1132 search results for "parallel"

Determining the Number of Factors with Parallel Analysis in R

April 12, 2016
By
Determining the Number of Factors with Parallel Analysis in R

Tom Schmitt April 12, 2016 As discussed on page 308 and illustrated on page 312 of Schmitt (2011), a first essential step in Factor Analysis is to determine the appropriate number of factors with Parallel Analysis in R. The data consists of 26 psychological tests administered by Holzinger and Swineford (1939) to 145 students and Continue Reading.. The post...

Read more »

Improve SVM Tuning through Parallelism

March 19, 2016
By
Improve SVM Tuning through Parallelism

As pointed out in the chapter 10 of “The Elements of Statistical Learning”, ANN and SVM (support vector machines) share similar pros and cons, e.g. lack of interpretability and good predictive power. However, in contrast to ANN usually suffering from local minima solutions, SVM is always able to converge globally. In addition, SVM is less

Read more »

Are you doing parallel computations in R? Then use BiocParallel

March 6, 2016
By
Are you doing parallel computations in R? Then use BiocParallel

It’s the morning of the first day of oral conferences at #ENAR2016. I feel like I have a spidey sense since I woke up 3 min after an email from Jeff Leek; just a funny coincidence. Anyhow, I promised Valerie Obenchain at #Bioc2014 that I would write a post about one of my favorite Bioconductor packages:...

Read more »

R for Deep Learning (II): Achieve High-Performance DNN with Parallel Acceleration

February 20, 2016
By
R for Deep Learning (II): Achieve High-Performance DNN with Parallel Acceleration

I would like to thank  Jun Ma  and all other technical reviewers and readers for their informative comments and suggestions in this post. 50 years of Data Science, David Donoho, 2015 Computing with Data.Every data scientist should know and use several languages for data analysis and data processing. These can include popular languages like R

Read more »

The R Parallel Programming Blog

February 2, 2016
By
The R Parallel Programming Blog

Today, parallel computing truly is a mainstream technology. But, stock R is still a single-thread and main memory (RAM) limited software, which really restricts its usage and efficiency against the challenges from very complex model architectures, dynamically configurable analytics models and big data input with billions of parameters and samples. Therefore, ParallelR dedicated on accelerate

Read more »

Writing fast asynchronous SGD/AdaGrad with RcppParallel

January 23, 2016
By
Writing fast asynchronous SGD/AdaGrad with RcppParallel

Word embeddings After Tomas Mikolov et al. released word2vec tool, there was a boom of articles about words vector representations. One of the greatest is GloVe, which did a big thing by explaining how such algorithms work. It also refolmulates word2vec optimization as a special kind of factoriazation for word cooccurences matrix. This post is devided into two main...

Read more »

Writing fast asynchronous SGD/AdaGrad with RcppParallel

January 23, 2016
By
Writing fast asynchronous SGD/AdaGrad with RcppParallel

Word embeddings After Tomas Mikolov et al. released word2vec tool, there was a boom of articles about words vector representations. One of the greatest is GloVe, which did a big thing by explaining how such algorithms work. It also refolmulates word2vec optimization as a special kind of factoriazation for word cooccurences matrix. This post is devided into two main...

Read more »

A gentle introduction to parallel computing in R

January 19, 2016
By
A gentle introduction to parallel computing in R

by John Mount Ph.D. Data Scientist at Win-Vector LLC Let's talk about the use and benefits of parallel computation in R. IBM's Blue Gene/P massively parallel supercomputer (Wikipedia). Parallel computing is a type of computation in which many calculations are carried out simultaneously." Wikipedia quoting: Gottlieb, Allan; Almasi, George S. (1989). Highly parallel computing The reason we care is:...

Read more »

A gentle introduction to parallel computing in R

January 18, 2016
By
A gentle introduction to parallel computing in R

Let’s talk about the use and benefits of parallel computation in R. IBM’s Blue Gene/P massively parallel supercomputer (Wikipedia). Parallel computing is a type of computation in which many calculations are carried out simultaneously.” Wikipedia quoting: Gottlieb, Allan; Almasi, George S. (1989). Highly parallel computing The reason we care is: by making the computer work … Continue reading...

Read more »

RcppParallel: Getting R and C++ to work (some more) in parallel

January 15, 2016
By
RcppParallel: Getting R and C++ to work (some more) in parallel

(Post by Dirk Eddelbuettel and JJ Allaire) A common theme over the last few decades was that we could afford to simply sit back and let computer (hardware) engineers take care of increases in computing speed thanks to Moore’s law. That same line of thought now frequently points out that we are getting closer and closer

Read more »

Sponsors

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)