Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
R High Performance Programming

You're reading from   R High Performance Programming Overcome performance difficulties in R with a range of exciting techniques and solutions

Arrow left icon
Product type Paperback
Published in Jan 2015
Publisher
ISBN-13 9781783989263
Length 176 pages
Edition 1st Edition
Languages
Arrow right icon
Authors (2):
Arrow left icon
Tjhi W Chandra Tjhi W Chandra
Author Profile Icon Tjhi W Chandra
Tjhi W Chandra
Aloysius Shao Qin Lim Aloysius Shao Qin Lim
Author Profile Icon Aloysius Shao Qin Lim
Aloysius Shao Qin Lim
Arrow right icon
View More author details
Toc

Table of Contents (12) Chapters Close

Preface 1. Understanding R's Performance – Why Are R Programs Sometimes Slow? FREE CHAPTER 2. Profiling – Measuring Code's Performance 3. Simple Tweaks to Make R Run Faster 4. Using Compiled Code for Greater Speed 5. Using GPUs to Run R Even Faster 6. Simple Tweaks to Use Less RAM 7. Processing Large Datasets with Limited RAM 8. Multiplying Performance with Parallel Computing 9. Offloading Data Processing to Database Systems 10. R and Big Data Index

Monitoring memory utilization, CPU utilization, and disk I/O using OS tools

Unlike execution time, R does not provide any good tools to profile CPU utilization and disk I/O. Even the memory profiling tools in R might not provide a complete or accurate picture. This is where we turn to OS-provided system monitoring tools to keep an eye on the computational resources as we run R programs. They are task manager or resource monitor in Windows, activity monitor in Mac OS X, and top in Linux. When running these tools, look for the processes that represent R (usually called R or rsession).

The information that we get varies depending on the operating system, but here are the key measures of R's resource utilization to keep an eye on:

  • % CPU or CPU usage: The percentage of the system's CPU time used by R
  • % memory, resident memory, or working set: The percentage of the system's physical memory used by R
  • Swap size or page outs: The size of memory used by R that is stored in the operating...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image