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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

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Product type Paperback
Published in Jan 2015
Publisher
ISBN-13 9781783989263
Length 176 pages
Edition 1st Edition
Languages
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Authors (2):
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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
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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

Index

A

  • active data
    • and non-active data, swapping / Swapping active and nonactive data
  • algorithm design affects
    • time complexity / Algorithm design affects time and space complexity
    • space complexity / Algorithm design affects time and space complexity
  • Amazon Machine Images (AMIs)
    • about / Installing gputools
  • Amazon Web Services (AWS)
    • about / Installing gputools
    • Hadoop, setting on / Setting up Hadoop on Amazon Web Services
  • Amdahl's law
    • about / Data parallelism versus task parallelism
  • array databases
    • using / Using array databases for maximum scientific-computing performance

B

  • batch processing
    • about / Processing large datasets in batches using Hadoop
  • big.matrix object
    • about / The bigmemory package
  • bigmemory package
    • using / The bigmemory package
  • bit vectors
    • using / Bit vectors
  • built-in functions
    • using / Use of built-in functions

C

  • cfunction() function...
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