CyberSys · February 25, 2025 19:06 · Apr 11, 2021
diff --git a/pytorch_install_old_gpu.md b/pytorch_install_old_gpu.md
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+# PyTorch Compile for Old GPU's (Nvidia)
+
+**Assuming that anaconda and latest Nvidia driver is installed !!!**
+
+Find latest version of this document here https://github.com/salihmarangoz/UbuntuTweaks in `InstallProgramsTools.md`
+
+## Table of Contents
+   * [PyTorch Compile for Old GPU's (Nvidia)](#pytorch-compile-for-old-gpus-nvidia)
+      * [Configuration](#configuration)
+      * [Install CUDA, cuBLAS, cuDNN](#install-cuda-cublas-cudnn)
+      * [Set up Anaconda](#set-up-anaconda)
+      * [Build PyTorch](#build-pytorch)
+      * [Set up Anaconda (2)](#set-up-anaconda-2)
+      * [PyTorch Extras](#pytorch-extras)
+
+Created by [gh-md-toc](https://github.com/ekalinin/github-markdown-toc)
+
+
+
+## Configuration
+
+```bash
+export VIRT_ENV_NAME="pytorch-build"                     # Anaconda env name
+export VIRT_ENV_DISPLAY_NAME="Python 3 (PyTorch GPU)"    # Displayed kernel name
+
+# Set CUDA env variables. I have used Cuda 10.0
+export CUDA_NVCC_EXECUTABLE="/usr/local/cuda-10.0/bin/nvcc"
+export CUDA_HOME="/usr/local/cuda-10.0"
+export CUDNN_INCLUDE_PATH="/usr/local/cuda-10.0/include/"
+export CUDNN_LIBRARY_PATH="/usr/local/cuda-10.0/lib64/"
+export LIBRARY_PATH="/usr/local/cuda-10.0/lib64"
+export CUDA_TOOLKIT_ROOT_DIR=$CUDA_HOME
+
+export TORCH_CUDA_ARCH_LIST=3.0     # Set CUDA compute capability (My GPU's was 3.0)
+export USE_CUDA=1                   # For adding GPU capability to pytorch
+export USE_CUDNN=1                  # For better CUDA performance
+export USE_MKLDNN=1                 # For faster CPU operations
+export MAX_JOBS=4                   # Limit max jobs
+export BUILD_CAFFE2=0               # Disable caffe2 build
+export BUILD_CAFFE2_OPS=0
+export BUILD_TEST=0                 # Don't compile tests
+export BUILD_BINARY=0               # Don't compile cpp binaries
+export USE_DISTRIBUTED=0            # Disable distributed computing features
+```
+
+## Install CUDA, cuBLAS, cuDNN
+
+```bash
+$ sudo add-apt-repository ppa:graphics-drivers
+$ sudo apt-key adv --fetch-keys  http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub
+$ sudo bash -c 'echo "deb http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 /" > /etc/apt/sources.list.d/cuda.list'
+$ sudo bash -c 'echo "deb http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64 /" > /etc/apt/sources.list.d/cuda_learn.list'
+$ sudo apt update
+$ sudo apt install libomp-dev cuda-toolkit-10-0 cuda-cublas-dev-10-0
+$ sudo apt install libcudnn7-dev=7.6.5.32-1+cuda10.0 libcudnn7=7.6.5.32-1+cuda10.0
+```
+
+## Set up Anaconda
+
+```bash
+# Set up env
+$ conda create -y --name "$VIRT_ENV_NAME"
+$ source activate "$VIRT_ENV_NAME"
+
+# Install build dependencies
+$ conda install numpy ninja pyyaml mkl mkl-include setuptools cmake cffi typing_extensions future six requests dataclasses
+
+# Disable anaconda linker temporarly
+$ cd ~/anaconda3/envs/pytorch-build/compiler_compat
+$ mv ld ld-old
+```
+
+## Build PyTorch
+
+```bash
+# Download PyTorch
+$ cd ~
+$ git clone --recursive https://github.com/pytorch/pytorch -b v1.8.1  # set pytorch version here
+$ cd ~/pytorch
+$ git checkout v1.8.1  # set pytorch version here
+$ git submodule sync
+$ git submodule update --init --recursive
+
+# Compile PyTorch
+$ export CMAKE_PREFIX_PATH=${CONDA_PREFIX:-"$(dirname $(which conda))/../"}
+$ python setup.py install  # run "python setup.py clean" before retrying
+```
+
+## Set up Anaconda (2)
+
+```bash
+# Enable anaconda linker back
+$ cd ~/anaconda3/envs/pytorch-build/compiler_compat
+$ mv ld-old ld
+
+# Install some ML/linalg/plot libs
+$ conda install -c  conda-forge ipykernel matplotlib Pillow pandas scipy scikit-image scikit-learn sympy
+
+# Add kernel to ipykernel
+$ python -m ipykernel install --user --name "$VIRT_ENV_NAME" --display-name "$VIRT_ENV_DISPLAY_NAME"
+```
+
+## PyTorch Extras
+
+```bash
+# Note: --no-deps may break dependencies and can cause problem in the feature but you shouldn't install another version of PyTorch in this environment, so use it
+$ conda install torchvision=0.9.0=py38_cu101 -c pytorch --no-deps
+$ conda install pytorch-model-summary -c conda-forge --no-deps
+```
+