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MD simulation ด้วย Amber
การใช้งานบน compute node
ตัวอย่างสำหรับการรันงานบน compute node โดยใช้ 160 CPU-cores และ job time limit 120:00:00 ชั่งโมง ภายใต้ project account projXXXX (จำเป็นต้องเปลี่ยนเป็น project account ที่ท่านเป็นสมาชิกในโครงการฯ)
| Code Block |
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#!/bin/bash -l
#SBATCH --partition=compute # specific partition to |
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gpu node #SBATCH -N |
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4 --ntasks-per-node=40 # for requset |
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4 compute node with 40 cpu-cores #SBATCH --time=120:00:00 # job time limit <hr:min:sec> #SBATCH --account=projXXXX # change projXXXX to your project account #SBATCH --job-name=testMD module purge # purge all module module load bzip2/1.0.8-GCCcore-8.3.0 module load XZ/5.2.4-GCCcore-8.3.0 module load GCC/8.3.0 module load OpenMPI/3.1.4- |
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gcccuda-2019b WORKDIR=$SLURM_SUBMIT_DIR ###################################################### # nothing should need changed below here to run unless you do not export AMBER_PREFIX="/tarafs/data/project/proj0XXXX/amber20_src" export AMBERHOME=/tarafs/data/project/proj0XXXX/amber20_src export PATH="${AMBER_PREFIX}/bin:${PATH}" |
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# Add location of Amber Python modules to default Python search path
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cd |
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$AMBERHOME |
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source amber.sh ###################################################### cd $WORKDIR srun pmemd.MPI -O -i input.in -o md.out -p system.top -c md_2.restrt -ref md_2.restrt -r md_1.restrt -x md_1.nc -v mdvel |
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Here is the job submission script for MD simulation on GPU node. ต้องทำการตั้งค่า |
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export AMBER_PREFIX="/tarafs/data/project/proj0999/amber20_src"
export AMBERHOME=/tarafs/data/project/proj0999/amber20_src |
การใช้งานบน GPU node
| Code Block |
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#!/bin/bash -l
#SBATCH --partition=gpu # specific partition to gpu node
#SBATCH |
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--nodes=1 # for requset 1 compute node with 40 cpu-cores #SBATCH --time=120:00:00 # job time limit <hr:min:sec> #SBATCH --account=projXXXX # change projXXXX to your project account #SBATCH --job-name=testMD module purge # purge all module module load bzip2/1.0.8-GCCcore-8.3.0 module load XZ/5.2.4-GCCcore-8.3.0 module load CUDA/10.1.243-GCC-8.3.0 module load gcccuda/2019b module load OpenMPI/3.1.4-gcccuda-2019b WORKDIR=$SLURM_SUBMIT_DIR ###################################################### # nothing should need changed below here to run unless you do not export AMBER_PREFIX="/tarafs/data/project/proj0XXXX/amber20_src" export AMBERHOME=/tarafs/data/project/proj0XXXX/amber20_src export PATH="${AMBER_PREFIX}/bin:${PATH}" |
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# Add location of Amber Python modules to default Python search path
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cd |
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$AMBERHOME |
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source amber.sh ###################################################### cd $WORKDIR srun -n 2 pmemd.cuda.MPI -O -i input.in -o md.out -p system.top -c md_2.restrt -ref md_2.restrt -r md_1.restrt -x md_1.nc -v mdvel |
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การวิเคราะห์ผลด้วย cpptraj
หากโครงสร้างที่ต้องการวิเคราะห์มีขนาดไม่เกิน 100,000 atoms ขอแนะนำให้ทำการวิเคราะห์ผลด้วย cpptraj บน devel node โดยใช้ 1 CPU-cores และ job time limit 2:00:00 ชั่งโมง
ตัวอย่าง job submission script for สำหรับ Trajectory analysis on บน compute node.
| Code Block |
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#!/bin/bash -l
#SBATCH --partition=devel # specific partition to compute node
#SBATCH --nodes=1 --ntasks-per-node=1 # for requset 1 compute node with 1 cpu-core
#SBATCH --account=projXXXX # change projXXXX to your project account
#SBATCH --time=2:00:00 # job time limit <hr:min:sec>
#SBATCH --account=projXXXX # change projXXXX to your project account
#SBATCH --job-name=mmpbsa
module purge # purge all module
module load bzip2/1.0.8-GCCcore-8.3.0
module load XZ/5.2.4-GCCcore-8.3.0
module load GCC/8.3.0
module load OpenMPI/3.1.4-GCC-8.3.0
WORKDIR=$SLURM_SUBMIT_DIR
######################################################
# nothing should need changed below here to run unless you do not
export AMBER_PREFIX="/tarafs/data/project/proj0XXXX/amber20_src"
export AMBERHOME=/tarafs/data/project/proj0XXXX/amber20_src
export PATH="${AMBER_PREFIX}/bin:${PATH}"
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# Add location of Amber Python modules to default Python search path
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cd |
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$AMBERHOME |
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source amber.sh ###################################################### cd $WORKDIR cpptraj -i rmsd.in > rmsd.out |
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