trungnt13

#!/bin/sh
# Add some niceties for a new NVIDIA Jetson TK1 - LT 19.3
# sudo ./configureJetsonTK1.sh 
# Note:
# -- Check DNS in /etc/resolv.conf if cannot connect to ports.ubuntu.com
# -- a
 
# Don't allow apt-get upgrade of xorg overwrite libglx.so
# May be fixed in future versions of LT4
sudo apt-mark hold xserver-xorg-core

trungnt13

wget https://bootstrap.pypa.io/get-pip.py
sudo python get-pip.py
sudo apt-get install python-numpy python-scipy python-matplotlib ipython ipython-notebook python-pandas python-sympy python-nose
sudo pip install Theano ; sudo pip install pymc ; sudo pip install pycrypto ; sudo pip install Cython ; sudo pip install image;
sudo pip install Scrapy ;sudo pip install virtualenv; sudo pip install virtualenv-clone; sudo pip install virtualenvwrapper;
sudo pip install h5py;sudo pip install xlwt;sudo pip install lxml ;sudo pip install colorama; sudo pip install PyDot;
sudo pip install scikits.audiolab;
sudo pip install paramiko; sudo pip install readchar;

trungnt13

Full tutorial of start a Jetson TK1: http://myzharbot.robot-home.it/blog/software/configuration-nvidia-jetson-tk1/

trungnt13

##############################################################
# Client
##############################################################
mkdir [repo] && cd [repo]
git init
git add -A
git commit -m "Init git repo"

##############################################################
# Server

trungnt13

# Download: prebuilt spark+hadoop
From: https://spark.apache.org/downloads.html
Prefer prebuilt version, easier to deploy to all worker
 
# Configuration
1. Slaves configuration

* Client: 

 sudo adduser worker

trungnt13

import theano
import theano.tensor as T
from theano.sandbox.rng_mrg import MRG_RandomStreams as RandomStreams
from theano.tensor.signal.downsample import max_pool_2d
from theano.tensor.extra_ops import repeat
from theano.sandbox.cuda.dnn import dnn_conv

from time import time
import numpy as np
from matplotlib import pyplot as plt

trungnt13

import os
import numpy as np
from matplotlib import pyplot as plt
from time import time

from foxhound import activations
from foxhound import updates
from foxhound import inits
from foxhound.theano_utils import floatX, sharedX

trungnt13

#!/usr/bin/env python

"""
Pass data between processes started through the multiprocessing module
using pyzmq and process them with PyCUDA
"""

import numpy as np
import zmq
import multiprocessing as mp

trungnt13

module purge
module load cmake/3.3.2
module load cuda/7.5
module load gcc/4.9.1
module load git
module load openblas

trungnt13

These instructions will explain how to install tensorflow on mac with cuda enabled GPU suport. I assume you know what tensorflow is and why you would want to have a deep learning framework running on your computer.

Prerequisites

Make sure to update your homebrew formulas

brew update