Installing the following packages should allow you to enable support for AArch64 containers on x86: The next section will go over the workflow that allows you to build on x86 and then run on Jetson. This section will go over the steps to enable that. You can very easily run AArch64 containers on your x86 workstation by using qemu’s virtualization features. One of the very cool features that are now enabled is the ability to build Arm CUDA binaries on your x86 machine without needing a cross compiler. Enabling Jetson Containers on an x86 workstation (using qemu) Only libcudadevrt.a and libcudart_static.a are included. Known limitation: The base l4t image doesn’t allow you to statically compile with all CUDA libraries.
#CUDA TOOLKIT DOCKER DRIVER#
( 8) Multiprocessors, ( 64) CUDA Cores/MP: 512 CUDA CoresĭeviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 10.0, CUDA Runtime Version = 10.0, NumDevs = 1 Total amount of global memory: 15692 MBytes (16454430720 bytes) $ sudo docker run -it -runtime nvidia devicequeryĬUDA Device Query (Runtime API) version (CUDART static linking)ĬUDA Driver Version / Runtime Version 10.0 / 10.0ĬUDA Capability Major/Minor version number: 7.2 samples /tmp/samples WORKDIR /tmp/samples/1_Utilities/deviceQuery RUN make clean & make CMD EOF
#CUDA TOOLKIT DOCKER INSTALL#
Dockerfile << EOF FROM nvcr.io/nvidia/l4t-base:r32.3.1 RUN apt-get update & apt-get install -y -no-install-recommends make g++ COPY. $ mkdir /tmp/docker-build & cd /tmp/docker-build Note that the version of JetPack would vary depending on the version being installed.Īfter JetPack is installed to your Jetson device, you can check that the NVIDIA Container Runtime is installed by running the following commands:
It is available for install via the NVIDIA SDK Manager along with other JetPack components as shown below in Figure 1. NVIDIA Container Runtime with Docker integration (via the nvidia-docker2 packages) is included as part of NVIDIA JetPack. The beta supports Jetson AGX Xavier, Jetson TX2 series, Jetson TX1, and Jetson Nano devices. The purpose of this document is to provide users with steps on getting started with running Docker containers on Jetson using the NVIDIA runtime. The NVIDIA runtime enables graphics and video processing applications such as DeepStream to be run in containers on the Jetson platform. This enables users to run GPU accelerated Deep Learning and HPC containers on Jetson devices. Starting with v4.2.1, NVIDIA JetPack includes a beta version of NVIDIA Container Runtime with Docker integration for the Jetson platform. NVIDIA Container Runtime on Jetson (Beta) Introduction
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