R中doMC和doParallel的区别 [英] the difference between doMC and doParallel in R

问题描述

doParallel 和 doMC 在 R 中的 foreach 函数有什么区别?doParallel 支持 windows，unix-like，而 doMC 只支持 unix-like.换句话说，为什么doParallel不能直接替代doMC?谢谢.

What's the difference between doParallel and doMC in R concerning foreach function? doParallel supports windows, unix-like, while doMC supports unix-like only. In other words, why doParallel cannot replace doMC directly? Thank you.

更新:doParallel 建立在 parallel 之上，本质上是 multicore 和 snow 的合并，并自动使用适当的工具你的系统.因此，我们可以使用 doParallel 来支持多系统.换句话说，我们可以用doParallel代替doMC.

Update: doParallel is built on parallel, which is essentially a merger of multicore and snow and automatically uses the appropriate tool for your system. As a result, we can use doParallel to support multi systems. In other words, we can use doParallel to replace doMC.

ref: http://michaeljkoontz.weebly.com/uploads/1/9/9/4/19940979/parallel.pdf

顺便说一句，registerDoParallel(ncores=3) 和

cl <- makeCluster(3)
registerDoParallel(cl)

好像registerDoParallel(ncores=3)可以自动停止集群，而第二个不会自动停止，需要stopCluster(cl).

It seems registerDoParallel(ncores=3) can stop cluster automatically, while the second do not stop automatically and needs stopCluster(cl).

ref: http://cran.r-project.org/web/packages/doParallel/vignettes/gettingstartedParallel.pdf

推荐答案

doParallel 包是 doSNOW 和 doMC 的合并，很多因为parallel 是snow 和multicore 的合并.但是尽管 doParallel 具有 doMC 的所有功能，Revolution Analytics 的 Rich Calaway 告诉我，他们希望保留 doMC，因为它是在某些情况下效率更高，即使 doMC 现在像 doParallel 一样使用 parallel.我没有亲自运行任何基准测试来确定是否存在显着差异以及何时存在显着差异.

The doParallel package is a merger of doSNOW and doMC, much as parallel is a merger of snow and multicore. But although doParallel has all the features of doMC, I was told by Rich Calaway of Revolution Analytics that they wanted to keep doMC around because it was more efficient in certain circumstances, even though doMC now uses parallel just like doParallel. I haven't personally run any benchmarks to determine if and when there is a significant difference.

我倾向于在 Linux 或 Mac OS X 计算机上使用 doMC，在 Windows 计算机上使用 doParallel，在 Linux 集群上使用 doMPI，但 doParallel 确实适用于所有这些平台.

I tend to use doMC on a Linux or Mac OS X computer, doParallel on a Windows computer, and doMPI on a Linux cluster, but doParallel does work on all of those platforms.

对于不同的注册方式，如果执行:

As for the different registration methods, if you execute:

registerDoParallel(cores=3)

在 Windows 机器上，它将隐式地创建一个集群对象，供以后使用 clusterApplyLB，而在 Linux 和 Mac OS X 上，没有创建或使用集群对象.内核数会被简单地记住并在稍后调用 mclapply 时用作 mc.cores 参数的值.

on a Windows machine, it will create a cluster object implicitly for later use with clusterApplyLB, whereas on Linux and Mac OS X, no cluster object is created or used. The number of cores is simply remembered and used as the value of the mc.cores argument later when calling mclapply.

如果你执行:

cl <- makeCluster(3)
registerDoParallel(cl)

然后注册的集群对象将与clusterApplyLB 一起使用，而不管平台如何.您是对的，在这种情况下，您有责任在创建集群对象后关闭它，而隐式集群对象会自动关闭.

then the registered cluster object will be used with clusterApplyLB regardless of the platform. You are correct that in this case, it is your responsibility to shutdown the cluster object since you created it, whereas the implicit cluster object is automatically shutdown.

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