Jetson Nano Developer Kit BO1

# NVIDIA Ampere architecture with 1024 NVIDIA® CUDA® cores with 32 tensor cores
# 6-core Arm® Cortex-A78AE v8.2
# 64-bit CPU
# 8GB 128-bit LPDDR5 68 GB/s
# Supports for external NVMe
$ lscpu
Architecture:        aarch64
Byte Order:          Little Endian
CPU(s):              4
On-line CPU(s) list: 0-3
Thread(s) per core:  1
Core(s) per socket:  4
Socket(s):           1
Vendor ID:           ARM
Model:               1
Model name:          Cortex-A57
Stepping:            r1p1
CPU max MHz:         1479.0000
CPU min MHz:         102.0000
BogoMIPS:            38.40
L1d cache:           32K
L1i cache:           48K
L2 cache:            2048K
Flags:               fp asimd evtstrm aes pmull sha1 sha2 crc32

• how to check floating-point strategy on aarch64？ When compiling your code, look for the -mfloat-abi flag in the command line
• how to check MMU Page Size on aarch64？ https://stackoverflow.com/questions/53051886/mmu-long-descriptor-page-table-sizes-in-aarch64
• how to check binutils version on aarch64? ld -v https://stackoverflow.com/questions/23604949/how-to-see-what-version-of-binutils-is-on-ubuntu

Datasheet

Jetson.GPIO /opt/nvidia/jetson-gpio/doc/README.txt

JetPack

JetPack libraries and APIs include:

• TensorRT and cuDNN for high-performance deep learning applications
• CUDA for GPU accelerated applications across multiple domains
• NVIDIA Container Runtime for containerized GPU accelerated applications
• Multimedia API package for camera applications and sensor driver development
• VisionWorks, OpenCV, and VPI (Developer Preview) for visual computing applications
• Sample applications

JetPack component	Sample locations on reference filesystem
TensorRT	/usr/src/tensorrt/samples/
cuDNN	/usr/src/cudnnsamples/
CUDA	/usr/local/cuda-/samples/
Multimedia API	/usr/src/tegra_multimedia_api/
VisionWorks	/usr/share/visionworks/sources/samples/ /usr/share/visionworks-tracking/sources/samples/ /usr/share/visionworks-sfm/sources/samples/
OpenCV	/usr/share/OpenCV/samples/
VPI	/opt/nvidia/vpi/vpi-0.0/samples

Jetson Linux Driver Package

NVIDIA® Jetson™ Linux Driver Package (L4T) is the operating system component of JetPack, and provides the Linux kernel, Bootloader, Jetson Board Support Package (BSP), and sample filesystem for Jetson developer kits. L4T is included on the Jetson Nano SD Card image. Alternatively, you can use SDK Manager to install L4T along with all the other JetPack components to your developer kit.

J48

Enables either J28 Micro-USB connector or J25 power jack as power source for the developer kit. Without a jumper, the developer kit can be powered by J28 MicroUSB connector. With a jumper, no power is drawn from J28, and the developer kit can be powered via J25 power jack.

• J25 input: 5V, 4A
• Car input: 8.4V, 2A
• Car battery: 4.2v, 0.45A

Jetbot Setup

• Getting Start
• Software setup - docker
• Navtive setup

Docker Container

# USB camera option:
sudo docker run --runtime nvidia -it --rm --network host \
 --volume ~/nvdli-data:/nvdli-nano/data \
 --device /dev/video0 \ 
 nvcr.io/nvidia/dli/dli-nano-ai:v2.0.2-r32.7.1
# CSI camera option:
sudo docker run --runtime nvidia -it --rm --network host \
 --volume ~/nvdli-data:/nvdli-nano/data \
 --volume /tmp/argus_socket:/tmp/argus_socket \
 --device /dev/video0 \
 nvcr.io/nvidia/dli/dli-nano-ai:v2.0.2-r32.7.1

# allow 10 sec for JupyterLab to start @ http://192.168.55.1:8888 (password dlinano)
# JupterLab logging location: /var/log/jupyter.log (inside the container)