Answers.Body: <p>I haven't used canu for several years but looking back at my labbook I ran it with two additional flags:</p>
  <p><code>-minThreads=8 -maxThreads=8</code></p>
  <p>My memory on the subject is a bit hazy but  think I had to play around with these settings to get it to work.  I also set the flag:</p>
  <p><code>-maxMemory=6</code></p>
  
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Answers.CreationDate: 2022-02-02T21:47:27.733Z
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Body: <p>I am currently running canu on an LSF Linux server using the following script called assemble.sh:</p>
  <pre><code>canu -p species -d output genomeSize=100m -pacbio-raw subreads.fastq
  </code></pre>
  <p>I then submit this script with the following in a computer node:</p>
  <pre><code>bsub -q basement -E 'test -e /nfs/users/nfs_c/cr' -R &quot;select[mem&gt;25000] rusage[mem=25000]&quot; -M25000 -o canu.o -e canu.e -J canu 'bash assemble.sh' -n8 -R&quot;span[hosts=1]&quot;
  </code></pre>
  <p>On my laptop, using 8 cores and 16 GB memory, assemble.sh took about 48h. On the cluster, it's been running for 72h and it is still running. I wonder if I am allocating resources correctly or if I can do something better. On my laptop, I can see in my activity monitor that canu is using many cores at the same time. Do you know how I can check this in an LSF server?</p>
  <p><a href="http://canu.readthedocs.io/en/latest/faq.html#faq" rel="nofollow noreferrer">This page</a> talks about submitting jobs on LSF. In particular, it mentions this: <code>gridOptions=&quot;your options list&quot;</code> but I don't know how to use this option.</p>
  <p>Any help would be appreciated.</p>
  <p>checking the queue with <code>bjobs -u all</code> shows there are 125259 jobs running. My own job is running, it's not pending. Does the number of other jobs affect the running of my own job? I will ask IT if there are preferred writing locations. I did not consider that could change the speed of the job. Do you know a command to check how many resources my job is using?</p>
  
Tags: <assembly><linux><canu>
Title: How to submit a canu job on LSF high-performance computing cluster farm?
ThreadText: # How to submit a canu job on LSF high-performance computing cluster farm?
  
  (Asked by: username_0 on 2017-11-23)
  
  I am currently running canu on an LSF Linux server using the following script called assemble.sh:
  
  ```
  canu -p species -d output genomeSize=100m -pacbio-raw subreads.fastq
  
  ```
  
  I then submit this script with the following in a computer node:
  
  ```
  bsub -q basement -E 'test -e /nfs/users/nfs_c/cr' -R "select[mem>25000] rusage[mem=25000]" -M25000 -o canu.o -e canu.e -J canu 'bash assemble.sh' -n8 -R"span[hosts=1]"
  
  ```
  
  On my laptop, using 8 cores and 16 GB memory, assemble.sh took about 48h. On the cluster, it's been running for 72h and it is still running. I wonder if I am allocating resources correctly or if I can do something better. On my laptop, I can see in my activity monitor that canu is using many cores at the same time. Do you know how I can check this in an LSF server?
  
  [This page](http://canu.readthedocs.io/en/latest/faq.html#faq) talks about submitting jobs on LSF. In particular, it mentions this: `gridOptions="your options list"` but I don't know how to use this option.
  
  Any help would be appreciated.
  
  checking the queue with `bjobs -u all` shows there are 125259 jobs running. My own job is running, it's not pending. Does the number of other jobs affect the running of my own job? I will ask IT if there are preferred writing locations. I did not consider that could change the speed of the job. Do you know a command to check how many resources my job is using?
  
  **Tags:** assembly, linux, canu
  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2022-02-02. Score: 1
  
  I haven't used canu for several years but looking back at my labbook I ran it with two additional flags:
  
  `-minThreads=8 -maxThreads=8`
  
  My memory on the subject is a bit hazy but think I had to play around with these settings to get it to work. I also set the flag:
  
  `-maxMemory=6`
  
  
  ---
  
  