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Mastering Parallel Programming with R. free ebook download

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Author(s):	Mastering Parallel Programming with R

Date:	2016	Format:	True PDF	Language:	English	ISBN/ASIN:	1784394009
Pages:	1	OCR:		Quality:		ISBN13:
Uploader:	gestalt	Upload Date:	1/4/2021 3:15:41 AM

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Master the robust features of R parallel programming to accelerate your data science computations.

This book is for R programmers who want to step beyond its inherent single-threaded and restricted memory limitations and learn how to implement highly accelerated and scalable algorithms that are a necessity for the performant processing of Big Data. No previous knowledge of parallelism is required. This book also provides for the more advanced technical programmer seeking to go beyond high level parallel frameworks.

What You Will Learn:

- Create and structure efficient load-balanced parallel computation in R, using R's built-in parallel package
- Deploy and utilize cloud-based parallel infrastructure from R, including launching a distributed computation on Hadoop running on Amazon Web Services (AWS)
- Get accustomed to parallel efficiency, and apply simple techniques to benchmark, measure speed and target improvement in your own code
- Develop complex parallel processing algorithms with the standard Message Passing Interface (MPI) using RMPI, pbdMPI, and SPRINT packages
- Build and extend a parallel R package (SPRINT) with your own MPI-based routines
- Implement accelerated numerical functions in R utilizing the vector processing capability of your Graphics Processing Unit (GPU) with OpenCL
- Understand parallel programming pitfalls, such as deadlock and numerical instability, and the approaches to handle and avoid them
- Build a task farm master-worker, spatial grid, and hybrid parallel R programs

R is one of the most popular programming languages used in data science. Applying R to big data and complex analytic tasks requires the harnessing of scalable compute resources.

Mastering Parallel Programming with R presents a comprehensive and practical treatise on how to build highly scalable and efficient algorithms in R. It will teach you a variety of parallelization techniques, from simple use of R's built-in parallel package versions of lapply(), to high-level AWS cloud-based Hadoop and Apache Spark frameworks. It will also teach you low level scalable parallel programming using RMPI and pbdMPI for message passing, applicable to clusters and supercomputers, and how to exploit thousand-fold simple processor GPUs through ROpenCL. By the end of the book, you will understand the factors that influence parallel efficiency, including assessing code performance and implementing load balancing  pitfalls to avoid, including deadlock and numerical instability issues  how to structure your code and data for the most appropriate type of parallelism for your problem domain  and how to extract the maximum performance from your R code running on a variety of computer systems.

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	Title	Link	Password	Size (MB)	Thank to	Inform Admin
2931340	Book	https://florenfile.com/pvgxcvzjfzaf...		3.70	gestalt

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Mastering Parallel Programming with R. free ebook download

Category: Databases

Description: Click to see full description

Category:
Databases