r - 有没有办法限制运行的R进程的数量

Question

我使用 doMC，它使用 multicore 包。当我(在控制台中)调试时，它发生了(好几次)它横向移动并且 fork-bombed .

R 有 setrlimit() 系统调用吗？ 在 pyhton 中，我会使用 resource.RLIMIT_NPROC

理想情况下，我想将运行的 R 进程数限制为一个数字

编辑:操作系统是 linux CentOS 6

Answer 1

应该有几个选择。这是来自 Writing R Extensions, Section 1.2.1.1 的相关部分

   Packages are not standard-alone programs, and an R process could
contain more than one OpenMP-enabled package as well as other components
(for example, an optimized BLAS) making use of OpenMP. So careful
consideration needs to be given to resource usage.  OpenMP works with
parallel regions, and for most implementations the default is to use as
many threads as 'CPUs' for such regions.  Parallel regions can be
nested, although it is common to use only a single thread below the
first level.  The correctness of the detected number of 'CPUs' and the
assumption that the R process is entitled to use them all are both
dubious assumptions.  The best way to limit resources is to limit the
overall number of threads available to OpenMP in the R process: this can
be done via environment variable 'OMP_THREAD_LIMIT', where
implemented.(4)  Alternatively, the number of threads per region can be
limited by the environment variable 'OMP_NUM_THREADS' or API call
'omp_set_num_threads', or, better, for the regions in your code as part
of their specification.  E.g. R uses
     #pragma omp parallel for num_threads(nthreads) ...
That way you only control your own code and not that of other OpenMP
users.

我最喜欢的工具之一是控制它的包:RhpcBLASctl .这是它的描述:

Control the number of threads on 'BLAS' (Aka 'GotoBLAS', 'ACML' and 'MKL'). and possible to control the number of threads in 'OpenMP'. get a number of logical cores and physical cores if feasible.

毕竟您需要控制并行 session 的数量以及分配给每个并行线程的 BLAS 核心数量。并行包默认每个 session 2 个线程是有原因的...

所有这些应该在很大程度上独立于您正在运行的 Linux 或 Unix 的风格。好吧，除了 OS X 当然(仍然 !!)没有为您提供 OpenMP 之外。

你可以从 doMC 和 friend 那里控制最外层。