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ขั้นตอนการติดตั้ง Amber20 สำหรับการใช้งานบน CPU

1. Obtain Amber20 at http://ambermd.org and download source codes

2. Upload and extract amber source codes at your project home director

   Code Block
   cd /tarafs/data/project/projxxxx #change projxxxx to your project ID tar xvfj AmberTools20.tar.bz2 tar xvfj Amber20.tar.bz2

3. Set the AMBERHOME home directory environment variable

   Code Block
   cd amber20_src export AMBERHOME=$PWD

4. Load modules and prepare for AMBER20 installation

   Code Block
   module purge module load bzip2/1.0.8-GCCcore-8.3.0 module load GCC/8.3.0 module load XZ/5.2.4-GCCcore-8.3.0

5. Go to the amber directory and execute the compilation script

   Code Block
   cd $AMBERHOME ./configure -noX11 gnu

6. Install and test

   Code Block
   source ./amber.sh make install make test

7. After the installation is successful, you can compile parallel (MPI) versions of Amber20 by load OpenMPI module

   Code Block
   module load OpenMPI/3.1.4-GCC-8.3.0

8. Then, recompilation with MPI

   Code Block
   ./configure -mpi -noX11 gnu make install

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การ compile Amber20 สำหรับการใช้งานบน GPU

หลังจากทำการ compile การตามขั้นตอนก่อนหน้าเรียบร้อยแล้ว ให้ทำการ complie สำหรับการใช้งานบนระบบ GPU ดังขั้นตอนต่อไปนี้

1. Go to the AMBERHOME home directory environment variable

   Code Block
   cd /tarafs/data/project/projxxxx #change projxxxx to your project ID cd amber20_src export AMBERHOME=$PWD

2. Load modules and prepare for AMBER20 installation

   Code Block
   module purge module load bzip2/1.0.8-GCCcore-8.3.0 module load XZ/5.2.4-GCCcore-8.3.0 module load gcccuda/2019b module load CUDA/10.1.243

3. Go to the amber directory and execute the compilation script for the installation with cuda

   Code Block
   cd $AMBERHOME ./configure -noX11 -cuda gnu make install

4. Testing

   Code Block
   make test.cuda_serial

5. After the installation is successful, you can compile parallel (MPI) versions with cuda

   Code Block
   module load OpenMPI/3.1.4-gcccuda-2019b module load NCCL/2.4.8-gcccuda-2019b export NCCL_HOME=/tarafs/utils/modules/software/NCCL/2.4.8-gcccuda-2019b/

6. Then, recompilation with MPI for GPU

   Code Block
   ./configure -noX11 -cuda -mpi -nccl gnu make install

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