Revision as of 14:11, 17 November 2016

Biowulf User Guide. Note that Biowulf2 runs Centos (RedHat) 6.x. (Biowulf1 is at Centos 5.x)

Linux distribution

$ ls /etc/*release  # login mode
$ cat /etc/redhat-release  
Red Hat Enterprise Linux Server release 6.8 (Santiago)

$ sinteractive      # switch to biowulf2 computing nodes
$ cat /etc/redhat-release 
CentOS release 6.6 (Final)
$ cat /etc/centos-release 
CentOS release 6.6 (Final)

Training notes

Storage

https://hpc.nih.gov/storage/

Quota

checkquota

Environment modules

# What modules are available
module avail
module -d avail # default
module avail STAR
module spider bed # search by a case-insensitive keyword

# Load a module
module list # loaded modules
module load STAR
module load STAR/2.4.1a
module load plinkseq macs bowtie # load multiple modules

# Unload a module
module unload STAR/2.4.1a

# Switch to a different version of an application
# If you load a module, then load another version of the same module, the first one will be unloaded.

# Examine a modulefile
$ module display STAR
-----------------------------------------------------------------------------
   /usr/local/lmod/modulefiles/STAR/2.5.1b.lua:
-----------------------------------------------------------------------------
help([[This module sets up the environment for using STAR.
Index files can be found in /fdb/STAR
]])
whatis("STAR: ultrafast universal RNA-seq aligner")
whatis("Version: 2.5.1b")
prepend_path("PATH","/usr/local/apps/STAR/2.5.1b/bin")

# Set up personal modulefiles

# Using modules in scripts

# Shared Modules

Single file - sbatch

sbatch
Note sbatch command does not support --module option. In sbatch case, the module command has to be put in the script file.
Script file must be starting with a line #!/bin/bash

Don't use the swarm command on a single script file since swarm will treat each line of the script file as an independent command.

sbatch --cpus-per-task=2 --mem=4g MYSCRIPT

An example of the script file (Slurm environment variable $SLURM_CPUS_PER_TASK within your script was used to specify the number of threads to the program)

#!/bin/bash

module load novocraft
novoalign -c $SLURM_CPUS_PER_TASK  -f s_1_sequence.txt -d celegans -o SAM > out.sam

Multiple files - swarm

swarm

swarm -t 3 -g 20 -f run_seqtools_vc.sh --module samtools,picard,bwa --verbose 1 --devel
# 3 commands run in 3 subjobs, each command requiring 20 gb and 3 threads, allocating 6 cores and 12 cpus
swarm -t 3 -g 20 -f run_seqtools_vc.sh --module samtools,picard,bwa --verbose 1

# To change the default walltime, use --time=24:00:00

swarm -t 8 -g 24 --module tophat,samtools,htseq -f run_master.sh
cat sw3n17156.o

Partition and freen

https://hpc.nih.gov/docs/b2-userguide.html#cluster_status
In the script file, we can use $SLURM_CPUS_PER_TASK to represent the number of cpus
In the swarm command, we can use -t to specify the threads and -g to specify the memory (GB).

Biowulf nodes are grouped into partitions. A partition can be specified when submitting a job. The default partition is 'norm'. The freen command can be used to see free nodes and CPUs, and available types of nodes on each partition.

We may need to run swarm commands on non-default partitions. For example, not many free CPUs are available in 'norm' partition. Or Total time for bundled commands is greater than partition walltime limit. Or because the default partition norm has nodes with a maximum of 120GB memory.

We can run the swarm command on different partition (the default is 'norm'). For example, to run on b1 parition (the hardware in b1 looks inferior to norm)

swarm -f outputs/run_seqtools_dge_align -g 20 -t 16 --module tophat,samtools,htseq --time=6:00:00 --partition b1 --verbose 1

Below is an output from freen command.

                                           ........Per-Node Resources........  
Partition    FreeNds       FreeCPUs       Cores CPUs   Mem   Disk    Features
--------------------------------------------------------------------------------
norm*       0/301        1624/9488         16    32    123g   800g   cpu32,core16,g128,ssd800,x2650,10g
unlimited   3/12         202/384           16    32    123g   800g   cpu32,core16,g128,ssd800,x2650,10g
niddk       1/82         228/2624          16    32    123g   800g   cpu32,core16,g128,ssd800,x2650,10g,niddk
ibfdr       0/184        0/5888            16    32     60g   800g   cpu32,core16,g64,ssd800,x2650,ibfdr
ibqdr       1/95         32/3040           16    32     29g   400g   cpu32,core16,g32,sata400,x2600,ibqdr
ibqdr       51/89        1632/2848         16    32     60g   400g   cpu32,core16,g64,sata400,x2600,ibqdr
gpu         1/4          116/128           16    32    123g   800g   cpu32,core16,g128,ssd800,x2650,gpuk20x,acemd
gpu         17/20        634/640           16    32    123g   800g   cpu32,core16,g128,ssd800,x2650,gpuk20x
largemem    3/4          254/256           32    64   1007g   800g   cpu64,core32,g1024,ssd800,x4620,10g
nimh        58/60        1856/1920         16    32    123g   800g   cpu32,core16,g128,ssd800,x2650,10g,nimh
ccr         0/85         1540/2720         16    32    123g   800g   cpu32,core16,g128,ssd800,x2650,10g,ccr
ccr         0/63         598/2016          16    32    123g   400g   cpu32,core16,g128,sata400,x2600,1g,ccr
ccr         0/60         974/1920          16    32     60g   400g   cpu32,core16,g64,sata400,x2600,1g,ccr
ccrclin     4/4          128/128           16    32     60g   400g   cpu32,core16,g64,sata400,x2600,1g,ccr
quick       0/85         1540/2720         16    32    123g   800g   cpu32,core16,g128,ssd800,x2650,10g,ccr
quick       0/63         598/2016          16    32    123g   400g   cpu32,core16,g128,sata400,x2600,1g,ccr
quick       0/60         974/1920          16    32     60g   400g   cpu32,core16,g64,sata400,x2600,1g,ccr
quick       1/82         228/2624          16    32    123g   800g   cpu32,core16,g128,ssd800,x2650,10g,niddk
quick       58/60        1856/1920         16    32    123g   800g   cpu32,core16,g128,ssd800,x2650,10g,nimh
b1          71/363       7584/8712         12    24     21g   100g   cpu24,core12,g24,sata100,x5660,1g
b1          3/287        3410/4592          8    16     21g   200g   cpu16,core8,g24,sata200,x5550,1g
b1          7/16         192/256            8    16     68g   200g   cpu16,core8,g72,sata200,x5550,1g
b1          5/20         300/640           16    32    250g   400g   cpu32,core16,g256,sata400,e2670,1g
b1          3/10         100/160            8    16     68g   100g   cpu16,core8,g72,sata100,x5550,1g

Running R scripts

https://hpc.nih.gov/apps/R.html

Running a swarm of R batch jobs on Biowulf

R --vanilla < /data/username/R/R1  > /data/username/R/R1.out
R --vanilla < /data/username/R/R2  > /data/username/R/R2.out

swarm -g 16 -f /home/username/Rjobs --module R

Parallelizing with 'parallel'

detectBatchCPUs <- function() { 
    ncores <- as.integer(Sys.getenv("SLURM_CPUS_PER_TASK")) 
    if (is.na(ncores)) { 
        ncores <- as.integer(Sys.getenv("SLURM_JOB_CPUS_PER_NODE")) 
    } 
    if (is.na(ncores)) { 
        return(4) # for helix
    } 
    return(ncores) 
}

ncpus <- detectBatchCPUs() 
options(mc.cores = ncpus) 
mclapply(..., mc.cores = ncpus) 
makeCluster(ncpus)

Monitor jobs/Delete jobs

https://hpc.nih.gov/docs/userguide.html#monitor

sjobs
watch -n 30 jobload
scancel -u XXXXX
scancel NNNNN
scancel --state=PENDING
scancel --state=RUNNING
squeue -u XXXX

jobhist 17500  # report the CPU and memory usage of completed jobs.

The other two commands are very useful too jobhist and swarmhist (temporary).

$ cat /usr/local/bin/swarmhist
#!/bin/bash
usage="usage: $0 jobid"
jobid=$1
[[ -n $jobid ]] || { echo $usage; exit 1; }
ret=$(grep "jobid=$jobid" /usr/local/logs/swarm_on_slurm.log)
[[ -n $ret ]] || { echo "no swarm found for jobid = $jobid"; exit; }
echo $ret | tr ';' '\n'

$ jobhist 22038972
$ swarmhist 22038972
date=(SKIP)
 host=(SKIP)
 jobid=22038972
 user=(SKIP)
 pwd=(SKIP)
 ncmds=1
 soptions=--array=0-0 --job-name=swarm --output(SKIP)
 njobs=1
 job-name=swarm
 command=/usr/local/bin/swarm -t 16 -g 20 -f outputs/run_seqtools_vc --module samtools,picard --verbose 1

Exit code

https://hpc.nih.gov/docs/b2-userguide.html#exitcodes

Local disk and temporary files

https://hpc.nih.gov/docs/b2-userguide.html#local

Interactive debugging

8GB and 4 CPUs on a single node. Increase them to 60 GB and more cores if we run something like STAR for rna-seq reads alignment.

sinteractive --mem=8g -c 4

Parallel jobs

Parallel (MPI) jobs that run on more than 1 node: Use the environment variable $SLURM_NTASKS within the script to specify the number of MPI processes.

Biowulf: Difference between revisions

Revision as of 14:11, 17 November 2016

Contents

Linux distribution

Training notes

Storage

Quota

Environment modules

Single file - sbatch

Multiple files - swarm

Partition and freen

Running R scripts

Monitor jobs/Delete jobs

Exit code

Local disk and temporary files

Interactive debugging

Parallel jobs

Navigation menu

Biowulf: Difference between revisions

Revision as of 14:11, 17 November 2016

Linux distribution

Training notes

Storage

Quota

Environment modules

Single file - sbatch

Multiple files - swarm

Partition and freen

Running R scripts

Monitor jobs/Delete jobs

Exit code

Local disk and temporary files

Interactive debugging

Parallel jobs

Navigation menu

Search