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

spicycode

# 0 is too far from ` ;)
set -g base-index 1

# Automatically set window title
set-window-option -g automatic-rename on
set-option -g set-titles on

#set -g default-terminal screen-256color
set -g status-keys vi
set -g history-limit 10000

thomd

alternatively use: http://geoff.greer.fm/lscolors/

LSCOLORS

The value of this variable describes what color to use for which attribute when colors are enabled with CLICOLOR. This string is a concatenation of pairs of the format fb, where f is the foreground color and b is the background color.

The color designators are as follows:

a black

khardix

#!/usr/bin/env python3.6

import asyncio
from contextlib import closing

import aiohttp
import tqdm


async def download(session, url, progress_queue):

yang-wei

When receiving JSON data from other resources(server API etc), we need Json.Decode to convert the JSON values into Elm values. This gist let you quickly learn how to do that.

I like to follow working example code so this is how the boilerplate will look like:

import Graphics.Element exposing (Element, show)
import Task exposing (Task, andThen)
import Json.Decode exposing (Decoder, int, string, object3, (:=))

import Http

simme

# First install tmux
brew install tmux

# For mouse support (for switching panes and windows)
# Only needed if you are using Terminal.app (iTerm has mouse support)
Install http://www.culater.net/software/SIMBL/SIMBL.php
Then install https://bitheap.org/mouseterm/

# More on mouse support http://floriancrouzat.net/2010/07/run-tmux-with-mouse-support-in-mac-os-x-terminal-app/

hfreire

# Install QEMU OSX port with ARM support
sudo port install qemu +target_arm
export QEMU=$(which qemu-system-arm)

# Dowload kernel and export location
curl -OL \
https://github.com/dhruvvyas90/qemu-rpi-kernel/blob/master/kernel-qemu-4.1.7-jessie
export RPI_KERNEL=./kernel-qemu-4.1.7-jessie

# Download filesystem and export location

max-mapper

mixxorz

"""
MIT License

Copyright (c) 2018 Mitchel Cabuloy

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is

karpathy

"""
A bare bones examples of optimizing a black-box function (f) using
Natural Evolution Strategies (NES), where the parameter distribution is a 
gaussian of fixed standard deviation.
"""

import numpy as np
np.random.seed(0)

# the function we want to optimize