AMSS-NCKU/makefile_and_run.py

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##
## This file defines the commands used to build and run AMSS-NCKU
## Author: Xiaoqu
## 2025/01/24
##
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import AMSS_NCKU_Input as input_data
import subprocess

## CPU core binding configuration
## Removed hardcoded taskset to allow full utilization of 96 cores via MPI+OpenMP
NUMACTL_CPU_BIND = ""

## Build parallelism configuration
## Use nohz_full cores (4-55, 60-111) for compilation: 52 + 52 = 104 cores
## Set make -j to utilize available cores for faster builds
BUILD_JOBS = 96


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## Compile the AMSS-NCKU main program ABE

def makefile_ABE():

    print(                                                        )
    print( " Compiling the AMSS-NCKU executable file ABE/ABEGPU " ) 
    print(                                                        )

    ## Build command
    if (input_data.GPU_Calculation == "no"):
        makefile_command  = f"{NUMACTL_CPU_BIND} make -j{BUILD_JOBS} ABE"
    elif (input_data.GPU_Calculation == "yes"):
        makefile_command  = f"{NUMACTL_CPU_BIND} make -j{BUILD_JOBS} ABEGPU"
    else:
        print( " CPU/GPU numerical calculation setting is wrong " )
        print(                                                    )
 
    ## Execute the command with subprocess.Popen and stream output
    makefile_process = subprocess.Popen(makefile_command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, text=True)

    ## Read and print output lines as they arrive
    for line in makefile_process.stdout:
        print(line, end='')  # stream output in real time

    ## Wait for the process to finish
    makefile_return_code = makefile_process.wait()
    if makefile_return_code != 0:
        raise subprocess.CalledProcessError(makefile_return_code, makefile_command)
        
    print(                                                                  )
    print( " Compilation of the AMSS-NCKU executable file ABE is finished " ) 
    print(                                                                  )
    
    return
        
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## Compile the AMSS-NCKU TwoPuncture program TwoPunctureABE

def makefile_TwoPunctureABE():

    print(                                                            )
    print( " Compiling the AMSS-NCKU executable file TwoPunctureABE " )
    print(                                                            )
    
    ## Build command
    makefile_command = f"{NUMACTL_CPU_BIND} make -j{BUILD_JOBS} TwoPunctureABE"

    ## Execute the command with subprocess.Popen and stream output
    makefile_process = subprocess.Popen(makefile_command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, text=True) 
    
    ## Read and print output lines as they arrive
    for line in makefile_process.stdout:
        print(line, end='')  # stream output in real time
        
    ## Wait for the process to finish
    makefile_return_code = makefile_process.wait()
    if makefile_return_code != 0:
        raise subprocess.CalledProcessError(makefile_return_code, makefile_command)
        
    print(                                                                             )
    print( " Compilation of the AMSS-NCKU executable file TwoPunctureABE is finished " )
    print(                                                                             )
    
    return
    
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## Run the AMSS-NCKU main program ABE

def run_ABE():

    print(                                                      )
    print( " Running the AMSS-NCKU executable file ABE/ABEGPU " ) 
    print(                                                      )

    ## Calculate OMP_NUM_THREADS
    ## User has 96 cores. Calculate threads per MPI process.
    total_physical_cores = 96
    omp_num_threads = total_physical_cores // input_data.MPI_processes
    if omp_num_threads < 1:
        omp_num_threads = 1
    
    print( f" Configuration: {input_data.MPI_processes} MPI processes, {omp_num_threads} OpenMP threads per process." )
    print( f" Total cores utilized: {input_data.MPI_processes * omp_num_threads}" )

    ## Define the command to run; cast other values to strings as needed
    
    if (input_data.GPU_Calculation == "no"):
        mpi_command         = f"{NUMACTL_CPU_BIND} mpirun -genv OMP_NUM_THREADS {omp_num_threads} -np {input_data.MPI_processes} ./ABE"
        mpi_command_outfile = "ABE_out.log"
    elif (input_data.GPU_Calculation == "yes"):
        mpi_command         = f"{NUMACTL_CPU_BIND} mpirun -genv OMP_NUM_THREADS {omp_num_threads} -np {input_data.MPI_processes} ./ABEGPU"
        mpi_command_outfile = "ABEGPU_out.log"
 
    ## Execute the MPI command and stream output
    mpi_process = subprocess.Popen(mpi_command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, text=True)

    ## Write ABE run output to file while printing to stdout
    with open(mpi_command_outfile, 'w') as file0:  
        ## Read and print output lines; also write each line to file
        for line in mpi_process.stdout:
            print(line, end='')  # stream output in real time
            file0.write(line)    # write the line to file
            file0.flush()        # flush to ensure each line is written immediately (optional)            
    file0.close()

    ## Wait for the process to finish
    mpi_return_code = mpi_process.wait()
    
    print(                                           )
    print( " The ABE/ABEGPU simulation is finished " ) 
    print(                                           )
    
    return

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## Run the AMSS-NCKU TwoPuncture program TwoPunctureABE

def run_TwoPunctureABE():

    print(                                                          )
    print( " Running the AMSS-NCKU executable file TwoPunctureABE " ) 
    print(                                                          )
    
    ## Define the command to run
    TwoPuncture_command         = NUMACTL_CPU_BIND + " ./TwoPunctureABE"
    TwoPuncture_command_outfile = "TwoPunctureABE_out.log"

    ## Execute the command with subprocess.Popen and stream output
    TwoPuncture_process = subprocess.Popen(TwoPuncture_command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, text=True)

    ## Write TwoPunctureABE run output to file while printing to stdout
    with open(TwoPuncture_command_outfile, 'w') as file0:  
        ## Read and print output lines; also write each line to file
        for line in TwoPuncture_process.stdout:
            print(line, end='')  # stream output in real time
            file0.write(line)    # write the line to file
            file0.flush()        # flush to ensure each line is written immediately (optional)                 
    file0.close()

    ## Wait for the process to finish
    TwoPuncture_command_return_code = TwoPuncture_process.wait()
    
    print(                                               )
    print( " The TwoPunctureABE simulation is finished " ) 
    print(                                               )
    
    return

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