This document contains useful software and links to documentation that we have found to be useful when working with Jetson AGX Xavier.
Copied from: https://git.its.aau.dk/WW82ZE/docs_xavier/src/branch/master
Nvidia Developer forum Jetson AGX Xavier topic
Jetson Community Projects
| # https://doc.ubuntu-fr.org/wakeonlan | |
| # check if your target pc is wake-on-lan enabled: | |
| sudo ethtool enp8s0 | egrep "^[[:blank:]]*Wake-on: (g|d)" | |
| # you should have: | |
| # Wake-on: g | |
| # get target pc mac address | |
| ifconfig enp8s0 |
| # https://raspberrypi.stackexchange.com/questions/117632/turn-off-external-leds-on-raspberry-pi-3 | |
| # check model | |
| cat /sys/firmware/devicetree/base/model | |
| # Raspberry Pi 3 Model B Rev 1.2 | |
| # Disable Power (red) and Activity (yellow) leds | |
| sudo nano /etc/rc.local | |
| # Add the following lines before `exit 0`: | |
| sudo sh -c 'echo none > /sys/class/leds/led0/trigger' |
| sudo apt install xorg-dev libssl-dev qtbase5-dev libgdk-pixbuf2.0-dev libnotify-dev qttools5-dev-tools qttools5-dev | |
| git clone https://github.com/symless/synergy-core.git | |
| cd synergy-core | |
| mkdir build | |
| cd build | |
| cmake .. | |
| make | |
| # https://github.com/symless/synergy-core/wiki/Command-Line | |
| # ./bin/synergyc $SYNERGY_SERVER_IP |
Basic tutorial 10: GStreamer tools
# (optional)
$ export GST_PLUGIN_PATH=/usr/lib/aarch64-linux-gnu/gstreamer-1.0:/usr/lib/aarch64-linux-gnu/gstreamer-1.0/deepstream
$ apt list --installed | grep streamer
| # https://github.com/ShigekiKarita/pytorch-distributed-slurm-example/blob/master/main_distributed.py | |
| # lauch 2 gpus x 2 nodes (= 4 gpus) | |
| # srun -N2 -p gpu --gres gpu:2 python main_distributed.py --dist-backend nccl --multiprocessing-distributed --dist-file dist_file | |
| import argparse | |
| import os | |
| import random | |
| import shutil | |
| import time | |
| import warnings | |
| import sys |
| import os | |
| import multiprocessing | |
| import torch | |
| import torch.nn.functional as F | |
| import torchmetrics | |
| import pytorch_lightning as pl | |
| from argparse import ArgumentParser | |
| from torch import nn |
| """ | |
| Created on Sat Sep 28 00:47:38 2019 | |
| @author: Kenan Kilictepe (Entegral / www.entegral.com.tr) | |
| """ | |
| import numba | |
| from numba import cuda | |
| import numpy as np | |
| from pdb import set_trace |
| '''Trains a simple convnet on the MNIST dataset. | |
| Gets to 99.25% test accuracy after 12 epochs | |
| (there is still a lot of margin for parameter tuning). | |
| 16 seconds per epoch on a GRID K520 GPU. | |
| ''' | |
| import keras | |
| from keras.datasets import mnist | |
| from keras.models import Sequential |