Parallelism In R

Kevin Feasel

2017-09-06

R

Florian Prive shows off a few methods for parallelizing code in R:

Parallelize with foreach

You need to do at least two things:

  • replace %do% by %dopar%. Basically, always use %dopar% because you can use registerDoSEQ() is you really want to run the foreach sequentially.

  • register a parallel backend using one of the packages that begin with do (such as doParalleldoMCdoMPI and more). I will list only the two main parallel backends because there are too many of them.

Check it out.  Florian spends a lot of time with foreach and doParallel, a little bit of time with flock, and mentions Microsoft R Open.  H/T R-Bloggers

Related Posts

Using Service Broker To Queue Up External Script Calls

Arvind Shyamsundar shows how to use Service Broker to run external R or Python scripts based on new data coming into a transactional system: Here, we will show you how you can use the asynchronous execution mechanism offered by SQL Server Service Broker to ‘queue’ up data inside SQL Server which can then be asynchronously passed to […]

Read More

Reasons For Using Docker With R

Jeroen Ooms gives us a few reasons why we might want to containerize our R-based products: The flagship of the OpenCPU system is the OpenCPU server: a mature and powerful Linux stack for embedding R in systems and applications. Because OpenCPU is completely open source we can build and ship on DockerHub. A ready-to-go linux server […]

Read More

Categories

September 2017
MTWTFSS
« Aug Oct »
 123
45678910
11121314151617
18192021222324
252627282930