setting 1 job per worker core after chunking the elements

先从 issue 中的 future::tweak(... batchtools_sge ...) 计划和 furrr::future_map 示例开始，然后检查 resources[["slots"]] 如何通过 batchtools.sge-mrg.tmpl 传递。完成的标准是确定 native chunking 是否能够在 worker 和 core 之间分配 16 个元素，并记录受支持的行为或要求。

I am using an sge template.

Is there a native way in future plan to have elements of a list be allocated to each available core in preset number of workers (ie chunking the list)?

ie if i have a workers with 8 cores and a vector (x) of length 16, i want future to send each element to a core on the workers to run in parallel. (assuming i am sending out jobs from the remote master)

sge <- future::tweak(
    future.batchtools::batchtools_sge,
    template = 'batchtools.sge-mrg.tmpl',
    workers = 2,
    resources = list(slots = 1)
  )
  
  future::plan(list(sge))
  
  x <- vector('list',16)

  ret <- furrr::future_map(x, .f = foo)
  

#!/bin/bash

## The name of the job, can be anything, simply used when displaying the list of running jobs
#$ -N <%= job.name %>

## Combining output/error messages into one file
#$ -j y

## Giving the name of the output log file
#$ -o <%= log.file %>

## One needs to tell the queue system to use the current directory as the working directory
## Or else the script may fail as it will execute in your top level home directory /home/username
#$ -cwd

## Use environment variables
#$ -V

## Use correct queue
##$ -q all.q

#$ -pe smp <%= resources[["slots"]] %>

## Export value of DEBUGME environemnt var to slave
export DEBUGME=<%= Sys.getenv("DEBUGME") %>

<%= sprintf("export OMP_NUM_THREADS=%i", resources$omp.threads) -%>
<%= sprintf("export OPENBLAS_NUM_THREADS=%i", resources$blas.threads) -%>
<%= sprintf("export MKL_NUM_THREADS=%i", resources$blas.threads) -%>


Rscript -e 'batchtools::doJobCollection("<%= uri %>")'
exit 0

cc @wlandau