Developer Guide

NVIDIA DOCA Developer Guide

This document details the recommended steps to set up an NVIDIA DOCA development environment.

This guide is intended for software developers aiming to modify existing NVIDIA® DOCA applications or develop their own DOCA-based software.

For steps to install DOCA on NVIDIA® BlueField® DPU, refer to the NVIDIA DOCA Installation Guide for Linux. This guide focuses on the recommended flow for developing DOCA-based software, and will target the following environments:

• BlueField DPU is accessible and can be used during the development and testing process
  • Working within a development container
• BlueField DPU is inaccessible, and the development happens on the host or on a different server
  • Cross-compilation from the host
  • Working within a development container on top of QEMU running on the host

It is recommended to follow the former case, leveraging the DPU during the development and testing process.

This guide recommends using DOCA's development container during the development process, whether it is on the DPU or on the host. Deploying development containers allows multiple developers to work simultaneously on the same device (host or DPU) in an isolated manner and even across multiple different DOCA SDK versions. This can allow multiple developers to work on the DPU itself, for example, without the need to have a dedicated DPU per developer.

Another benefit of this container-based approach is that the development container allows developers to create and test their DOCA-based software in a user-friendly environment that comes pre-shipped with a set of handy development tools. The development container is focused on improving the development experience and is designed for that purpose, whereas the BlueField software is meant to be an efficient runtime environment for DOCA products.

2.1. Setup

A DOCA development container is created as part of the DOCA base image containers and it is recommended that it is deployed on top of the DPU. The doca:devel container supports multiple deployment techniques and may be found on NGC. The complete instructions for deploying the DOCA container on the DPU can be found under the "DOCA Development Containers" section in the NVIDIA DOCA Container Deployment Guide.

The development container allows developers to develop and test their DOCA-based software in a developer-friendly environment that comes pre-shipped with a set of handy development tools. In contrast to the BlueField OS that is meant to be an efficient runtime environment for DOCA products, the development container is focused on improving the development experience and is designed for that purpose.

2.2. Development

It is recommended to do the development within the doca:devel container.

That said, some developers prefer different integrated development environments (IDEs) or development tools, and sometimes will prefer working using a graphical IDE, at least until it is time to compile the code. As such, the recommendation is to mount a network share to the DPU (refer to NVIDIA DOCA DPU CLI for more information) and mount it to the container as well. While in a docker-based deployment this is straightforward, in the Kubernetes-based deployment it requires updating the "hostPath" field in the container's .yaml file:

            

            
…
- mountPath: /doca_devel 
  name: input-output 
resources: 
… 
# Shared host <-> container folder (directory shared with the hosting DPU)
- name: input-output 
  hostPath: 
    path: /tmp/doca_devel  # This field should point at the desired directory
    type: DirectoryOrCreate
        

2.3. Testing

The container is marked as "privileged", hence it can directly access the HW capabilities of the BlueField DPU. This means that once the tested program compiles successfully, it can be directly tested from within the container without the need to copy it to the DPU and running it there.

2.4. Publishing

Once the program passes the testing phase, it should be prepared for deployment. While some proof-of-concept (POC) programs are just copied "as-is" in their binary form, most deployments will probably be in the form of a package (.deb/.rpm) or a container.

Construction of the binary package can be done as-is inside the current doca:devel container, or as part of a CI pipeline that will leverage the same development container as part of it. For the construction of a container to ship the developed software, it is recommended to use a multi-staged build that ships the software on top of the runtime-oriented DOCA base images:

• doca:base-rt – Slim DOCA runtime environment
• doca:full-rt – Full DOCA runtime environment similar to the BlueField image

The runtime DOCA base images, alongside more details about their structure, can be found under the same NGC page that hosts the doca:devel image.

For a multi-staged build, it is recommended to compile the software inside the doca:devel container, and later copy it to one of the runtime container images. All relevant images must be pulled directly from NGC (using docker pull) to the container registry of the DPU.

If the development process needs to be done without access to a BlueField DPU, the recommendation is to use a QEMU-based deployment of a container on top of a regular x86 server. The development container for the host will be the same doca:devel image we mentioned previously.

3.1. Setup

1. Make sure Docker is installed on your host. Run:
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   docker version
           

   If it is not installed, visit the official Install Docker Engine webpage for installation instructions.

2. Install QEMU on the host.
   Note:

   This step is for x86 hosts only. If you are working on an aarch64 host, move to the next step.

   • For an Ubuntu host, run:
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     sudo apt-get install qemu binfmt-support qemu-user-static
     sudo docker run --rm --privileged multiarch/qemu-user-static --reset -p yes
             

   • For a CentOS/RHEL 7.x host, run:
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     sudo yum install epel-release
     sudo yum install qemu-system-arm
             

   • For a CentOS 8.0/8.2 host, run:
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     sudo yum install epel-release
     sudo yum install qemu-kvm
             

   • For a Fedora host, run:
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     sudo yum install qemu-system-aarch64
             

3. If you are using CentOS or Fedora on the host, verify if qemu-aarch64.conf exists. Run:
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   $ cat /etc/binfmt.d/qemu-aarch64.conf
           

   If it is missing, run:
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   echo ":qemu-aarch64:M::\x7fELF\x02\x01\x01\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x00\xb7:\xff\xff\xff\xff\xff\xff\xff\xfc\xff\xff\xff\xff\xff\xff\xff\xff\xfe\xff\xff:/usr/bin/qemu-aarch64-static:" > /etc/binfmt.d/qemu-aarch64.conf
           

   
   
4. If you are using CentOS or Fedora on the host, restart system binfmt. Run:
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   $ sudo systemctl restart systemd-binfmt
           

5. To load and execute the development container, refer to the "Docker Deployment" section of the NVIDIA DOCA Container Deployment Guide.

3.2. Development

Much like the development phase using a BlueField DPU, it is recommended to develop within the container running on top of QEMU.

3.3. Testing

While the compilation can be performed on top of the container, testing the compiled software must be done on top of a BlueField DPU. This is because the QEMU environment emulates an aarch64 architecture, but it does not emulate the hardware devices present on the BlueField DPU. Therefore, the tested program will not be able to access the devices needed for its successful execution, thus mandating that the testing is done on top of a physical DPU.

3.4. Publishing

The publishing process is identical to the publishing process when using a BlueField DPU.

In a typical setup, developers prefer to work on a familiar host since compilation is often significantly faster there. Therefore, developers may work on their host while cross-compiling their project to the DPU's Arm architecture.

4.1. Setup

1. Install Docker and QEMU your host. See steps 1-4 under section Setup.
2. Download the doca-cross component as described in NVIDIA DOCA Installation Guide for Linux and unpack it under the /root directory. Inside this directory one can find:
   • arm64_armv8_linux_gcc – cross file containing specific information about the cross compiler and the host machine
   • DOCA_cross.sh – script which handles all the required dependencies and pre-installations steps
   • A .txt file used by the script
3. To load the development container, refer to section "Docker Deployment" of the NVIDIA DOCA Container Deployment Guide.
   Note:

   It is important to ensure that the same DOCA version is used in the development container and the DOCA metapackages installed on the host.

4. Start running the container using the container's image ID while mapping the doca-cross directory to the container's /doca_devel directory:
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   sudo docker run -v /root/doca-cross/:/doca_devel --privileged -it -e container=docker <image_id>
           

   Now the shell will be redirected to be within the container.

5. Run the preparation script to copy all the Arm dependencies required for DOCA's cross compilation. The script will be in the mapped directory named doca_devel.
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   (container) /# cd doca_devel/
   (container) /doca_devel# ./DOCA_cross.sh
           

6. Exit the container and run the same script from the host side:
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   (host) /root/doca-cross# ./DOCA_cross.sh
           

   The /root/doca-cross directory is now fully configured and prepared for cross-compilation against DOCA.

7. Update the environment variables to point at the linaro cross-compiler:
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   export PATH=${PATH}:/opt/gcc-linaro/<linaro_version_dir>/aarch64-linux-gnu/bin:/opt/gcc-linaro/<linaro_version_dir>/bin
           

   Everything is set up and the cross-compilation can now be used.

   Note:

   Make sure to update the command according to the Linaro version installed by the script in the previous step. <linaro_version_dir> can be found under /opt/gcc-linaro/.

   Note:

   Cross-compilation requires Meson version ≥0.61.2 to be installed on the host. This is already provided as part of DOCA's installation.

4.2. DOCA and CUDA Setup

1. To cross-compile DOCA and CUDA applications, you must install CUDA Toolkit 1.6:
   1. The first toolkit installation is for x86 architecture. Select x86_64.
   2. The second toolkit installation is for Arm. Select arm64-sbsa and then cross.
   3. Select your host operating system, architecture, OS distribution, and version and select the installation type. It is recommended to use the deb (local) type.
2. Execute the following exports:
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   export CPATH=/usr/local/cuda/targets/sbsa-linux/include:$CPATH
   export LD_LIBRARY_PATH=/usr/local/cuda/targets/sbsa-linux/lib:$LD_LIBRARY_PATH
   export PATH=/usr/local/cuda/bin:/usr/local/cuda-11.6/bin:$PATH
           

3. Verify the meson version is at least 0.61.2.

   Everything is set up and the cross-compilation can now be used.

4.3. Development

It is recommended to develop normally while remembering to compile using the cross-compilation configuration file arm64_armv8_linux_gcc which can be found under the doca-cross directory. The following is an example procedure for cross-compiling DOCA applications from the host and to the Arm architecture:

1. Enable the meson cross-compilation option in /opt/mellanox/doca/applications/meson_options.txt by setting enable_cross_compilation_to_dpu to true.
2. Cross-compile the DOCA applications:
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   /opt/mellanox/doca/applications # meson cross-build --cross-file /root/doca-cross/arm64_armv8_linux_gcc 
   /opt/mellanox/doca/applications # ninja -C cross-build
           

   The cross-compiled binaries are created under the cross-build directory.

3. Cross-compile the DOCA and CUDA application:
   1. Set flag for GPU-enabled cross-compilation, enable_gpu_support, in /opt/mellanox/doca/applications/meson_options.txt to true.
   2. Run the compilation command as follows:
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      /opt/mellanox/doca/applications # meson cross-build --cross-file /root/doca-cross/arm64_armv8_linux_gcc -Dcuda_ccbindir=aarch64-linux-gnu-g++
      /opt/mellanox/doca/applications # ninja -C cross-build
              

      The cross-compiled binaries are created under the cross-build directory.

            

            
[built-in options]
pkg_config_path = ''
        

4.4. Testing

While the compilation can be performed on top of the host, testing the compiled software must be done on top of a BlueField-2 DPU. This is because the tested program is not able to access the devices needed for its successful execution, which mandates that the testing is performed on top of a physical DPU.

4.5. Publishing

The publishing process is identical to the publishing process when using a BlueField DPU.

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