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Update readme documentation #290

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merged 7 commits into from
Aug 23, 2023
Merged

Update readme documentation #290

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Aug 16, 2023
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Merge branch 'main' into updateReadME
mraduldubey Aug 17, 2023
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Merge branch 'main' into updateReadME
mraduldubey Aug 18, 2023
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18 changes: 15 additions & 3 deletions README.md
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Expand Up @@ -21,7 +21,8 @@ Automatically built and tested on Ubuntu 18.04, Jetson Boards and Windows 11 x64
### Prerequisites for CUDA
* Make account on developer.nvidia.com, else the next steps will show HTTP 404/403 errors
* Download and install CUDA tool kit based on your OS: __Note: we test both with CUDA v10.2 and v11.7 so either is fine__
* Ubuntu 18.04 : [CUDA Toolkit 10.2](https://developer.nvidia.com/cuda-10.2-download-archive?target_os=Linux&target_arch=x86_64&target_distro=Ubuntu&target_version=1804&target_type=debnetwork) or [CUDA Toolkit 11.7](https://developer.nvidia.com/cuda-downloads?target_os=Linux&target_arch=x86_64&Distribution=Ubuntu&target_version=18.04&target_type=deb_network)
* Ubuntu 18.04/20.04: 18.04 - [CUDA Toolkit 10.2](https://developer.nvidia.com/cuda-10.2-download-archive?target_os=Linux&target_arch=x86_64&target_distro=Ubuntu&target_version=1804&target_type=debnetwork),
20.04 - [CUDA Toolkit 11.7](https://developer.nvidia.com/cuda-11-7-0-download-archive?target_os=Linux&target_arch=x86_64&Distribution=Ubuntu&target_version=20.04)
* Windows 10/11 : [Cuda Toolkit 10.2](https://developer.nvidia.com/cuda-10.2-download-archive?target_os=Windows&target_arch=x86_64&target_version=10&target_type=exelocal) or [CUDA Toolkit 11.7](https://developer.nvidia.com/cuda-downloads?target_os=Windows&target_arch=x86_64)
* Download [Cudnn](https://developer.nvidia.com/rdp/cudnn-archive#a-collapse765-102) and extract where cuda is installed. Note: this is a painful process. Here are the steps:
* Download the correct tar/zip file matching your cuda version. _Do not download the exe/installer/deb package._
Expand Down Expand Up @@ -110,10 +111,19 @@ build_windows_cuda.bat
### Prerequisites
* Run the following to get latest build tools
```
sudo apt-get update && sudo apt-get -y install autoconf automake autopoint build-essential git-core git-lfs libass-dev libfreetype6-dev libgnutls28-dev libmp3lame-dev libsdl2-dev libtool libsoup-gnome2.4-dev libncurses5-dev libva-dev libvdpau-dev libvorbis-dev libxcb1-dev libxcb-shm0-dev libxcb-xfixes0-dev ninja-build pkg-config texinfo wget yasm zlib1g-dev nasm gperf bison curl zip unzip tar python3-pip flex && pip3 install meson
sudo apt-get update && sudo apt-get -y install autoconf automake autopoint build-essential git-core git-lfs libass-dev libssl-dev libfreetype6-dev libgnutls28-dev libmp3lame-dev libsdl2-dev libtool libsoup-gnome2.4-dev libncurses5-dev libva-dev libvdpau-dev libvorbis-dev libxcb1-dev libxcb-shm0-dev libxcb-xfixes0-dev ninja-build pkg-config texinfo wget yasm zlib1g-dev nasm gperf bison curl zip unzip tar python3-pip flex && pip3 install meson
```
* Note: start a new terminal as pip3 settings do not get effective on the same shell
* CMake minimum version 3.24 - Follow [this article](https://anglehit.com/how-to-install-the-latest-version-of-cmake-via-command-line/) to update cmake
* Add CUDA to path by appending following line to ~/.bashrc
```
export PATH=/usr/local/cuda/bin:$PATH
```
* reload ~/.bashrc:
```
source ~/.bashrc:
```
* Verify by checking output of nvcc --version, it must show 10.2 or 11.7 according to installed cuda. Then check output of nvidia-smi and verify the same. You can check nvidia path by giving echo $PATH in any terminal. If path is added and nvcc --version is not giving output reboot and try again.
* Clone with submodules and LFS.
```
git clone --recursive https://github.com/Apra-Labs/ApraPipes.git
Expand All @@ -123,7 +133,9 @@ build_windows_cuda.bat
### Build for linux

* ```chmod +x build_linux_*.sh```
* ```./build_linux_x64.sh``` or ```./build_linux_no_cuda.sh``` depending on previous step. No Cuda as the name suggests will not build the Nvidia Cuda GPU Modules. Use this if there is no nvidia GPU present on your host
* ```./build_linux_cuda.sh``` or ```./build_linux_no_cuda.sh``` depending on previous step.
If Nvidia GPU is present on system and CUDA is built then use - build_linux_cuda.sh
If there is no Nvidia GPU present on your host use - build_linux_no_cuda.sh. No Cuda as the name suggests will not build the Nvidia Cuda GPU Modules. Use this if

Build can take ~2 hours depending on the machine configuration.

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