Why are my Nextflow processes not executing in parallel?

Question

I have written a Nextflow script with three process:

• The first process takes a pair of fastq files and aligns with reference genome. The process writes the resulting SAM file into sam channel.
• Second process takes input from the sam channel and creates a BAM file from it, and writes it into bam channel.
• Final process reads from bam channel and sorts the BAM files.

Following is the entire code:

#!~/bin nextflow

reads_ch = Channel.fromFilePairs('raw/*_{1,2}.fastq.gz', flat: true)
ref_genome = file('reference/genome/index/ref_genome')

process mapToRef {
    memory '20 GB'
    cpus 16
    input:
    tuple val(sample_id), file(read1), file(read2) from reads_ch
    
    output:
    tuple val(sample_id), file("${sample_id}.sam") into sam_ch

    script:
    """
    ~/biotools/bwa/bwa mem -t 60 ${ref_genome} ${read1} ${read2} > ${sample_id}.sam
    """   
}

process samToBam {
    memory '20 GB'
    cpus 16
    input:
    tuple val(sample_id), file("${sample_id}.sam") from sam_ch

    output:
    tuple val(sample_id), file("${sample_id}.bam") into bam_ch

    script:
    """
    ~/biotools/SAMTOOLS/samtools-1.12/samtools view -S -b ${sample_id}.sam > ${sample_id}.bam 
    """
}

process sortBam {
    memory '20 GB'
    cpus 16
    input:
    tuple val(sample_id), file("${sample_id}.bam") from bam_ch

    output:
    tuple val(sample_id), file("${sample_id}.sorted.bam") into sorted_bam_ch

    script:
    """
    ~/biotools/SAMTOOLS/samtools-1.12/samtools sort ${sample_id}.bam -o ${sample_id}.sorted.bam
    """
}

All three processes successfully execute their commands. However, they are executed sequentially. For example, the first process mapToRef runs sequentially for all read pairs, followed by samToBam, which too, runs sequentially after all mapToRefs have finished execution. I was under impression that parallelization would "work" out of the box, but I must be doing something wrong. I am a complete beginner in Nextflow and would greatly appreciate any help regarding this.

EDIT

Output of reads_ch.view():

[ERR2512393, /home/work/raw/ERR2512393_1.fastq.gz, /home/work/raw/ERR2512393_2.fastq.gz]
[ERR2512394, /home/work/raw/ERR2512394_1.fastq.gz, /home/work/raw/ERR2512394_2.fastq.gz]
[ERR2512391, /home/work/raw/ERR2512391_1.fastq.gz, /home/work/raw/ERR2512391_2.fastq.gz]
[ERR2512392, /home/work/raw/ERR2512392_1.fastq.gz, /home/work/raw/ERR2512392_2.fastq.gz]
[ERR2512390, /home/work/raw/ERR2512390_1.fastq.gz, /home/work/raw/ERR2512390_2.fastq.gz]

Answer 1

I have tested it on my end with the following script:

#!/usr/bin/env nextflow

reads_ch = Channel.fromFilePairs('/root/test_nextflow/*_{1,2}.fastq.gz', flat: true)


process mapToRef {
  memory '1 GB'
  echo true
  cpus 1

  input:
  tuple val(sample_id), file(r1), file(r2) from reads_ch

  output:
  tuple val(sample_id), file("${sample_id}.sam") into sam_ch

  script:
  """
  echo bwa mem ${r1} {r2}
  if [ ${sample_id} == "ERR2512393" ]; then sleep 10; fi
  touch ${sample_id}.sam
  """
}

process samToBam {
  memory '1 GB'
  cpus 1
  echo true

  input:
  tuple val(sample_id), file(sam) from sam_ch

  output:
  tuple val(sample_id), file("${sample_id}.bam") into bam_ch

  script:
  """
  echo samtools view -S -b ${sample_id}.sam
  touch ${sample_id}.bam
  """
}

process sortBam {
  memory '1 GB'
  cpus 1
  input:
  tuple val(sample_id), file(bam) from bam_ch

  output:
  tuple val(sample_id), file("${sample_id}.sorted.bam") into sorted_bam_ch

  script:
  """
  echo samtools sort ${sample_id}.bam
  touch ${sample_id}.sorted.bam
  """
}

It's producing the following result:

As you can see, the two processes are running in parallel (2 of 2)

It could be that yours are limited by the resources? If your PC doesn't have 40GB of memory and 32 CPUs, it will run them sequentially.

EDIT: By adding sleep 10 to mapToRef, we can clearly see both of them are running in parallel now:

EDIT 2: Added condition to "sleep" on one of the samples:

Final EDIT: be mindful of the resources you allocate to your processes. You could use ${task.cpus} and ${task.memory.toGiga()} to facilitate the configuration of your processes so that they are not different from what you have defined and what is actually used. See CPUs