nadavrot

High-Performance Matrix Multiplication

This is a short post that explains how to write a high-performance matrix multiplication program on modern processors. In this tutorial I will use a single core of the Skylake-client CPU with AVX2, but the principles in this post also apply to other processors with different instruction sets (such as AVX512).

Intro

Matrix multiplication is a mathematical operation that defines the product of

bradtraversy

Wordpress & Docker

This file will setup Wordpress, MySQL & PHPMyAdmin with a single command. Add the code below to a file called "docker-compose.yaml" and run the command

$ docker-compose up -d

# To Tear Down
$ docker-compose down --volumes

branneman

Better local require() paths for Node.js

Problem

When the directory structure of your Node.js application (not library!) has some depth, you end up with a lot of annoying relative paths in your require calls like:

const Article = require('../../../../app/models/article');

Those suck for maintenance and they're ugly.

Possible solutions

zziuni

# source : http://code.google.com/p/natvpn/source/browse/trunk/stun_server_list
# A list of available STUN server.

stun.l.google.com:19302
stun1.l.google.com:19302
stun2.l.google.com:19302
stun3.l.google.com:19302
stun4.l.google.com:19302
stun01.sipphone.com
stun.ekiga.net

domenic

Auto-deploying built products to gh-pages with GitHub Actions

This is a set up for projects which want to check in only their source files, but have their gh-pages branch automatically updated with some compiled output every time they push.

A file below this one contains the steps for doing this with Travis CI. However, these days I recommend GitHub Actions, for the following reasons:

• It is much easier and requires less steps, because you are already authenticated with GitHub, so you don't need to share secret keys across services like you do when coordinate Travis CI and GitHub.
• It is free, with no quotas.
• Anecdotally, builds are much faster with GitHub Actions than with Travis CI, especially in terms of time spent waiting for a builder.

yetithefoot

{url:'stun:stun01.sipphone.com'},
{url:'stun:stun.ekiga.net'},
{url:'stun:stun.fwdnet.net'},
{url:'stun:stun.ideasip.com'},
{url:'stun:stun.iptel.org'},
{url:'stun:stun.rixtelecom.se'},
{url:'stun:stun.schlund.de'},
{url:'stun:stun.l.google.com:19302'},
{url:'stun:stun1.l.google.com:19302'},
{url:'stun:stun2.l.google.com:19302'},

y-yoi

import click
import requests

template = u"""/*
Name: {name}
Description: {description}
Data source: {data_source}
Created By: {created_by}
Last Update At: {last_updated_at}
*/

AlexeyKupershtokh

select
    concat(
        'create table ',
        table_name,
        '(',
        string_agg(
                concat(
                        column_name,
                        ' ',
                        CASE when is_nullable = 'YES' THEN 'Nullable(' END,

debasishg

General Background and Overview

1. Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
2. Models and Issues in Data Stream Systems
3. Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
4. Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
5. [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t

Arachnid

import bisect

class NFA(object):
  EPSILON = object()
  ANY = object()
  
  def __init__(self, start_state):
    self.transitions = {}
    self.final_states = set()
    self._start_state = start_state