DOWNLOAD R High Performance Programming
FREE READ R High Performance Programming ↠ E-book, or Kindle E-pub It the performance of R programs Optimize R code to run faster and use less memory Use compiled code in R and other languages such as C to speed up computations Harness the power of GPUs for computational speed Process data sets that are larger than memory using disk based memory and chunking Tap into the capacity of multiple CPUs using parallel computing Leverage the power of advanced database systems and Big Data tools from within R In Detail With the increasing use of information in all areas of business and science R provides an easy and powerful way to analyze and process the vast amounts of data involved It is one of the most popular tools today for faster data exploration statistical analysis and statis.READ Ä E-book, or Kindle E-pub Ë Aloysius Lim
FREE READ R High Performance Programming ↠ E-book, or Kindle E-pub Overcome performance difficulties in R with a range of exciting techniues and solutions About This Book Benchmark and profile R programs to solve performance bottlenecks Combine the ease of use and flexibility of R with the power of big data tools Filled with practical techniues and useful code examples to process large data sets efficiently Who This Book Is For This book is for programmers and developers who want to improve the performance of their R programs by making them run faster with large data sets or who are trying to solve a pesky performance problem What You Will Learn Benchmark and profile R programs to solve performance bottlenecks Understand how CPU memory and disk inputoutput constraints can lim.
Aloysius Lim Ë 9 FREE READ
FREE READ R High Performance Programming ↠ E-book, or Kindle E-pub Tical modeling and can generate useful insights and discoveries from large amounts of dataThrough this practical and varied guide you will become euipped to solve a range of performance problems in R programming You will learn how to profile and benchmark R programs identify bottlenecks assess and identify performance limitations from the CPU identify memory or disk inputoutput constraints and optimize the computational speed of your R programs using great tricks such as vectorizing computations You will then move on to advanced techniues such as compiling code and tapping into the computing power of GPUs optimizing memory consumption and handling larger than memory data sets using disk based memory and chunki.
- Kindle Edition
- R High Performance Programming
- Aloysius Lim
- 27 May 2020