Rocky Python Prime Array

Job Array

Job arrays allow you to run the same code many times with a different task id. The task id can then be used to determine which subset of your data to process. This strategy breaks your large job up into multiple smaller jobs that not only execute more quickly but can run concurrently.

In the example of discovering prime numbers, lets say we want to discover all the primes in the first 1 million numbers. We could just create code that goes from 1 to 1000000. But if we use a job array, we could create 100 jobs that each search 10000 numbers.

Batch File

There are three differences when turning this into a job array.

First, we've added a SBATCH parameter to define not only how many jobs but the range of task ids to produce. In our example, we're making the range 0 to 100.

Secondly, for the log file pattern, we're using %A and %a instead of %j. These are patterns specific to job arrays. You can read more about the file patterns at this link

Lastly, we pass the environment variable $SLURM_ARRAY_TASK_ID as a parameter to our code. We will need to read in this parameter and use it to determine what data to process. We know from our array definition that it will be a number from 0 to 100.

#!/bin/bash

#SBATCH --job-name=PYTHON_PRIME_ARRAY
#SBATCH --output=logs/python_prime_array_%A-%a.out
#SBATCH --array=0-100

module load Python

python prime_array.py $SLURM_ARRAY_TASK_ID

Python Code

import sys

# How many numbers to check for prime from each job
CHUNKSIZE = 10000

ARRAYID=0
if len(sys.argv) > 1:
    ARRAYID = int(sys.argv[1])

MIN = ARRAYID * CHUNKSIZE
MAX = MIN + CHUNKSIZE

def is_prime(num):
    if num <= 1:
        return False
    else:
        for i in range(2, num):
            if (num % i) == 0:
                return False
    return True


for i in range(MIN, MAX+1):
    if is_prime(i):
        print(i)