Alexei Matusevski shmalex

Prevent NVIDIA GPUs' throttling on headless server

Unlock manual fan & overclock settings
sudo nvidia-xconfig -a --cool-bits=28 --allow-empty-initial-configuration
Reboot system
Create script /usr/local/bin/gpu-fan-control.sh

#!/bin/bash

I am moving this gist to a github repo so more people can contribute to it. Also, it makes it easier for me to version control.

Please go to - https://github.com/praveenpuglia/shadow-dom-in-depth for latest version of this document. Also, if you find the document useful, please shower your love, go ⭐️ it. :)

Shadow DOM

Heads Up! It's all about the V1 Spec.

In a nutshell, Shadow DOM enables local scoping for HTML & CSS.

This will create a proxy server in whatever your availability zone your VPC is in. For me, that's us-east-1b. For you, that may be something different. Steps 10+ should more or less work regardless of your provider since those steps cover the setup and configuration of TinyProxy.

Click the Launch Instance button.
Choose Ubuntu Server 14.04 LTS (HVM), SSD Volume Type. This isn't strictly necessary. If you choose another OS, check its documentation for how to install new packages.
On the Choose an Instance Type screen, select t2.micro. It's Free Tier eligible.
Click the Next: ... buttons until you reach the Configure Security Group screen.
- You may wish to reduce the amount of storage on the Add Storage screen. This is optional.
- You may wish to add a tag on the Tag Instance screen. This is also optional.
On the Configure Security Group screen:

Select Create a new security group.


	# https://stackoverflow.com/questions/39928401/recover-db-password-stored-in-my-dbeaver-connection

	# requires pycryptodome lib (pip install pycryptodome)

	import sys
	import base64
	import os
	import json
	from Crypto.Cipher import AES

	// create a bookmark and use this code as the URL, you can now toggle the css on/off
	// thanks+credit: https://dev.to/gajus/my-favorite-css-hack-32g3
	javascript: (function() {
	var elements = document.body.getElementsByTagName('*');
	var items = [];
	for (var i = 0; i < elements.length; i++) {
	if (elements[i].innerHTML.indexOf('* { background:#000!important;color:#0f0!important;outline:solid #f00 1px!important; background-color: rgba(255,0,0,.2) !important; }') != -1) {
	items.push(elements[i]);
	}
	}

	import matplotlib.pyplot as plt
	import numpy as np

	def show_images(images, cols = 1, titles = None):
	"""Display a list of images in a single figure with matplotlib.

	Parameters
	---------
	images: List of np.arrays compatible with plt.imshow.

	#!/usr/bin/env node

	const NKEYS = 4;

	function arrayOfSize(size) {
	var a = Array(size);

	for (var i = 0; i < size; i += 1)
	a[i] = null;

	"""
	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)