通过mc.cores与makePSOCKcluster设置内核? [英] Setting cores via mc.cores vs. makePSOCKcluster?

问题描述

我想知道通过 makePSOCKcluster 和显式地在foreach循环中设置R使用的内核数之间有什么区别?我应该在两个实例中分别进行设置，还是在使 makePSOCKcluster 足够时进行设置?

I was wondering what is the difference between setting the number of cores for R to use via makePSOCKcluster and explictly in the foreach loop? Should I be setting this seperately in both instances, or is doing so when making the makePSOCKcluster enough?

cl <- makePSOCKcluster(max(1, detectCores() - 1))
registerDoParallel(cl)

和

mcoptions <- list(  preschedule=FALSE, mc.cores = max(1,detectCores()-1)  )
stream = foreach(i=1:NROW(stream_sponsored), .inorder=FALSE,
        .combine=rbind,
        .options.multicore=mcoptions)  %dopar% {
#do something
}

推荐答案

来自['核心"选项可让您临时覆盖用于单个foreach操作的工人数.这比必须重新注册doParallel更方便.尽管如果在注册doParallel时未指定"cores"值，您也可以使用options函数动态更改此值:

'The "cores" options allows you to temporarily override the number of workers to use for a single foreach operation. This is more convenient than having to re-register doParallel. Although if no value of "cores" was specified when doParallel was registered, you can also change this value dynamically using the options function:

options(cores=2)
getDoParWorkers()
options(cores=3)
getDoParWorkers()

如果在注册doParallel时确实指定了内核数，则"cores"选项将被忽略:

If you did specify the number of cores when registering doParallel, the "cores" option is ignored:

registerDoParallel(4)
options(cores=2)
getDoParWorkers()

如您所见，可以使用许多选项来控制并行使用的工作程序的数量，但是默认行为通常可以满足您的要求.'

As you can see, there are a number of options for controlling the number of workers to use with parallel, but the default behaviour usually does what you want.'

因此，简而言之，如果您一次调用foreach，则无需在foreach中指定核心.但是，如果您要调用两个或多个具有不同内核的foreach，则无需在registerDoParallel中指定内核

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