# Performance

## Simple multiprocessing in R

Continuing my effort to help you get the most out of your CPUs, I figured we could look into using some multiprocessing functionality available for your R scripts. While there are a few different options for running multi-core treatments on your data, we'll focus on something really simple to put in place. A while back, I was putting together a script to run a large series of logistic regressions (using the glm package) in an attempt to model some data. [...]

By | 2017-04-29T15:33:26+00:00 March 14, 2016|Categories: Performance, R|Tags: |0 Comments

## Factorial and Log Factorial

Factorial: When you need to calculate n!, you have several solutions.  The "rush" solution: using a loop or a recursive function:  def factorial_for(n): r = 1 for i in range(2, n + 1): r *= i return(r) def factorial_rec(n): if n > 1: return(n * factorial_rec(n - 1)) else: return(1) Here, the multiplication of the numbers sequentially will create a huge number very quickly. This is good, but computers are faster when 2 small numbers (120x30240) are involved in a multiplication versus the [...]

By | 2017-04-29T15:33:07+00:00 February 22, 2016|Categories: Performance, Python|Tags: |0 Comments

## What’s the fastest? – R edition

When I started using R, about ten years ago, the community was much smaller. No R-bloggers to get inspired or ggplot2 to make nice graphs. It was the beginning of an other implementation of R (other than CRAN's) known as Revolution R from Revolution Analytics. Their R targeted enterprise and was designed to be faster and more scalable. They also offer an open source version of their product called RRO. In April 2015, the company was acquired by Microsoft! May [...]

By | 2017-04-29T15:32:29+00:00 February 12, 2016|Categories: Performance, R|0 Comments

## [Python] Iterators vs Generators

In Python, there are iterators and generators. You probably already use iterators without even knowing that you do so. But understanding the difference between those two concepts is really important since choosing one over the other has a huge impact on memory usage. If you are working with small datasets, memory usage might not be your first concern. However, with big datasets, it is another story. So what are they exactly, iterators and generators? Iterators The process of going through [...]

By | 2017-04-29T15:37:35+00:00 September 18, 2015|Categories: Performance, Python|0 Comments

## Put Those CPUs to Good Use !

If you're like me, you've probably noticed that, by default, the python scripts we write only use a portion of the processing power at our disposal.. As such, you've probably said to yourself: Hey, I paid good money for a quad-core CPU ! What's happening ? While it's true that nowadays, most CPUs are multi-core, the code we write must also be tailored appropriately in order to make use of more than one at a time. So let's dive into [...]

By | 2017-04-24T13:28:50+00:00 July 12, 2015|Categories: Performance, Python|Tags: |0 Comments