and apply our provided patch:
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@ -75,7 +28,7 @@ Navigate to your NVSHMEM source directory and apply our provided patch:
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git apply /path/to/deep_ep/dir/third-party/nvshmem.patch
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```
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### 4. Configure NVIDIA driver
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### 3. Configure NVIDIA driver (required by inter-node communication)
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Enable IBGDA by modifying `/etc/modprobe.d/nvidia.conf`:
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@ -92,26 +45,31 @@ sudo reboot
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For more detailed configurations, please refer to the [NVSHMEM Installation Guide](https://docs.nvidia.com/nvshmem/release-notes-install-guide/install-guide/abstract.html).
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### 5. Build and installation
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### 4. Build and installation
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The following example demonstrates building NVSHMEM with IBGDA support:
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DeepEP uses NVLink for intra-node communication and IBGDA for inter-node communication. All the other features are disabled to reduce the dependencies.
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```bash
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CUDA_HOME=/path/to/cuda \
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GDRCOPY_HOME=/path/to/gdrcopy \
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NVSHMEM_SHMEM_SUPPORT=0 \
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NVSHMEM_UCX_SUPPORT=0 \
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NVSHMEM_USE_NCCL=0 \
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NVSHMEM_MPI_SUPPORT=0 \
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NVSHMEM_IBGDA_SUPPORT=1 \
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NVSHMEM_PMIX_SUPPORT=0 \
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NVSHMEM_TIMEOUT_DEVICE_POLLING=0 \
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NVSHMEM_USE_GDRCOPY=1 \
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cmake -S . -B build/ -DCMAKE_INSTALL_PREFIX=/path/to/your/dir/to/install
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export CUDA_HOME=/path/to/cuda
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# disable all features except IBGDA
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export NVSHMEM_IBGDA_SUPPORT=1
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cd build
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make -j$(nproc)
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make install
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export NVSHMEM_SHMEM_SUPPORT=0
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export NVSHMEM_UCX_SUPPORT=0
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export NVSHMEM_USE_NCCL=0
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export NVSHMEM_PMIX_SUPPORT=0
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export NVSHMEM_TIMEOUT_DEVICE_POLLING=0
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export NVSHMEM_USE_GDRCOPY=0
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export NVSHMEM_IBRC_SUPPORT=0
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export NVSHMEM_BUILD_TESTS=0
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export NVSHMEM_BUILD_EXAMPLES=0
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export NVSHMEM_MPI_SUPPORT=0
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export NVSHMEM_BUILD_HYDRA_LAUNCHER=0
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export NVSHMEM_BUILD_TXZ_PACKAGE=0
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export NVSHMEM_TIMEOUT_DEVICE_POLLING=0
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cmake -G Ninja -S . -B build -DCMAKE_INSTALL_PREFIX=/path/to/your/dir/to/install
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cmake --build build/ --target install
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```
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## Post-installation configuration
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