working parallel

gistfile1.txt

library(future)
library(mrgsolve)
library(dplyr)
data(extran3)
ipar <- extran3 %>% dplyr::select(ID,CL,VC,KA) %>% distinct(ID)
mod <- mrgsolve:::house()

plan(multiprocess)
f <- list()
for (ii in 1:2) {
  f[[ii]] <- future({
    data <- extran3
    mod %>% Req(CP) %>% 
      data_set(data) %>%
      mrgsim %>% as.data.frame %>%
      mutate(rep = ii)
  })
}
v <- lapply(f, FUN = value)
bind_rows(v)

This crumps for you?

library(future)
library(mrgsolve)
library(dplyr)
data(extran3)
ipar <- extran3 %>% dplyr::select(ID,CL,VC,KA) %>% distinct(ID)
mod <- mrgsolve:::house()

plan(multiprocess)
f <- list()

system.time({
  for (ii in 1:2) {
    f[[ii]] <- future({
      data <- expand.ev(amt=100,ID=1:200)
      mod %>% 
        Req(CP) %>% 
        data_set(data) %>%
        mrgsim %>% 
        mutate(rep = ii)
    })
  }
})

> library(future)
> library(mrgsolve)
> library(dplyr)
> data(extran3)
> ipar <- extran3 %>% dplyr::select(ID,CL,VC,KA) %>% distinct(ID)
> mod <- mrgsolve:::house()
> 
> plan(multiprocess)
> f <- list()
> 
> system.time({
+   for (ii in 1:2) {
+     f[[ii]] <- future({
+       data <- expand.ev(amt=100,ID=1:200)
+       mod %>% 
+         Req(CP) %>% 
+         data_set(data) %>%
+         mrgsim %>% 
+         mutate(rep = ii)
+     })
+   }
+ })
   user  system elapsed 
  0.016   0.007   0.023 
> v <- lapply(f, FUN = value)
> bind_rows(v)
# A tibble: 192,800 x 4
      ID  time       CP   rep
   <dbl> <dbl>    <dbl> <int>
1      1  0.00 0.000000     1
2      1  0.00 0.000000     1
3      1  0.25 1.287441     1
4      1  0.50 2.225208     1
5      1  0.75 2.904129     1
6      1  1.00 3.391488     1
7      1  1.25 3.737128     1
8      1  1.50 3.977972     1
9      1  1.75 4.141369     1
10     1  2.00 4.247580     1
# ... with 192,790 more rows

Session info ----------------------------------------------------------------------------------------------------------------------------
 setting  value                       
 version  R version 3.3.0 (2016-05-03)
 system   x86_64, darwin13.4.0        
 ui       RStudio (0.99.902)          
 language (EN)                        
 collate  en_US.UTF-8                 
 tz       America/Chicago             
 date     2016-08-11                  

Packages --------------------------------------------------------------------------------------------------------------------------------
 package       * version     date       source        
 assertthat      0.1         2013-11-08 local         
 codetools       0.2-14      2015-07-15 CRAN (R 3.2.3)
 DBI             0.4-1       2016-05-08 CRAN (R 3.3.0)
 devtools        1.12.0      2016-06-24 CRAN (R 3.3.0)
 digest          0.6.9       2016-01-08 CRAN (R 3.2.1)
 dplyr         * 0.5.0       2016-06-24 CRAN (R 3.3.0)
 future        * 1.0.1       2016-07-04 CRAN (R 3.3.0)
 globals         0.6.1       2016-02-03 CRAN (R 3.3.0)
 lazyeval        0.2.0       2016-06-12 CRAN (R 3.3.0)
 listenv         0.6.0       2015-12-28 CRAN (R 3.3.0)
 magrittr        1.5         2014-11-22 CRAN (R 3.1.2)
 memoise         1.0.0       2016-01-29 CRAN (R 3.2.1)
 mrgsolve      * 0.7.5.9000  2016-08-06 local         
 R6              2.1.2       2016-01-26 CRAN (R 3.2.3)
 Rcpp            0.12.6      2016-07-19 CRAN (R 3.3.0)
 RcppArmadillo   0.7.200.2.0 2016-07-24 CRAN (R 3.3.0)
 rsconnect       0.4.3       2016-05-02 CRAN (R 3.3.0)
 tibble          1.1         2016-07-04 CRAN (R 3.3.0)
 withr           1.0.2       2016-06-20 CRAN (R 3.3.0)

> devtools::session_info()
Session info ------------------------------------------------------------
 setting  value                       
 version  R version 3.3.0 (2016-05-03)
 system   x86_64, darwin15.4.0        
 ui       RStudio (0.99.1198)         
 language (EN)                        
 collate  en_US.UTF-8                 
 tz       America/Detroit             
 date     2016-08-11                  

Packages ----------------------------------------------------------------
 package       * version     date      
 assertthat      0.1         2013-12-06
 codetools       0.2-14      2015-07-15
 DBI             0.4-1       2016-05-08
 devtools        1.11.1      2016-04-21
 digest          0.6.10      2016-08-02
 dplyr         * 0.5.0       2016-06-24
 future        * 1.0.1       2016-08-11
 globals         0.6.1       2016-02-03
 lazyeval        0.2.0       2016-06-12
 listenv         0.6.0       2015-12-28
 magrittr        1.5         2014-11-22
 memoise         1.0.0       2016-01-29
 mrgsolve      * 0.7.5.9000  2016-08-09
 R6              2.1.2       2016-01-26
 Rcpp            0.12.6      2016-07-19
 RcppArmadillo   0.7.200.2.0 2016-07-24
 rsconnect       0.4.3       2016-05-02
 tibble          1.1         2016-07-04
 withr           1.0.1       2016-02-04
 source                                       
 CRAN (R 3.3.0)                               
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 CRAN (R 3.3.0)                               
 Github (HenrikBengtsson/future@771d11b)      
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 CRAN (R 3.3.0)                               
 CRAN (R 3.3.0)                               
 CRAN (R 3.3.0)                               
 Github (metrumresearchgroup/mrgsolve@777ba41)
 CRAN (R 3.3.0)                               
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 CRAN (R 3.3.0)   

.libPaths("lib")
library(future)
library(future.BatchJobs)
library(mrgsolve)
library(dplyr)

mod <- mrgsolve:::house()

data <- expand.ev(amt=100,ID=1:20)

plan(batchjobs_sge, pathname="simple.tmpl")

f <- lapply(1:10, function(i) {
  future({
    mod %>% 
      Req(CP) %>% 
      data_set(data) %>%
      mrgsim %>% 
      mutate(rep = i)
  })
}) 

data <- lapply(f,value) %>% bind_rows

simple.tmpl

#!/bin/bash

#$ -N <%= job.name %>
#$ -j y
#$ -o <%= log.file %>
#$ -cwd
#$ -V


# we merge R output with stdout from SGE, which gets then logged via -o option
R CMD BATCH --no-save --no-restore  "<%= rscript %>" /dev/stdout
exit 0