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 (1)
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.