john-science

Latency Comparison Numbers (~2012)
----------------------------------
L1 cache reference                           0.5 ns
Branch mispredict                            5   ns
L2 cache reference                           7   ns                      14x L1 cache
Mutex lock/unlock                           25   ns
Main memory reference                      100   ns                      20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy             3,000   ns        3 us
Send 1K bytes over 1 Gbps network       10,000   ns       10 us
Read 4K randomly from SSD*             150,000   ns      150 us          ~1GB/sec SSD

kirkegaard

import os
import time
import sched
import threading
import inquirer


class Tamagotchi:
    age = 0
    bored = 0

john-science

Buttermilk Biscuits

Makes 12 2 ½” biscuits

This is a recipe for fluffy biscuits, not flakey. They are best straight out of the oven with butter or jam. Always make extra, they are great split, buttered, and griddled for breakfast sandwiches. We use a food processor to mix the butter and flour. You can use your hands or a fork but using the food processor helps to keep the butter cold which will help make tender biscuits (and it is much faster & more uniform).

Equipment

• food processor
• 2 ½” round biscuit cutter

magnetikonline

List all Git repository objects by size

• Summary
• Example

Summary

Bash script to:

• Iterate all commits made within a Git repository.

john-science

Smallest Lenses Adaptable to the Sony a7

This has been moved to a blog post.

john-science

/**
 * A quick example of using Emoji in Java.
 * compile with: javac HelloWorld.java
 * run with:     java HelloWorld
 */

public class HelloWorld {

    public static void main(String[] args) {
        String \u0ca2 = "Hello, World 1";

pathikrit

val n = 9
val s = Math.sqrt(n).toInt
type Board = IndexedSeq[IndexedSeq[Int]]
 
def solve(board: Board, cell: Int = 0): Option[Board] = (cell%n, cell/n) match {
  case (r, `n`) => Some(board)
  case (r, c) if board(r)(c) > 0 => solve(board, cell + 1)
  case (r, c) =>
    def guess(x: Int) = solve(board.updated(r, board(r).updated(c, x)), cell + 1)  
    val used = board.indices.flatMap(i => Seq(board(r)(i), board(i)(c), board(s*(r/s) + i/s)(s*(c/s) + i%s)))

bonzanini

# You need to install scikit-learn:
# sudo pip install scikit-learn
#
# Dataset: Polarity dataset v2.0
# http://www.cs.cornell.edu/people/pabo/movie-review-data/
#
# Full discussion:
# https://marcobonzanini.wordpress.com/2015/01/19/sentiment-analysis-with-python-and-scikit-learn

PaulKinlan

(function() { 
  var CSSCriticalPath = function(w, d, opts) {
    var opt = opts || {};
    var css = {};
    var pushCSS = function(r) {
      if(!!css[r.selectorText] === false) css[r.selectorText] = {};
      var styles = r.style.cssText.split(/;(?![A-Za-z0-9])/);
      for(var i = 0; i < styles.length; i++) {
        if(!!styles[i] === false) continue;
        var pair = styles[i].split(": ");

jboner

Latency Comparison Numbers (~2012)
----------------------------------
L1 cache reference                           0.5 ns
Branch mispredict                            5   ns
L2 cache reference                           7   ns                      14x L1 cache
Mutex lock/unlock                           25   ns
Main memory reference                      100   ns                      20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy             3,000   ns        3 us
Send 1K bytes over 1 Gbps network       10,000   ns       10 us
Read 4K randomly from SSD*             150,000   ns      150 us          ~1GB/sec SSD