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

dvf

class Blockchain(object):
    def __init__(self):
        self.chain = []
        self.current_transactions = []
        
    def new_block(self):
        # Creates a new Block and adds it to the chain
        pass
    
    def new_transaction(self):

rspeer

rondy

FWIW: I (@rondy) am not the creator of the content shared here, which is an excerpt from Edmond Lau's book. I simply copied and pasted it from another location and saved it as a personal note, before it gained popularity on news.ycombinator.com. Unfortunately, I cannot recall the exact origin of the original source, nor was I able to find the author's name, so I am can't provide the appropriate credits.

---

Effective Engineer - Notes

• By Edmond Lau
• Highly Recommended 👍
• http://www.theeffectiveengineer.com/

What's an Effective Engineer?

Skehmatics

#!/bin/bash

# export DBUS_SESSION_BUS_ADDRESS environment variable because cron hates me
PID=$(pgrep -u USER gnome-session-b)
export DBUS_SESSION_BUS_ADDRESS=$(grep -z DBUS_SESSION_BUS_ADDRESS /proc/$PID/environ|cut -d= -f2-)

/usr/bin/gsettings set org.gnome.shell.extensions.user-theme name 'Flat-Plat'
/usr/bin/gsettings set org.gnome.desktop.interface gtk-theme 'Flat-Plat'
/usr/bin/gsettings set org.gnome.desktop.background picture-uri 'file://WALLPAPER-PATH'
/usr/bin/gsettings --schemadir ~/.local/share/gnome-shell/extensions/drop-down-terminal@gs-extensions.zzrough.org set org.zzrough.gs-extensions.drop-down-terminal background-color 'rgb(69,90,100)'

cdfpaz

#include <stdio.h>
#include <math.h>

const double Pi = 3.14159265359;

// Standard Normal probability density function
// Normal PDF(x) = exp(-x*x/2)/{sigma * sqrt(2 * Pi) }
double Normal_PDF(const double & x) {
    return (1.0/(double)pow(2 * Pi, 0.5)) * exp(-0.5 * x * x); 
}

jakevdp

# By Jake VanderPlas
# License: BSD-style

import matplotlib.pyplot as plt
import numpy as np


def discrete_cmap(N, base_cmap=None):
    """Create an N-bin discrete colormap from the specified input map"""

brentp

from sklearn import linear_model
from scipy import stats
import numpy as np


class LinearRegression(linear_model.LinearRegression):
    """
    LinearRegression class after sklearn's, but calculate t-statistics
    and p-values for model coefficients (betas).
    Additional attributes available after .fit()

aflaxman

from pylab import *

def cface(ax, x1,x2,x3,x4,x5,x6,x7,x8,x9,x10,x11,x12,x13,x14,x15,x16,x17,x18):
    # x1 = height  of upper face
    # x2 = overlap of lower face
    # x3 = half of vertical size of face
    # x4 = width of upper face
    # x5 = width of lower face
    # x6 = length of nose
    # x7 = vertical position of mouth

ckirkendall

(use '[clojure.core.match :only [match]])

(defn evaluate [env [sym x y]]
  (match [sym]
    ['Number]   x
    ['Add]      (+ (evaluate env x) (evaluate env y))
    ['Multiply] (* (evaluate env x) (evaluate env y))
    ['Variable] (env x)))
    
(def environment {"a" 3, "b" 4, "c" 5})