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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

rava-dosa

/// This is not written to compile. I just copied everything into one file to make viewing easy
/// Here is a sample usage (task definitions and implementations omitted)

int main()
{
    TaskScheduler scheduler;
    MyTaskA taskA;
    MyTaskB taskB;

    BOOL running = true

rava-dosa

{
    "Shoe": [
        {
            "Women": [
                {
                    "Sandals": [
                        {
                            "Slide": [
                                {
                                    "id": "1",

rava-dosa

Setting up for Deep Learning on Ubuntu 14.04

Saving this so I can find it later & potentially help others. This sets up the latest as of 10/7/2017

• Python
• Keras
• Tensorflow
• PyTorch

Assumes Anaconda3 is installed. Here is mine:

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• The Dataflow Model: A Practical Approach to Balancing Correctness, Latency, and Cost in Massive-Scale, Unbounded, Out-of-Order Data Processing
  By Google (Akidau et al)
  In Proceedings of the VLDB Endowment, Vol. 8, No. 12
  August 2015
  http://www.vldb.org/pvldb/vol8/p1792-Akidau.pdf

• MillWheel: Fault-Tolerant Stream Processing at Internet Scale
  By Google (Akidau et al)

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Backend Development

• node.js
  • Installation paths: use one of these techniques to install node and npm without having to sudo.
  • Node.js HOWTO: Install Node+NPM as user (not root) under Unix OSes
  • Felix's Node.js Guide
  • Creating a REST API using Node.js, Express, and MongoDB
  • Node Cellar Sample Application with Backbone.js, Twitter Bootstrap, Node.js, Express, and MongoDB
  • JavaScript Event Loop
• Node.js for PHP programmers

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/* 
  A Minimal Capture Program

  This program opens an audio interface for capture, configures it for
  stereo, 16 bit, 44.1kHz, interleaved conventional read/write
  access. Then its reads a chunk of random data from it, and exits. It
  isn't meant to be a real program.

  From on Paul David's tutorial : http://equalarea.com/paul/alsa-audio.html

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##first, grab our tarball for 32bit
wget http://c758482.r82.cf2.rackcdn.com/Sublime%20Text%202.0.2.tar.bz2
for 64bit
wget http://c758482.r82.cf2.rackcdn.com/Sublime%20Text%202.0.2%20x64.tar.bz2

##create your personal apps folder mkdir ~/apps ##extract sublime text into your apps folder tar -xvzf Sublime*.tar.bz2 -C ~/apps/

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# Remove unused images

docker rmi -f $(docker images | grep "<none>" | awk "{print \$3}")

# Remove dangling images
docker rmi $(docker images --filter "dangling=true" -q --no-trunc)

# Ejecutar bash dentro de un servicio docker

$ docker-compose exec <service id> bash

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/**
 * OpenCV video streaming over TCP/IP
 * Client: Receives video from server and display it
 * by Steve Tuenkam
 */

#include "opencv2/opencv.hpp"
#include <sys/socket.h> 
#include <arpa/inet.h>
#include <unistd.h>