Hardware Pre-requisite
- Jetson Nano
- A 5V 4Ampere Charger
- 64GB SD card
Software
- Jetson SD card image from https://developer.nvidia.com/embedded/downloads
- Etcher software installed on your system
- Preparing Your Raspberry Pi Flashing Jetson SD Card Image
- Unzip the SD card image
- Insert SD card into your system.
- Bring up Etcher tool and select the target SD card to which you want to flash the image.
Verifying the device
sudo lshw -C system
pico2
description: Computer
product: NVIDIA Jetson Nano Developer Kit
serial: 1422919082257
width: 64 bits
capabilities: smp cp15_barrier setend swp
DeviceQuery
/usr/local/cuda/samples/1_Utilities/deviceQuery
sudo make
ajeetraina@ajeetraina-desktop:/usr/local/cuda/samples/1_Utilities/deviceQuery$ sudo make
/usr/local/cuda-10.2/bin/nvcc -ccbin g++ -I../../common/inc -m64 -gencode arch=compute_30,code=sm_30 -gencode arch=compute_32,code=sm_32 -gencode arch=compute_53,code=sm_53 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_62,code=sm_62 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_72,code=sm_72 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_75,code=compute_75 -o deviceQuery.o -c deviceQuery.cpp
/usr/local/cuda-10.2/bin/nvcc -ccbin g++ -m64 -gencode arch=compute_30,code=sm_30 -gencode arch=compute_32,code=sm_32 -gencode arch=compute_53,code=sm_53 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_62,code=sm_62 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_72,code=sm_72 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_75,code=compute_75 -o deviceQuery deviceQuery.o
mkdir -p ../../bin/aarch64/linux/release
cp deviceQuery ../../bin/aarch64/linux/release
ajeetraina@ajeetraina-desktop:/usr/local/cuda/samples/1_Utilities/deviceQuery$ ls
Makefile NsightEclipse.xml deviceQuery deviceQuery.cpp deviceQuery.o readme.txt
ajeetraina@ajeetraina-desktop:/usr/local/cuda/samples/1_Utilities/deviceQuery$ ./deviceQuery
./deviceQuery Starting...
CUDA Device Query (Runtime API) version (CUDART static linking)
Detected 1 CUDA Capable device(s)
Device 0: "NVIDIA Tegra X1"
CUDA Driver Version / Runtime Version 10.2 / 10.2
CUDA Capability Major/Minor version number: 5.3
Total amount of global memory: 3956 MBytes (4148387840 bytes)
( 1) Multiprocessors, (128) CUDA Cores/MP: 128 CUDA Cores
GPU Max Clock rate: 922 MHz (0.92 GHz)
Memory Clock rate: 13 Mhz
Memory Bus Width: 64-bit
L2 Cache Size: 262144 bytes
Maximum Texture Dimension Size (x,y,z) 1D=(65536), 2D=(65536, 65536), 3D=(4096, 4096, 4096)
Maximum Layered 1D Texture Size, (num) layers 1D=(16384), 2048 layers
Maximum Layered 2D Texture Size, (num) layers 2D=(16384, 16384), 2048 layers
Total amount of constant memory: 65536 bytes
Total amount of shared memory per block: 49152 bytes
Total number of registers available per block: 32768
Warp size: 32
Maximum number of threads per multiprocessor: 2048
Maximum number of threads per block: 1024
Max dimension size of a thread block (x,y,z): (1024, 1024, 64)
Max dimension size of a grid size (x,y,z): (2147483647, 65535, 65535)
Maximum memory pitch: 2147483647 bytes
Texture alignment: 512 bytes
Concurrent copy and kernel execution: Yes with 1 copy engine(s)
Run time limit on kernels: Yes
Integrated GPU sharing Host Memory: Yes
Support host page-locked memory mapping: Yes
Alignment requirement for Surfaces: Yes
Device has ECC support: Disabled
Device supports Unified Addressing (UVA): Yes
Device supports Compute Preemption: No
Supports Cooperative Kernel Launch: No
Supports MultiDevice Co-op Kernel Launch: No
Device PCI Domain ID / Bus ID / location ID: 0 / 0 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 10.2, CUDA Runtime Version = 10.2, NumDevs = 1
Result = PASS
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/sbsa/cuda-ubuntu1804.pin
sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600
wget https://developer.download.nvidia.com/compute/cuda/11.3.1/local_installers/cuda-repo-ubuntu1804-11-3-local_11.3.1-465.19.01-1_arm64.deb
sudo dpkg -i cuda-repo-ubuntu1804-11-3-local_11.3.1-465.19.01-1_arm64.deb
sudo apt-key add /var/cuda-repo-ubuntu1804-11-3-local/7fa2af80.pub
sudo apt-get update
sudo apt-get -y install cuda
In case you face any dependency issue while executing the last command, run the below fix:
sudo apt-get -o dpkg::Options::="--force-overwrite" install --fix-broken
Setting up libcublas-11-3 (11.5.1.109-1) ...
Setting up nvidia-utils-465 (465.19.01-0ubuntu1) ...
Setting up nvidia-dkms-465 (465.19.01-0ubuntu1) ...
update-initramfs: deferring update (trigger activated)
A modprobe blacklist file has been created at /etc/modprobe.d to prevent Nouveau
from loading. This can be reverted by deleting the following file:
/etc/modprobe.d/nvidia-graphics-drivers.conf
A new initrd image has also been created. To revert, please regenerate your
initrd by running the following command after deleting the modprobe.d file:
`/usr/sbin/initramfs -u`
*****************************************************************************
*** Reboot your computer and verify that the NVIDIA graphics driver can ***
*** be loaded. ***
*****************************************************************************
INFO:Enable nvidia
DEBUG:Parsing /usr/share/ubuntu-drivers-common/quirks/lenovo_thinkpad
DEBUG:Parsing /usr/share/ubuntu-drivers-common/quirks/dell_latitude
DEBUG:Parsing /usr/share/ubuntu-drivers-common/quirks/put_your_quirks_here
Loading new nvidia-465.19.01 DKMS files...
It is likely that 4.9.253-tegra belongs to a chroot's host
Building for 4.15.0-166-generic and 4.9.253-tegra
Building for architecture arm64
Building initial module for 4.15.0-166-generic
Verifying
dpkg -l | grep cuda
ii cuda 11.3.1-1 arm64 CUDA meta-package
ii cuda-11-3 11.3.1-1 arm64 CUDA 11.3 meta-package
ii cuda-command-line-tools-10-2 10.2.460-1 arm64 CUDA command-line tools
ii cuda-command-line-tools-11-3 11.3.1-1 arm64 CUDA command-line tools
ii cuda-compiler-10-2 10.2.460-1 arm64 CUDA compiler
ii cuda-compiler-11-3 11.3.1-1 arm64 CUDA compiler
ii cuda-cudart-10-2 10.2.300-1 arm64 CUDA Runtime native Libraries
ii cuda-cudart-11-0 11.0.194-1 arm64 CUDA Runtime native Libraries
ii cuda-cudart-11-3 11.3.109-1 arm64 CUDA Runtime native Libraries
ii cuda-cudart-dev-10-2 10.2.300-1 arm64 CUDA Runtime native dev links, headers
ii cuda-cudart-dev-11-3 11.3.109-1 arm64 CUDA Runtime native dev links, headers
ii cuda-cuobjdump-10-2 10.2.300-1 arm64 CUDA cuobjdump
ii cuda-cuobjdump-11-3 11.3.58-1 arm64 CUDA cuobjdump
ii cuda-cupti-10-2 10.2.300-1 arm64 CUDA profiling tools runtime libs.
ii cuda-cupti-11-3 11.3.111-1 arm64 CUDA profiling tools runtime libs.
ii cuda-cupti-dev-10-2 10.2.300-1 arm64 CUDA profiling tools interface.
ii cuda-cupti-dev-11-3 11.3.111-1 arm64 CUDA profiling tools interface.
ii cuda-cuxxfilt-11-3 11.3.58-1 arm64 CUDA cuxxfilt
ii cuda-documentation-10-2 10.2.300-1 arm64 CUDA documentation
ii cuda-documentation-11-3 11.3.111-1 arm64 CUDA documentation
ii cuda-driver-dev-10-2 10.2.300-1 arm64 CUDA Driver native dev stub library
ii cuda-driver-dev-11-3 11.3.109-1 arm64 CUDA Driver native dev stub library
ii cuda-drivers 465.19.01-1 arm64 CUDA Driver meta-package, branch-agnostic
ii cuda-drivers-465 465.19.01-1 arm64 CUDA Driver meta-package, branch-specific
ii cuda-gdb-10-2 10.2.300-1 arm64 CUDA-GDB
ii cuda-gdb-11-3 11.3.109-1 arm64 CUDA-GDB
ii cuda-libraries-10-2 10.2.460-1 arm64 CUDA Libraries 10.2 meta-package
ii cuda-libraries-11-3 11.3.1-1 arm64 CUDA Libraries 11.3 meta-package
ii cuda-libraries-dev-10-2 10.2.460-1 arm64 CUDA Libraries 10.2 development meta-package
ii cuda-libraries-dev-11-3 11.3.1-1 arm64 CUDA Libraries 11.3 development meta-package
ii cuda-memcheck-10-2 10.2.300-1 arm64 CUDA-MEMCHECK
ii cuda-nsight-compute-11-3 11.3.1-1 arm64 NVIDIA Nsight Compute
ii cuda-nsight-systems-11-3 11.3.1-1 arm64 NVIDIA Nsight Systems
ii cuda-nvcc-10-2 10.2.300-1 arm64 CUDA nvcc
ii cuda-nvcc-11-3 11.3.109-1 arm64 CUDA nvcc
ii cuda-nvdisasm-10-2 10.2.300-1 arm64 CUDA disassembler
ii cuda-nvdisasm-11-3 11.3.58-1 arm64 CUDA disassembler
ii cuda-nvgraph-10-2 10.2.300-1 arm64 NVGRAPH native runtime libraries
ii cuda-nvgraph-dev-10-2 10.2.300-1 arm64 NVGRAPH native dev links, headers
ii cuda-nvml-dev-10-2 10.2.300-1 arm64 NVML native dev links, headers
ii cuda-nvml-dev-11-3 11.3.58-1 arm64 NVML native dev links, headers
ii cuda-nvprof-10-2 10.2.300-1 arm64 CUDA Profiler tools
ii cuda-nvprof-11-3 11.3.111-1 arm64 CUDA Profiler tools
ii cuda-nvprune-10-2 10.2.300-1 arm64 CUDA nvprune
ii cuda-nvprune-11-3 11.3.58-1 arm64 CUDA nvprune
ii cuda-nvrtc-10-2 10.2.300-1 arm64 NVRTC native runtime libraries
ii cuda-nvrtc-11-3 11.3.109-1 arm64 NVRTC native runtime libraries
ii cuda-nvrtc-dev-10-2 10.2.300-1 arm64 NVRTC native dev links, headers
ii cuda-nvrtc-dev-11-3 11.3.109-1 arm64 NVRTC native dev links, headers
ii cuda-nvtx-10-2 10.2.300-1 arm64 NVIDIA Tools Extension
ii cuda-nvtx-11-3 11.3.109-1 arm64 NVIDIA Tools Extension
ii cuda-repo-ubuntu1804-11-0-local 11.0.2-450.51.05-1 arm64 cuda repository configuration files
ii cuda-repo-ubuntu1804-11-3-local 11.3.1-465.19.01-1 arm64 cuda repository configuration files
ii cuda-runtime-11-3 11.3.1-1 arm64 CUDA Runtime 11.3 meta-package
ii cuda-samples-10-2 10.2.300-1 arm64 CUDA example applications
ii cuda-samples-11-3 11.3.58-1 arm64 CUDA example applications
ii cuda-sanitizer-11-3 11.3.111-1 arm64 CUDA Sanitizer
ii cuda-thrust-11-3 11.3.109-1 arm64 CUDA Thrust
ii cuda-toolkit-10-2 10.2.460-1 arm64 CUDA Toolkit 10.2 meta-package
rc cuda-toolkit-11-0 11.0.2-1 arm64 CUDA Toolkit 11.0 meta-package
ii cuda-toolkit-11-3 11.3.1-1 arm64 CUDA Toolkit 11.3 meta-package
ii cuda-toolkit-11-3-config-common 11.3.109-1 all Common config package for CUDA Toolkit 11.3.
ii cuda-toolkit-11-config-common 11.3.109-1 all Common config package for CUDA Toolkit 11.
ii cuda-toolkit-config-common 11.3.109-1 all Common config package for CUDA Toolkit.
ii cuda-tools-10-2 10.2.460-1 arm64 CUDA Tools meta-package
ii cuda-tools-11-3 11.3.1-1 arm64 CUDA Tools meta-package
ii cuda-visual-tools-10-2 10.2.460-1 arm64 CUDA visual tools
rc cuda-visual-tools-11-0 11.0.2-1 arm64 CUDA visual tools
ii cuda-visual-tools-11-3 11.3.1-1 arm64 CUDA visual tools
ii graphsurgeon-tf 8.0.1-1+cuda10.2 arm64 GraphSurgeon for TensorRT package
ii libcudnn8 8.2.1.32-1+cuda10.2 arm64 cuDNN runtime libraries
ii libcudnn8-dev 8.2.1.32-1+cuda10.2 arm64 cuDNN development libraries and headers
ii libcudnn8-samples 8.2.1.32-1+cuda10.2 arm64 cuDNN documents and samples
ii libnvinfer-bin 8.0.1-1+cuda10.2 arm64 TensorRT binaries
ii libnvinfer-dev 8.0.1-1+cuda10.2 arm64 TensorRT development libraries and headers
ii libnvinfer-doc 8.0.1-1+cuda10.2 all TensorRT documentation
ii libnvinfer-plugin-dev 8.0.1-1+cuda10.2 arm64 TensorRT plugin libraries
ii libnvinfer-plugin8 8.0.1-1+cuda10.2 arm64 TensorRT plugin libraries
ii libnvinfer-samples 8.0.1-1+cuda10.2 all TensorRT samples
ii libnvinfer8 8.0.1-1+cuda10.2 arm64 TensorRT runtime libraries
ii libnvonnxparsers-dev 8.0.1-1+cuda10.2 arm64 TensorRT ONNX libraries
ii libnvonnxparsers8 8.0.1-1+cuda10.2 arm64 TensorRT ONNX libraries
ii libnvparsers-dev 8.0.1-1+cuda10.2 arm64 TensorRT parsers libraries
ii libnvparsers8 8.0.1-1+cuda10.2 arm64 TensorRT parsers libraries
ii nvidia-container-csv-cuda 10.2.460-1 arm64 Jetpack CUDA CSV file
ii nvidia-container-csv-cudnn 8.2.1.32-1+cuda10.2 arm64 Jetpack CUDNN CSV file
ii nvidia-container-csv-tensorrt 8.0.1.6-1+cuda10.2 arm64 Jetpack TensorRT CSV file
ii nvidia-l4t-cuda 32.6.1-20210916211029 arm64 NVIDIA CUDA Package
ii python3-libnvinfer 8.0.1-1+cuda10.2 arm64 Python 3 bindings for TensorRT
ii python3-libnvinfer-dev 8.0.1-1+cuda10.2 arm64 Python 3 development package for TensorRT
ii tensorrt 8.0.1.6-1+cuda10.2 arm64 Meta package of TensorRT
ii uff-converter-tf 8.0.1-1+cuda10.2 arm64 UFF converter for TensorRT package
ajeetraina@ajeetraina-desktop:~$
Setting up PATH variable
cd /usr/local/cuda
cuda/ cuda-10/ cuda-10.2/ cuda-11/ cuda-11.0/ cuda-11.3/
ajeetraina@ajeetraina-desktop:~$ cd /usr/local/cuda^C
ajeetraina@ajeetraina-desktop:~$ export PATH=/usr/local/cuda-11.3/bin${PATH:+:${PATH}}
ajeetraina@ajeetraina-desktop:~$ nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2021 NVIDIA Corporation
Built on Mon_May__3_19:15:10_PDT_2021
Cuda compilation tools, release 11.3, V11.3.109
Build cuda_11.3.r11.3/compiler.29920130_0
ajeetraina@ajeetraina-desktop:~$
Top comments (3)
Still a useful reference, Ajeet - the deviceQuery verification step especially. The Jetson Nano CUDA 10.2 + TensorRT 8 stack described here is battle-tested.
For anyone on a newer Jetson Orin Nano: the process is broadly similar via JetPack, but key differences:
dpkg::Options force-overwritefix is still sometimes needed when mixing JetPack versionsnvcc --versionpath is the same sanity checktegrastatsto baseline thermal/power before loading heavy CUDA workloadsWe run OpenClaw on the Jetson Orin Nano and the CUDA stack enables local inference (llama.cpp with CUDA backend). The jump from the original Nano (128 CUDA cores, 4GB) to Orin Nano (1024 CUDA cores, 8GB) is genuinely dramatic.
Saw your NanoClaw article too - great to see OpenClaw in the Docker ecosystem!
Thanks, this is exactly what I was looking for as I'm in the process of creating a custom image for my Jetson Nano cluster and like to pick what I want loaded instead of using the Jetson JetPack where you can't really decide on what will or won't be installed.
Ajeet, you saving my days, thank you, this what I was looking for, finally I successed install cuda on my jetson nano