About DRM4G

DRM4G is an open platform, based on ?GridWay , to define, submit, and manage computational jobs. DRM4G is a ?Python (2.6+, 3.3+) implementation that provides a single point of control for computing resources without installing any intermediate middlewares. As a result, a user is able to run the same job on laptops, desktops, workstations, clusters, supercomputers, and any grid.

Start Guide

In order to install DRM4G, download the installation script :

[user@mycomputer~]$ wget --no-check-certificate https://meteo.unican.es/work/DRM4G/drm4g_bootstrap.sh

And then run it :

[user@mycomputer~]$ bash ./drm4g_bootstrap.sh --dir $HOME

==========================
DRM4G installation script
==========================

--> Checking the last version of DRM4G ...

--> DRM4G version selected: 2.4.1

--> Downloading drm4g-2.4.1.tar.gz ...

--> Unpacking drm4g-2.4.1.tar.gz in directory /home/user ...

--> Installing DRM4G python requirements locally ...

====================================
Installation of DRM4G 2.4.1 is done!
====================================

In order to work with DRM4G you have to enable its 
environment with the command:

    source /home/user/drm4g/bin/drm4g_init.sh

You need to run the above command on every new shell you 
open before using DRM4G, but just once per session.

Start to run DRM4G

1. Enable DRM4G:

   [user@mycomputer~]$ source $HOME/drm4g/bin/drm4g_init.sh
   

2. Start up DRM4G :

   [user@mycomputer~]$ drm4g start
   Checking DRM4G local configuration ...
     Creating a DRM4G local configuration in '/home/user/.drm4g'
     Copying from '/home/user/drm4g/etc' to '/home/user/.drm4g/etc'
   Starting DRM4G .... 
     OK
   Starting ssh-agent ...
     OK
   

3. Show information about all available resources, their hosts and their queues :

   [user@mycomputer~]$ drm4g resource list
   RESOURCE            STATE               
   localmachine        enabled
   

   [user@mycomputer~]$ drm4g host list
   HID ARCH       JOBS(R/T) LRMS       HOST                
   0   x86_64           0/0 fork       localmachine
   

   [user@mycomputer~]$ drm4g host list 0
   HID ARCH       JOBS(R/T) LRMS       HOST                
   0   x86_64           0/0 fork       localmachine        
   
   QUEUENAME      JOBS(R/T) WALLT CPUT  MAXR  MAXQ 
   default              0/0 0     0     1     1               
   

My first job

1. Create a job template :

   [user@mycomputer~]$ echo "EXECUTABLE=/bin/date" > date.job
   

2. Submit the job :

   [user@mycomputer~]$ drm4g job submit date.job
   ID: 0
   

3. Check the evolution of the job :

   [user@mycomputer~]$ drm4g job list 0
   JID DM   EM   START    END      EXEC    XFER    EXIT NAME            HOST                                          
   0   pend ---- 19:39:09 --:--:-- 0:00:00 0:00:00 --   date.job        --                        
   

   If you execute successive drm4g job list 0, you will see the different states of this job:
   • pend: The job is pending for a host to run on.

      JID DM   EM   START    END      EXEC    XFER    EXIT NAME            HOST                                          
      0   pend ---- 19:39:09 --:--:-- 0:00:00 0:00:00 --   date.job        --                                            
     

   • prol: The frontend is being prepared for execution.

      JID DM   EM   START    END      EXEC    XFER    EXIT NAME            HOST                                          
      0   prol ---- 19:39:09 --:--:-- 0:00:00 0:00:00 --   date.job        --                                                            
     

   • wrap pend: The job has been successfully submitted to the frontend and it is pending in the queue

      JID DM   EM   START    END      EXEC    XFER    EXIT NAME            HOST                                          
      0   wrap pend 19:39:09 --:--:-- 0:00:00 0:00:00 --   date.job localhost/fork                                                                         
     

   • wrap actv:The job is running in the remote queue.

      JID DM   EM   START    END      EXEC    XFER    EXIT NAME            HOST                                          
      0   wrap actv 19:39:09 --:--:-- 0:00:05 0:00:00 --   date.job localhost/fork                                                         
     

   • epil:The job is done/complete in queue and it's fetching the results.

      JID DM   EM   START    END      EXEC    XFER    EXIT NAME            HOST                                          
      0   epil ---- 19:39:09 --:--:-- 0:00:10 0:00:00 --   date.job localhost/fork
     

   • done:The job is done.

      JID DM   EM   START    END      EXEC    XFER    EXIT NAME            HOST                                          
      0   done ---- 19:39:09 19:39:27 0:00:10 0:00:01 0    date.job localhost/fork         
     

4. In this job template, the results from the job are standard output (stdout) and standard error (stderr), both files will be in the same directory of the sob submision:

   [user@mycomputer~]$ cat stdout.0
   Mon Jul 28 12:29:43 CEST 2014
   
   [user@mycomputer~]$ cat stderr.0
   

How to configure a TORQUE/PBS resource

In order to configure a TORQUE/PBS cluster accessed through ssh protocol, you can follow the next steps:

1. Generate a public/private key pair without password :

   [user@mycomputer~]$ ssh-keygen -t rsa -b 2048 -f $HOME/.ssh/meteo_rsa -N ""
   

2. Copy the new public key to the TORQUE/PBS resource :

   [user@mycomputer~]$ ssh-copy-id -i $HOME/.ssh/meteo_rsa.pub user@ui.macc.unican.es
   

3. Configure the meteo resource :

   [user@mycomputer~]$ drm4g resource edit
   [meteo]
   enable            = true
   communicator      = ssh
   username          = user
   frontend          = ui.macc.unican.es
   private_key       = ~/.ssh/meteo_rsa
   lrms              = pbs
   queue             = grid
   max_jobs_running  = 1
   max_jobs_in_queue = 2
   

4. List and check if resource has been created successfully :

   [user@mycomputer~]$ drm4g resource list
   RESOURCE            STATE               
   meteo               enabled
   
   [user@mycomputer~]$ drm4g host list
   HID ARCH       JOBS(R/T) LRMS       HOST                
   0   x86_64           0/0 pbs        meteo
   

That's it! Now, you can summit jobs to meteo.

User Scenarios

In this section it will be described how to take advantage of DRM4G to calculate the number Pi. To do that, three types of jobs single, array and mpi will be used.

Single Job

• C code :

  #include <stdio.h>
  #include <string.h>
  #include <stdlib.h>
  
  int main (int argc, char** args)
  {
    int task_id;
    int total_tasks;
    long long int n;
    long long int i;
  
    double l_sum, x, h;
  
    task_id = 0;
    total_tasks = 100;
    n = atoll(args[1]);
  
    fprintf(stderr, "task_id=%d total_tasks=%d n=%lld\n", task_id, total_tasks, n);
  
    h = 1.0/n;
  
    l_sum = 0.0;
  
    for (i = task_id; i < n; i += total_tasks)
    {
      x = (i + 0.5)*h;
      l_sum += 4.0/(1.0 + x*x);
    }
  
    l_sum *= h;
  
    printf("%0.12g\n", l_sum);
  
    return 0;
  }
  

• DRM4G job template :

  EXECUTABLE  = pi.sh
  ARGUMENTS   = 100000000
  STDOUT_FILE = stdout_file.${JOB_ID}
  STDERR_FILE = stderr_file.${JOB_ID}
  INPUT_FILES = pi.c, pi.sh
  

• pi.sh script :

  #!/bin/bash
  gcc -o pi pi.c
  chmod +x ./pi
  ./pi
  

Array Job

• C code :

  #include <stdio.h>
  #include <string.h>
  #include <stdlib.h>
  
  int main (int argc, char** args)
  {
    int task_id;
    int total_tasks;
    long long int n;
    long long int i;
  
    double l_sum, x, h;
  
    task_id = atoi(args[1]);
    total_tasks = atoi(args[2]);
    n = atoll(args[3]);
  
    fprintf(stderr, "task_id=%d total_tasks=%d n=%lld\n", task_id, total_tasks, n);
  
    h = 1.0/n;
  
    l_sum = 0.0;
  
    for (i = task_id; i < n; i += total_tasks)
    {
      x = (i + 0.5)*h;
      l_sum += 4.0/(1.0 + x*x);
    }
  
    l_sum *= h;
  
    printf("%0.12g\n", l_sum);
  
    return 0;
  }
  

• DRM4G job template :

  EXECUTABLE  = pi.sh
  ARGUMENTS   = ${TASK_ID} ${TOTAL_TASKS} 100000000
  STDOUT_FILE = stdout_file.${TASK_ID}
  STDERR_FILE = stderr_file.${TASK_ID}
  INPUT_FILES = pi.c, pi.sh
  

• pi.sh script :

  #!/bin/bash
  gcc -o pi pi.c
  chmod +x ./pi
  ./pi $@
  

MPI Job

• C code :

  #include "mpi.h"
  #include <stdio.h>
  #include <math.h>
  
  int main( int argc, char *argv[])
  {
      int done = 0, n, myid, numprocs, i;
      double PI25DT = 3.141592653589793238462643;
      double mypi, pi, h, sum, x;
      double startwtime = 0.0, endwtime;
      int  namelen;
      char processor_name[MPI_MAX_PROCESSOR_NAME];
  
      MPI_Init(&argc,&argv);
      MPI_Comm_size(MPI_COMM_WORLD,&numprocs);
      MPI_Comm_rank(MPI_COMM_WORLD,&myid);
      MPI_Get_processor_name(processor_name,&namelen);
  
      printf("Process %d on %s\n", myid, processor_name);
  
      n = atoll(args[1]);
  
      startwtime = MPI_Wtime();
  
      h   = 1.0 / (double) n;
      sum = 0.0;
      for (i = myid + 1; i <= n; i += numprocs)
      {
          x = h * ((double)i - 0.5);
          sum += 4.0 / (1.0 + x*x);
      }
      mypi = h * sum;
  
      MPI_Reduce(&mypi, &pi, 1, MPI_DOUBLE, MPI_SUM, 0, MPI_COMM_WORLD);
  
      if (myid == 0)
      {
          printf("pi is approximately %.16f, Error is %.16f\n",
                 pi, fabs(pi - PI25DT));
          endwtime = MPI_Wtime();
          printf("wall clock time = %f\n", endwtime-startwtime);
      }
  
      MPI_Finalize();
  
      return 0;
  }
  

• DRM4G job template :

  EXECUTABLE    = mpi.sh
  ARGUMENTS     = 100000000
  STDOUT_FILE   = stdout.${JOB_ID}
  STDERR_FILE   = stderr.${JOB_ID}
  INPUT_FILES   = mpi.sh, mpi.c
  NP            = 2
  

• mpi.sh script :

  mpicc mpi.c -o mpi
  chmod +x mpi
  mpirun -np 2 ./mpi