jctosta

You can use the following commands to limit the maximum power allowed to your NVIDIA GPU when using linux systems.

First, let's check how much power the GPU is allowed to draw and the current value:

nvidia-smi -q -d POWER

This should return an output similar to this one:

MihailCosmin

#!/bin/bash

### steps ####
# verify the system has a cuda-capable gpu
# download and install the nvidia cuda toolkit and cudnn
# setup environmental variables
# verify the installation
###

### to verify your gpu is cuda enable check

robhrt7

This is a fork of original gist https://gist.github.com/nrollr/3f57fc15ded7dddddcc4e82fe137b58e, with slight changes on pointing to 5.7 version branch, instead of 8 (latest default of MySQL in Hombrew).

Install MySQL 5.7 on macOS

This procedure explains how to install MySQL using Homebrew on macOS (Sierra 10.12 and up)

Install Homebrew

• Installing Homebrew is effortless, open Terminal and enter :
  $ /usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
• Note: Homebrew will download and install Command Line Tools for Xcode 8.0 as part of the installation process.

jdesive

Mount Synology NFS share to Ubuntu 16.04

I have all hardware virtualized in ESXi 6.5...
Synology DSM 5.2-5644
Ubuntu 16.04

Start

On your fresh install on Ubuntu 16.04:

1. Click the Connections icon on the top bar
2. Goto Edit Connections

swyoon

import numpy as np
import tensorflow as tf

__author__ = "Sangwoong Yoon"

def np_to_tfrecords(X, Y, file_path_prefix, verbose=True):
    """
    Converts a Numpy array (or two Numpy arrays) into a tfrecord file.
    For supervised learning, feed training inputs to X and training labels to Y.
    For unsupervised learning, only feed training inputs to X, and feed None to Y.

WIStudent

Compiling DeepMatching's GPU version on Ubuntu 16.10

DeepMatching is an algorithm that finds corresponding points in two images. Its GPU implementation was written for Fedora 21, which makes things a bit more difficult if you want to run it on an Ubuntu system. This document contains step-by-step instructions on how to get DeepMatching running on Ubuntu 16.10. I only tested it with Ubuntu 16.10, just let me know if it works with previous versions too.

To compile the GPU version you first need to compile the Caffe version that is included that comes with the DeepMatching files. Newer versions of Caffe won't work because Caffe changed the structure of its header files.

Compiling Caffe

Before compiling Caffe we need to make sure all its dependencies are installed. From the installation guide for Ubuntu 16.04/15.10:

sudo apt-get install build-essential cmake git pkg-config

kylemcdonald

#include "ofMain.h"
#include "ofxTiming.h"

class ofApp : public ofBaseApp {
public:
    ofVideoGrabber grabber;
    DelayTimer delay;
    ofTrueTypeFont font;
    string description;
    

karpathy

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)