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Author SHA1 Message Date
3f7e20f702 删除diff_new.f90中冗余部分,方便后续工作 2026-02-08 00:54:23 +08:00
673dd20722 对fmisc.f90的polint修改 2026-02-07 01:56:44 +08:00
18 changed files with 1386 additions and 5091 deletions

4
.gitignore vendored
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@@ -1,5 +1,3 @@
__pycache__
GW150914
GW150914*
.codex
docs/
GW150914-origin

445
AMSS_NCKU_ABEtest.py Normal file
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##################################################################
##
## AMSS-NCKU ABE Test Program (Skip TwoPuncture if data exists)
## Modified from AMSS_NCKU_Program.py
## Author: Xiaoqu
## Modified: 2026/02/01
##
##################################################################
##################################################################
## Print program introduction
import print_information
print_information.print_program_introduction()
##################################################################
import AMSS_NCKU_Input as input_data
##################################################################
## Create directories to store program run data
import os
import shutil
import sys
import time
## Set the output directory according to the input file
File_directory = os.path.join(input_data.File_directory)
## Check if output directory exists and if TwoPuncture data is available
skip_twopuncture = False
output_directory = os.path.join(File_directory, "AMSS_NCKU_output")
binary_results_directory = os.path.join(output_directory, input_data.Output_directory)
if os.path.exists(File_directory):
print( " Output directory already exists." )
print()
# Check if TwoPuncture initial data files exist
if (input_data.Initial_Data_Method == "Ansorg-TwoPuncture"):
twopuncture_output = os.path.join(output_directory, "TwoPunctureABE")
input_par = os.path.join(output_directory, "input.par")
if os.path.exists(twopuncture_output) and os.path.exists(input_par):
print( " Found existing TwoPuncture initial data." )
print( " Do you want to skip TwoPuncture phase and reuse existing data?" )
print( " Input 'skip' to skip TwoPuncture and start ABE directly" )
print( " Input 'regenerate' to regenerate everything from scratch" )
print()
while True:
try:
inputvalue = input()
if ( inputvalue == "skip" ):
print( " Skipping TwoPuncture phase, will reuse existing initial data." )
print()
skip_twopuncture = True
break
elif ( inputvalue == "regenerate" ):
print( " Regenerating everything from scratch." )
print()
skip_twopuncture = False
break
else:
print( " Please input 'skip' or 'regenerate'." )
except ValueError:
print( " Please input 'skip' or 'regenerate'." )
else:
print( " TwoPuncture initial data not found, will regenerate everything." )
print()
# If not skipping, remove and recreate directory
if not skip_twopuncture:
shutil.rmtree(File_directory, ignore_errors=True)
os.mkdir(File_directory)
os.mkdir(output_directory)
os.mkdir(binary_results_directory)
figure_directory = os.path.join(File_directory, "figure")
os.mkdir(figure_directory)
shutil.copy("AMSS_NCKU_Input.py", File_directory)
print( " Output directory has been regenerated." )
print()
else:
# Create fresh directory structure
os.mkdir(File_directory)
shutil.copy("AMSS_NCKU_Input.py", File_directory)
os.mkdir(output_directory)
os.mkdir(binary_results_directory)
figure_directory = os.path.join(File_directory, "figure")
os.mkdir(figure_directory)
print( " Output directory has been generated." )
print()
# Ensure figure directory exists
figure_directory = os.path.join(File_directory, "figure")
if not os.path.exists(figure_directory):
os.mkdir(figure_directory)
##################################################################
## Output related parameter information
import setup
## Print and save input parameter information
setup.print_input_data( File_directory )
if not skip_twopuncture:
setup.generate_AMSSNCKU_input()
setup.print_puncture_information()
##################################################################
## Generate AMSS-NCKU program input files based on the configured parameters
if not skip_twopuncture:
print()
print( " Generating the AMSS-NCKU input parfile for the ABE executable." )
print()
## Generate cgh-related input files from the grid information
import numerical_grid
numerical_grid.append_AMSSNCKU_cgh_input()
print()
print( " The input parfile for AMSS-NCKU C++ executable file ABE has been generated." )
print( " However, the input relevant to TwoPuncture need to be appended later." )
print()
##################################################################
## Plot the initial grid configuration
if not skip_twopuncture:
print()
print( " Schematically plot the numerical grid structure." )
print()
import numerical_grid
numerical_grid.plot_initial_grid()
##################################################################
## Generate AMSS-NCKU macro files according to the numerical scheme and parameters
if not skip_twopuncture:
print()
print( " Automatically generating the macro file for AMSS-NCKU C++ executable file ABE " )
print( " (Based on the finite-difference numerical scheme) " )
print()
import generate_macrodef
generate_macrodef.generate_macrodef_h()
print( " AMSS-NCKU macro file macrodef.h has been generated. " )
generate_macrodef.generate_macrodef_fh()
print( " AMSS-NCKU macro file macrodef.fh has been generated. " )
##################################################################
# Compile the AMSS-NCKU program according to user requirements
# NOTE: ABE compilation is always performed, even when skipping TwoPuncture
print()
print( " Preparing to compile and run the AMSS-NCKU code as requested " )
print( " Compiling the AMSS-NCKU code based on the generated macro files " )
print()
AMSS_NCKU_source_path = "AMSS_NCKU_source"
AMSS_NCKU_source_copy = os.path.join(File_directory, "AMSS_NCKU_source_copy")
## If AMSS_NCKU source folder is missing, create it and prompt the user
if not os.path.exists(AMSS_NCKU_source_path):
os.makedirs(AMSS_NCKU_source_path)
print( " The AMSS-NCKU source files are incomplete; copy all source files into ./AMSS_NCKU_source. " )
print( " Press Enter to continue. " )
inputvalue = input()
# Copy AMSS-NCKU source files to prepare for compilation
# If skipping TwoPuncture and source_copy already exists, remove it first
if skip_twopuncture and os.path.exists(AMSS_NCKU_source_copy):
shutil.rmtree(AMSS_NCKU_source_copy)
shutil.copytree(AMSS_NCKU_source_path, AMSS_NCKU_source_copy)
# Copy the generated macro files into the AMSS_NCKU source folder
if not skip_twopuncture:
macrodef_h_path = os.path.join(File_directory, "macrodef.h")
macrodef_fh_path = os.path.join(File_directory, "macrodef.fh")
else:
# When skipping TwoPuncture, use existing macro files from previous run
macrodef_h_path = os.path.join(File_directory, "macrodef.h")
macrodef_fh_path = os.path.join(File_directory, "macrodef.fh")
shutil.copy2(macrodef_h_path, AMSS_NCKU_source_copy)
shutil.copy2(macrodef_fh_path, AMSS_NCKU_source_copy)
# Compile related programs
import makefile_and_run
## Change working directory to the target source copy
os.chdir(AMSS_NCKU_source_copy)
## Build the main AMSS-NCKU executable (ABE or ABEGPU)
makefile_and_run.makefile_ABE()
## If the initial-data method is Ansorg-TwoPuncture, build the TwoPunctureABE executable
## Only build TwoPunctureABE if not skipping TwoPuncture phase
if (input_data.Initial_Data_Method == "Ansorg-TwoPuncture" ) and not skip_twopuncture:
makefile_and_run.makefile_TwoPunctureABE()
## Change current working directory back up two levels
os.chdir('..')
os.chdir('..')
print()
##################################################################
## Copy the AMSS-NCKU executable (ABE/ABEGPU) to the run directory
if (input_data.GPU_Calculation == "no"):
ABE_file = os.path.join(AMSS_NCKU_source_copy, "ABE")
elif (input_data.GPU_Calculation == "yes"):
ABE_file = os.path.join(AMSS_NCKU_source_copy, "ABEGPU")
if not os.path.exists( ABE_file ):
print()
print( " Lack of AMSS-NCKU executable file ABE/ABEGPU; recompile AMSS_NCKU_source manually. " )
print( " When recompilation is finished, press Enter to continue. " )
inputvalue = input()
## Copy the executable ABE (or ABEGPU) into the run directory
shutil.copy2(ABE_file, output_directory)
## If the initial-data method is TwoPuncture, copy the TwoPunctureABE executable to the run directory
## Only copy TwoPunctureABE if not skipping TwoPuncture phase
if (input_data.Initial_Data_Method == "Ansorg-TwoPuncture" ) and not skip_twopuncture:
TwoPuncture_file = os.path.join(AMSS_NCKU_source_copy, "TwoPunctureABE")
if not os.path.exists( TwoPuncture_file ):
print()
print( " Lack of AMSS-NCKU executable file TwoPunctureABE; recompile TwoPunctureABE in AMSS_NCKU_source. " )
print( " When recompilation is finished, press Enter to continue. " )
inputvalue = input()
## Copy the TwoPunctureABE executable into the run directory
shutil.copy2(TwoPuncture_file, output_directory)
##################################################################
## If the initial-data method is TwoPuncture, generate the TwoPuncture input files
if (input_data.Initial_Data_Method == "Ansorg-TwoPuncture" ) and not skip_twopuncture:
print()
print( " Initial data is chosen as Ansorg-TwoPuncture" )
print()
print()
print( " Automatically generating the input parfile for the TwoPunctureABE executable " )
print()
import generate_TwoPuncture_input
generate_TwoPuncture_input.generate_AMSSNCKU_TwoPuncture_input()
print()
print( " The input parfile for the TwoPunctureABE executable has been generated. " )
print()
## Generated AMSS-NCKU TwoPuncture input filename
AMSS_NCKU_TwoPuncture_inputfile = 'AMSS-NCKU-TwoPuncture.input'
AMSS_NCKU_TwoPuncture_inputfile_path = os.path.join( File_directory, AMSS_NCKU_TwoPuncture_inputfile )
## Copy and rename the file
shutil.copy2( AMSS_NCKU_TwoPuncture_inputfile_path, os.path.join(output_directory, 'TwoPunctureinput.par') )
## Run TwoPuncture to generate initial-data files
start_time = time.time() # Record start time
print()
print()
## Change to the output (run) directory
os.chdir(output_directory)
## Run the TwoPuncture executable
import makefile_and_run
makefile_and_run.run_TwoPunctureABE()
## Change current working directory back up two levels
os.chdir('..')
os.chdir('..')
elif (input_data.Initial_Data_Method == "Ansorg-TwoPuncture" ) and skip_twopuncture:
print()
print( " Skipping TwoPuncture execution, using existing initial data." )
print()
start_time = time.time() # Record start time for ABE only
else:
start_time = time.time() # Record start time
##################################################################
## Update puncture data based on TwoPuncture run results
if not skip_twopuncture:
import renew_puncture_parameter
renew_puncture_parameter.append_AMSSNCKU_BSSN_input(File_directory, output_directory)
## Generated AMSS-NCKU input filename
AMSS_NCKU_inputfile = 'AMSS-NCKU.input'
AMSS_NCKU_inputfile_path = os.path.join(File_directory, AMSS_NCKU_inputfile)
## Copy and rename the file
shutil.copy2( AMSS_NCKU_inputfile_path, os.path.join(output_directory, 'input.par') )
print()
print( " Successfully copy all AMSS-NCKU input parfile to target dictionary. " )
print()
else:
print()
print( " Using existing input.par file from previous run." )
print()
##################################################################
## Launch the AMSS-NCKU program
print()
print()
## Change to the run directory
os.chdir( output_directory )
import makefile_and_run
makefile_and_run.run_ABE()
## Change current working directory back up two levels
os.chdir('..')
os.chdir('..')
end_time = time.time()
elapsed_time = end_time - start_time
##################################################################
## Copy some basic input and log files out to facilitate debugging
## Path to the file that stores calculation settings
AMSS_NCKU_error_file_path = os.path.join(binary_results_directory, "setting.par")
## Copy and rename the file for easier inspection
shutil.copy( AMSS_NCKU_error_file_path, os.path.join(output_directory, "AMSSNCKU_setting_parameter") )
## Path to the error log file
AMSS_NCKU_error_file_path = os.path.join(binary_results_directory, "Error.log")
## Copy and rename the error log
shutil.copy( AMSS_NCKU_error_file_path, os.path.join(output_directory, "Error.log") )
## Primary program outputs
AMSS_NCKU_BH_data = os.path.join(binary_results_directory, "bssn_BH.dat" )
AMSS_NCKU_ADM_data = os.path.join(binary_results_directory, "bssn_ADMQs.dat" )
AMSS_NCKU_psi4_data = os.path.join(binary_results_directory, "bssn_psi4.dat" )
AMSS_NCKU_constraint_data = os.path.join(binary_results_directory, "bssn_constraint.dat")
## copy and rename the file
shutil.copy( AMSS_NCKU_BH_data, os.path.join(output_directory, "bssn_BH.dat" ) )
shutil.copy( AMSS_NCKU_ADM_data, os.path.join(output_directory, "bssn_ADMQs.dat" ) )
shutil.copy( AMSS_NCKU_psi4_data, os.path.join(output_directory, "bssn_psi4.dat" ) )
shutil.copy( AMSS_NCKU_constraint_data, os.path.join(output_directory, "bssn_constraint.dat") )
## Additional program outputs
if (input_data.Equation_Class == "BSSN-EM"):
AMSS_NCKU_phi1_data = os.path.join(binary_results_directory, "bssn_phi1.dat" )
AMSS_NCKU_phi2_data = os.path.join(binary_results_directory, "bssn_phi2.dat" )
shutil.copy( AMSS_NCKU_phi1_data, os.path.join(output_directory, "bssn_phi1.dat" ) )
shutil.copy( AMSS_NCKU_phi2_data, os.path.join(output_directory, "bssn_phi2.dat" ) )
elif (input_data.Equation_Class == "BSSN-EScalar"):
AMSS_NCKU_maxs_data = os.path.join(binary_results_directory, "bssn_maxs.dat" )
shutil.copy( AMSS_NCKU_maxs_data, os.path.join(output_directory, "bssn_maxs.dat" ) )
##################################################################
## Plot the AMSS-NCKU program results
print()
print( " Plotting the txt and binary results data from the AMSS-NCKU simulation " )
print()
import plot_xiaoqu
import plot_GW_strain_amplitude_xiaoqu
## Plot black hole trajectory
plot_xiaoqu.generate_puncture_orbit_plot( binary_results_directory, figure_directory )
plot_xiaoqu.generate_puncture_orbit_plot3D( binary_results_directory, figure_directory )
## Plot black hole separation vs. time
plot_xiaoqu.generate_puncture_distence_plot( binary_results_directory, figure_directory )
## Plot gravitational waveforms (psi4 and strain amplitude)
for i in range(input_data.Detector_Number):
plot_xiaoqu.generate_gravitational_wave_psi4_plot( binary_results_directory, figure_directory, i )
plot_GW_strain_amplitude_xiaoqu.generate_gravitational_wave_amplitude_plot( binary_results_directory, figure_directory, i )
## Plot ADM mass evolution
for i in range(input_data.Detector_Number):
plot_xiaoqu.generate_ADMmass_plot( binary_results_directory, figure_directory, i )
## Plot Hamiltonian constraint violation over time
for i in range(input_data.grid_level):
plot_xiaoqu.generate_constraint_check_plot( binary_results_directory, figure_directory, i )
## Plot stored binary data
plot_xiaoqu.generate_binary_data_plot( binary_results_directory, figure_directory )
print()
print( f" This Program Cost = {elapsed_time} Seconds " )
print()
##################################################################
print()
print( " The AMSS-NCKU-Python simulation is successfully finished, thanks for using !!! " )
print()
##################################################################

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@@ -9,19 +9,9 @@
##################################################################
##################################################################
## Guard against re-execution by multiprocessing child processes.
## Without this, using 'spawn' or 'forkserver' context would cause every
## worker to re-run the entire script.
if __name__ != '__main__':
import sys as _sys
_sys.exit(0)
##################################################################
## Print program introduction
##################################################################
## Print program introduction
import print_information
@@ -432,36 +422,31 @@ print( " Plotting the txt and binary results data from the AMSS-NCKU simulation
print( )
import plot_xiaoqu
import plot_GW_strain_amplitude_xiaoqu
from parallel_plot_helper import run_plot_tasks_parallel
plot_tasks = []
## Plot black hole trajectory
plot_tasks.append( ( plot_xiaoqu.generate_puncture_orbit_plot, (binary_results_directory, figure_directory) ) )
plot_tasks.append( ( plot_xiaoqu.generate_puncture_orbit_plot3D, (binary_results_directory, figure_directory) ) )
## Plot black hole separation vs. time
plot_tasks.append( ( plot_xiaoqu.generate_puncture_distence_plot, (binary_results_directory, figure_directory) ) )
## Plot gravitational waveforms (psi4 and strain amplitude)
for i in range(input_data.Detector_Number):
plot_tasks.append( ( plot_xiaoqu.generate_gravitational_wave_psi4_plot, (binary_results_directory, figure_directory, i) ) )
plot_tasks.append( ( plot_GW_strain_amplitude_xiaoqu.generate_gravitational_wave_amplitude_plot, (binary_results_directory, figure_directory, i) ) )
## Plot ADM mass evolution
for i in range(input_data.Detector_Number):
plot_tasks.append( ( plot_xiaoqu.generate_ADMmass_plot, (binary_results_directory, figure_directory, i) ) )
## Plot Hamiltonian constraint violation over time
for i in range(input_data.grid_level):
plot_tasks.append( ( plot_xiaoqu.generate_constraint_check_plot, (binary_results_directory, figure_directory, i) ) )
run_plot_tasks_parallel(plot_tasks)
## Plot stored binary data
plot_xiaoqu.generate_binary_data_plot( binary_results_directory, figure_directory )
import plot_xiaoqu
import plot_GW_strain_amplitude_xiaoqu
## Plot black hole trajectory
plot_xiaoqu.generate_puncture_orbit_plot( binary_results_directory, figure_directory )
plot_xiaoqu.generate_puncture_orbit_plot3D( binary_results_directory, figure_directory )
## Plot black hole separation vs. time
plot_xiaoqu.generate_puncture_distence_plot( binary_results_directory, figure_directory )
## Plot gravitational waveforms (psi4 and strain amplitude)
for i in range(input_data.Detector_Number):
plot_xiaoqu.generate_gravitational_wave_psi4_plot( binary_results_directory, figure_directory, i )
plot_GW_strain_amplitude_xiaoqu.generate_gravitational_wave_amplitude_plot( binary_results_directory, figure_directory, i )
## Plot ADM mass evolution
for i in range(input_data.Detector_Number):
plot_xiaoqu.generate_ADMmass_plot( binary_results_directory, figure_directory, i )
## Plot Hamiltonian constraint violation over time
for i in range(input_data.grid_level):
plot_xiaoqu.generate_constraint_check_plot( binary_results_directory, figure_directory, i )
## Plot stored binary data
plot_xiaoqu.generate_binary_data_plot( binary_results_directory, figure_directory )
print( )
print( f" This Program Cost = {elapsed_time} Seconds " )

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AMSS_NCKU_Verify_ASC26.py Normal file
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#!/usr/bin/env python3
"""
AMSS-NCKU GW150914 Simulation Regression Test Script
Verification Requirements:
1. XY-plane trajectory RMS error < 1% (Optimized vs. baseline, max of BH1 and BH2)
2. ADM constraint violation < 2 (Grid Level 0)
RMS Calculation Method:
- Computes trajectory deviation on the XY plane independently for BH1 and BH2
- For each black hole: RMS = sqrt((1/M) * sum((Δr_i / r_i^max)^2)) × 100%
- Final RMS = max(RMS_BH1, RMS_BH2)
Usage: python3 AMSS_NCKU_Verify_ASC26.py [output_dir]
Default: output_dir = GW150914/AMSS_NCKU_output
Reference: GW150914-origin (baseline simulation)
"""
import numpy as np
import sys
import os
# ANSI Color Codes
class Color:
GREEN = '\033[92m'
RED = '\033[91m'
YELLOW = '\033[93m'
BLUE = '\033[94m'
BOLD = '\033[1m'
RESET = '\033[0m'
def get_status_text(passed):
if passed:
return f"{Color.GREEN}{Color.BOLD}PASS{Color.RESET}"
else:
return f"{Color.RED}{Color.BOLD}FAIL{Color.RESET}"
def load_bh_trajectory(filepath):
"""Load black hole trajectory data"""
data = np.loadtxt(filepath)
return {
'time': data[:, 0],
'x1': data[:, 1], 'y1': data[:, 2], 'z1': data[:, 3],
'x2': data[:, 4], 'y2': data[:, 5], 'z2': data[:, 6]
}
def load_constraint_data(filepath):
"""Load constraint violation data"""
data = []
with open(filepath, 'r') as f:
for line in f:
if line.startswith('#'):
continue
parts = line.split()
if len(parts) >= 8:
data.append([float(x) for x in parts[:8]])
return np.array(data)
def calculate_rms_error(bh_data_ref, bh_data_target):
"""
Calculate trajectory-based RMS error on the XY plane between baseline and optimized simulations.
This function computes the RMS error independently for BH1 and BH2 trajectories,
then returns the maximum of the two as the final RMS error metric.
For each black hole, the RMS is calculated as:
RMS = sqrt( (1/M) * sum( (Δr_i / r_i^max)^2 ) ) × 100%
where:
Δr_i = sqrt((x_ref,i - x_new,i)^2 + (y_ref,i - y_new,i)^2)
r_i^max = max(sqrt(x_ref,i^2 + y_ref,i^2), sqrt(x_new,i^2 + y_new,i^2))
Args:
bh_data_ref: Reference (baseline) trajectory data
bh_data_target: Target (optimized) trajectory data
Returns:
rms_value: Final RMS error as a percentage (max of BH1 and BH2)
error: Error message if any
"""
# Align data: truncate to the length of the shorter dataset
M = min(len(bh_data_ref['time']), len(bh_data_target['time']))
if M < 10:
return None, "Insufficient data points for comparison"
# Extract XY coordinates for both black holes
x1_ref = bh_data_ref['x1'][:M]
y1_ref = bh_data_ref['y1'][:M]
x2_ref = bh_data_ref['x2'][:M]
y2_ref = bh_data_ref['y2'][:M]
x1_new = bh_data_target['x1'][:M]
y1_new = bh_data_target['y1'][:M]
x2_new = bh_data_target['x2'][:M]
y2_new = bh_data_target['y2'][:M]
# Calculate RMS for BH1
delta_r1 = np.sqrt((x1_ref - x1_new)**2 + (y1_ref - y1_new)**2)
r1_ref = np.sqrt(x1_ref**2 + y1_ref**2)
r1_new = np.sqrt(x1_new**2 + y1_new**2)
r1_max = np.maximum(r1_ref, r1_new)
# Calculate RMS for BH2
delta_r2 = np.sqrt((x2_ref - x2_new)**2 + (y2_ref - y2_new)**2)
r2_ref = np.sqrt(x2_ref**2 + y2_ref**2)
r2_new = np.sqrt(x2_new**2 + y2_new**2)
r2_max = np.maximum(r2_ref, r2_new)
# Avoid division by zero for BH1
valid_mask1 = r1_max > 1e-15
if np.sum(valid_mask1) < 10:
return None, "Insufficient valid data points for BH1"
terms1 = (delta_r1[valid_mask1] / r1_max[valid_mask1])**2
rms_bh1 = np.sqrt(np.mean(terms1)) * 100
# Avoid division by zero for BH2
valid_mask2 = r2_max > 1e-15
if np.sum(valid_mask2) < 10:
return None, "Insufficient valid data points for BH2"
terms2 = (delta_r2[valid_mask2] / r2_max[valid_mask2])**2
rms_bh2 = np.sqrt(np.mean(terms2)) * 100
# Final RMS is the maximum of BH1 and BH2
rms_final = max(rms_bh1, rms_bh2)
return rms_final, None
def analyze_constraint_violation(constraint_data, n_levels=9):
"""
Analyze ADM constraint violation
Return maximum constraint violation for Grid Level 0
"""
# Extract Grid Level 0 data (first entry for each time step)
level0_data = constraint_data[::n_levels]
# Calculate maximum absolute value for each constraint
results = {
'Ham': np.max(np.abs(level0_data[:, 1])),
'Px': np.max(np.abs(level0_data[:, 2])),
'Py': np.max(np.abs(level0_data[:, 3])),
'Pz': np.max(np.abs(level0_data[:, 4])),
'Gx': np.max(np.abs(level0_data[:, 5])),
'Gy': np.max(np.abs(level0_data[:, 6])),
'Gz': np.max(np.abs(level0_data[:, 7]))
}
results['max_violation'] = max(results.values())
return results
def print_header():
"""Print report header"""
print("\n" + Color.BLUE + Color.BOLD + "=" * 65 + Color.RESET)
print(Color.BOLD + " AMSS-NCKU GW150914 Simulation Regression Test Report" + Color.RESET)
print(Color.BLUE + Color.BOLD + "=" * 65 + Color.RESET)
def print_rms_results(rms_rel, error, threshold=1.0):
"""Print RMS error results"""
print(f"\n{Color.BOLD}1. RMS Error Analysis (Baseline vs Optimized){Color.RESET}")
print("-" * 45)
if error:
print(f" {Color.RED}Error: {error}{Color.RESET}")
return False
passed = rms_rel < threshold
print(f" RMS relative error: {rms_rel:.4f}%")
print(f" Requirement: < {threshold}%")
print(f" Status: {get_status_text(passed)}")
return passed
def print_constraint_results(results, threshold=2.0):
"""Print constraint violation results"""
print(f"\n{Color.BOLD}2. ADM Constraint Violation Analysis (Grid Level 0){Color.RESET}")
print("-" * 45)
names = ['Ham', 'Px', 'Py', 'Pz', 'Gx', 'Gy', 'Gz']
for i, name in enumerate(names):
print(f" Max |{name:3}|: {results[name]:.6f}", end=" ")
if (i + 1) % 2 == 0: print()
if len(names) % 2 != 0: print()
passed = results['max_violation'] < threshold
print(f"\n Maximum violation: {results['max_violation']:.6f}")
print(f" Requirement: < {threshold}")
print(f" Status: {get_status_text(passed)}")
return passed
def print_summary(rms_passed, constraint_passed):
"""Print summary"""
print("\n" + Color.BLUE + Color.BOLD + "=" * 65 + Color.RESET)
print(Color.BOLD + "Verification Summary" + Color.RESET)
print(Color.BLUE + Color.BOLD + "=" * 65 + Color.RESET)
all_passed = rms_passed and constraint_passed
res_rms = get_status_text(rms_passed)
res_con = get_status_text(constraint_passed)
print(f" [1] RMS trajectory check: {res_rms}")
print(f" [2] ADM constraint check: {res_con}")
final_status = f"{Color.GREEN}{Color.BOLD}ALL CHECKS PASSED{Color.RESET}" if all_passed else f"{Color.RED}{Color.BOLD}SOME CHECKS FAILED{Color.RESET}"
print(f"\n Overall result: {final_status}")
print(Color.BLUE + Color.BOLD + "=" * 65 + Color.RESET + "\n")
return all_passed
def main():
# Determine target (optimized) output directory
if len(sys.argv) > 1:
target_dir = sys.argv[1]
else:
script_dir = os.path.dirname(os.path.abspath(__file__))
target_dir = os.path.join(script_dir, "GW150914/AMSS_NCKU_output")
# Determine reference (baseline) directory
script_dir = os.path.dirname(os.path.abspath(__file__))
reference_dir = os.path.join(script_dir, "GW150914-origin/AMSS_NCKU_output")
# Data file paths
bh_file_ref = os.path.join(reference_dir, "bssn_BH.dat")
bh_file_target = os.path.join(target_dir, "bssn_BH.dat")
constraint_file = os.path.join(target_dir, "bssn_constraint.dat")
# Check if files exist
if not os.path.exists(bh_file_ref):
print(f"{Color.RED}{Color.BOLD}Error:{Color.RESET} Baseline trajectory file not found: {bh_file_ref}")
sys.exit(1)
if not os.path.exists(bh_file_target):
print(f"{Color.RED}{Color.BOLD}Error:{Color.RESET} Target trajectory file not found: {bh_file_target}")
sys.exit(1)
if not os.path.exists(constraint_file):
print(f"{Color.RED}{Color.BOLD}Error:{Color.RESET} Constraint data file not found: {constraint_file}")
sys.exit(1)
# Print header
print_header()
print(f"\n{Color.BOLD}Reference (Baseline):{Color.RESET} {Color.BLUE}{reference_dir}{Color.RESET}")
print(f"{Color.BOLD}Target (Optimized): {Color.RESET} {Color.BLUE}{target_dir}{Color.RESET}")
# Load data
bh_data_ref = load_bh_trajectory(bh_file_ref)
bh_data_target = load_bh_trajectory(bh_file_target)
constraint_data = load_constraint_data(constraint_file)
# Calculate RMS error
rms_rel, error = calculate_rms_error(bh_data_ref, bh_data_target)
rms_passed = print_rms_results(rms_rel, error)
# Analyze constraint violation
constraint_results = analyze_constraint_violation(constraint_data)
constraint_passed = print_constraint_results(constraint_results)
# Print summary
all_passed = print_summary(rms_passed, constraint_passed)
# Return exit code
sys.exit(0 if all_passed else 1)
if __name__ == "__main__":
main()

File diff suppressed because it is too large Load Diff

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@@ -1,8 +1,7 @@
#ifndef TWO_PUNCTURES_H
#define TWO_PUNCTURES_H
#include <omp.h>
#define StencilSize 19
#define N_PlaneRelax 1
#define NRELAX 200
@@ -33,7 +32,7 @@ private:
int npoints_A, npoints_B, npoints_phi;
double target_M_plus, target_M_minus;
double admMass;
double adm_tol;
@@ -43,18 +42,6 @@ private:
int ntotal;
// ===== Precomputed spectral derivative matrices =====
double *D1_A, *D2_A;
double *D1_B, *D2_B;
double *DF1_phi, *DF2_phi;
// ===== Pre-allocated workspace for LineRelax (per-thread) =====
int max_threads;
double **ws_diag_be, **ws_e_be, **ws_f_be, **ws_b_be, **ws_x_be;
double **ws_l_be, **ws_u_be, **ws_d_be, **ws_y_be;
double **ws_diag_al, **ws_e_al, **ws_f_al, **ws_b_al, **ws_x_al;
double **ws_l_al, **ws_u_al, **ws_d_al, **ws_y_al;
struct parameters
{
int nvar, n1, n2, n3;
@@ -71,28 +58,6 @@ public:
int Newtonmaxit);
~TwoPunctures();
// 02/07: New/modified methods
void allocate_workspace();
void free_workspace();
void precompute_derivative_matrices();
void build_cheb_deriv_matrices(int n, double *D1, double *D2);
void build_fourier_deriv_matrices(int N, double *DF1, double *DF2);
void Derivatives_AB3_MatMul(int nvar, int n1, int n2, int n3, derivs v);
void ThomasAlgorithm_ws(int N, double *b, double *a, double *c, double *x, double *q,
double *l, double *u_ws, double *d, double *y);
void LineRelax_be_omp(double *dv,
int const i, int const k, int const nvar,
int const n1, int const n2, int const n3,
double const *rhs, int const *ncols, int **cols,
double **JFD, int tid);
void LineRelax_al_omp(double *dv,
int const j, int const k, int const nvar,
int const n1, int const n2, int const n3,
double const *rhs, int const *ncols,
int **cols, double **JFD, int tid);
void relax_omp(double *dv, int const nvar, int const n1, int const n2, int const n3,
double const *rhs, int const *ncols, int **cols, double **JFD);
void Solve();
void set_initial_guess(derivs v);
int index(int i, int j, int k, int l, int a, int b, int c, int d);
@@ -151,11 +116,23 @@ public:
double BY_KKofxyz(double x, double y, double z);
void SetMatrix_JFD(int nvar, int n1, int n2, int n3, derivs u, int *ncols, int **cols, double **Matrix);
void J_times_dv(int nvar, int n1, int n2, int n3, derivs dv, double *Jdv, derivs u);
void relax(double *dv, int const nvar, int const n1, int const n2, int const n3,
double const *rhs, int const *ncols, int **cols, double **JFD);
void LineRelax_be(double *dv,
int const i, int const k, int const nvar,
int const n1, int const n2, int const n3,
double const *rhs, int const *ncols, int **cols,
double **JFD);
void JFD_times_dv(int i, int j, int k, int nvar, int n1, int n2,
int n3, derivs dv, derivs u, double *values);
void LinEquations(double A, double B, double X, double R,
double x, double r, double phi,
double y, double z, derivs dU, derivs U, double *values);
void LineRelax_al(double *dv,
int const j, int const k, int const nvar,
int const n1, int const n2, int const n3,
double const *rhs, int const *ncols,
int **cols, double **JFD);
void ThomasAlgorithm(int N, double *b, double *a, double *c, double *x, double *q);
void Save(char *fname);
// provided by Vasileios Paschalidis (vpaschal@illinois.edu)
@@ -164,4 +141,4 @@ public:
void SpecCoef(parameters par, int ivar, double *v, double *cf);
};
#endif /* TWO_PUNCTURES_H */
#endif /* TWO_PUNCTURES_H */

File diff suppressed because it is too large Load Diff

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@@ -17,62 +17,50 @@
real*8, dimension(ex(1),ex(2),ex(3)), intent(inout) :: Axx,Axy,Axz
real*8, dimension(ex(1),ex(2),ex(3)), intent(inout) :: Ayy,Ayz,Azz
!~~~~~~~> Local variable:
integer :: i,j,k
real*8 :: lgxx,lgyy,lgzz,ldetg
real*8 :: lgupxx,lgupxy,lgupxz,lgupyy,lgupyz,lgupzz
real*8 :: ltrA,lscale
real*8, parameter :: F1o3 = 1.D0 / 3.D0, ONE = 1.D0, TWO = 2.D0
!~~~~~~>
do k=1,ex(3)
do j=1,ex(2)
do i=1,ex(1)
lgxx = dxx(i,j,k) + ONE
lgyy = dyy(i,j,k) + ONE
lgzz = dzz(i,j,k) + ONE
ldetg = lgxx * lgyy * lgzz &
+ gxy(i,j,k) * gyz(i,j,k) * gxz(i,j,k) &
+ gxz(i,j,k) * gxy(i,j,k) * gyz(i,j,k) &
- gxz(i,j,k) * lgyy * gxz(i,j,k) &
- gxy(i,j,k) * gxy(i,j,k) * lgzz &
- lgxx * gyz(i,j,k) * gyz(i,j,k)
lgupxx = ( lgyy * lgzz - gyz(i,j,k) * gyz(i,j,k) ) / ldetg
lgupxy = - ( gxy(i,j,k) * lgzz - gyz(i,j,k) * gxz(i,j,k) ) / ldetg
lgupxz = ( gxy(i,j,k) * gyz(i,j,k) - lgyy * gxz(i,j,k) ) / ldetg
lgupyy = ( lgxx * lgzz - gxz(i,j,k) * gxz(i,j,k) ) / ldetg
lgupyz = - ( lgxx * gyz(i,j,k) - gxy(i,j,k) * gxz(i,j,k) ) / ldetg
lgupzz = ( lgxx * lgyy - gxy(i,j,k) * gxy(i,j,k) ) / ldetg
ltrA = lgupxx * Axx(i,j,k) + lgupyy * Ayy(i,j,k) &
+ lgupzz * Azz(i,j,k) &
+ TWO * (lgupxy * Axy(i,j,k) + lgupxz * Axz(i,j,k) &
+ lgupyz * Ayz(i,j,k))
Axx(i,j,k) = Axx(i,j,k) - F1o3 * lgxx * ltrA
Axy(i,j,k) = Axy(i,j,k) - F1o3 * gxy(i,j,k) * ltrA
Axz(i,j,k) = Axz(i,j,k) - F1o3 * gxz(i,j,k) * ltrA
Ayy(i,j,k) = Ayy(i,j,k) - F1o3 * lgyy * ltrA
Ayz(i,j,k) = Ayz(i,j,k) - F1o3 * gyz(i,j,k) * ltrA
Azz(i,j,k) = Azz(i,j,k) - F1o3 * lgzz * ltrA
lscale = ONE / ( ldetg ** F1o3 )
dxx(i,j,k) = lgxx * lscale - ONE
gxy(i,j,k) = gxy(i,j,k) * lscale
gxz(i,j,k) = gxz(i,j,k) * lscale
dyy(i,j,k) = lgyy * lscale - ONE
gyz(i,j,k) = gyz(i,j,k) * lscale
dzz(i,j,k) = lgzz * lscale - ONE
enddo
enddo
enddo
!~~~~~~~> Local variable:
real*8, dimension(ex(1),ex(2),ex(3)) :: trA,detg
real*8, dimension(ex(1),ex(2),ex(3)) :: gxx,gyy,gzz
real*8, dimension(ex(1),ex(2),ex(3)) :: gupxx,gupxy,gupxz,gupyy,gupyz,gupzz
real*8, parameter :: F1o3 = 1.D0 / 3.D0, ONE = 1.D0, TWO = 2.D0
!~~~~~~>
gxx = dxx + ONE
gyy = dyy + ONE
gzz = dzz + ONE
detg = gxx * gyy * gzz + gxy * gyz * gxz + gxz * gxy * gyz - &
gxz * gyy * gxz - gxy * gxy * gzz - gxx * gyz * gyz
gupxx = ( gyy * gzz - gyz * gyz ) / detg
gupxy = - ( gxy * gzz - gyz * gxz ) / detg
gupxz = ( gxy * gyz - gyy * gxz ) / detg
gupyy = ( gxx * gzz - gxz * gxz ) / detg
gupyz = - ( gxx * gyz - gxy * gxz ) / detg
gupzz = ( gxx * gyy - gxy * gxy ) / detg
trA = gupxx * Axx + gupyy * Ayy + gupzz * Azz &
+ TWO * (gupxy * Axy + gupxz * Axz + gupyz * Ayz)
Axx = Axx - F1o3 * gxx * trA
Axy = Axy - F1o3 * gxy * trA
Axz = Axz - F1o3 * gxz * trA
Ayy = Ayy - F1o3 * gyy * trA
Ayz = Ayz - F1o3 * gyz * trA
Azz = Azz - F1o3 * gzz * trA
detg = ONE / ( detg ** F1o3 )
gxx = gxx * detg
gxy = gxy * detg
gxz = gxz * detg
gyy = gyy * detg
gyz = gyz * detg
gzz = gzz * detg
dxx = gxx - ONE
dyy = gyy - ONE
dzz = gzz - ONE
return
@@ -93,72 +81,52 @@
real*8, dimension(ex(1),ex(2),ex(3)), intent(inout) :: Axx,Axy,Axz
real*8, dimension(ex(1),ex(2),ex(3)), intent(inout) :: Ayy,Ayz,Azz
!~~~~~~~> Local variable:
integer :: i,j,k
real*8 :: lgxx,lgyy,lgzz,lscale
real*8 :: lgxy,lgxz,lgyz
real*8 :: lgupxx,lgupxy,lgupxz,lgupyy,lgupyz,lgupzz
real*8 :: ltrA
real*8, parameter :: F1o3 = 1.D0 / 3.D0, ONE = 1.D0, TWO = 2.D0
!~~~~~~>
do k=1,ex(3)
do j=1,ex(2)
do i=1,ex(1)
! for g: normalize determinant first
lgxx = dxx(i,j,k) + ONE
lgyy = dyy(i,j,k) + ONE
lgzz = dzz(i,j,k) + ONE
lgxy = gxy(i,j,k)
lgxz = gxz(i,j,k)
lgyz = gyz(i,j,k)
lscale = lgxx * lgyy * lgzz + lgxy * lgyz * lgxz &
+ lgxz * lgxy * lgyz - lgxz * lgyy * lgxz &
- lgxy * lgxy * lgzz - lgxx * lgyz * lgyz
lscale = ONE / ( lscale ** F1o3 )
lgxx = lgxx * lscale
lgxy = lgxy * lscale
lgxz = lgxz * lscale
lgyy = lgyy * lscale
lgyz = lgyz * lscale
lgzz = lgzz * lscale
dxx(i,j,k) = lgxx - ONE
gxy(i,j,k) = lgxy
gxz(i,j,k) = lgxz
dyy(i,j,k) = lgyy - ONE
gyz(i,j,k) = lgyz
dzz(i,j,k) = lgzz - ONE
! for A: trace-free using normalized metric (det=1, no division needed)
lgupxx = ( lgyy * lgzz - lgyz * lgyz )
lgupxy = - ( lgxy * lgzz - lgyz * lgxz )
lgupxz = ( lgxy * lgyz - lgyy * lgxz )
lgupyy = ( lgxx * lgzz - lgxz * lgxz )
lgupyz = - ( lgxx * lgyz - lgxy * lgxz )
lgupzz = ( lgxx * lgyy - lgxy * lgxy )
ltrA = lgupxx * Axx(i,j,k) + lgupyy * Ayy(i,j,k) &
+ lgupzz * Azz(i,j,k) &
+ TWO * (lgupxy * Axy(i,j,k) + lgupxz * Axz(i,j,k) &
+ lgupyz * Ayz(i,j,k))
Axx(i,j,k) = Axx(i,j,k) - F1o3 * lgxx * ltrA
Axy(i,j,k) = Axy(i,j,k) - F1o3 * lgxy * ltrA
Axz(i,j,k) = Axz(i,j,k) - F1o3 * lgxz * ltrA
Ayy(i,j,k) = Ayy(i,j,k) - F1o3 * lgyy * ltrA
Ayz(i,j,k) = Ayz(i,j,k) - F1o3 * lgyz * ltrA
Azz(i,j,k) = Azz(i,j,k) - F1o3 * lgzz * ltrA
enddo
enddo
enddo
!~~~~~~~> Local variable:
real*8, dimension(ex(1),ex(2),ex(3)) :: trA
real*8, dimension(ex(1),ex(2),ex(3)) :: gxx,gyy,gzz
real*8, dimension(ex(1),ex(2),ex(3)) :: gupxx,gupxy,gupxz,gupyy,gupyz,gupzz
real*8, parameter :: F1o3 = 1.D0 / 3.D0, ONE = 1.D0, TWO = 2.D0
!~~~~~~>
gxx = dxx + ONE
gyy = dyy + ONE
gzz = dzz + ONE
! for g
gupzz = gxx * gyy * gzz + gxy * gyz * gxz + gxz * gxy * gyz - &
gxz * gyy * gxz - gxy * gxy * gzz - gxx * gyz * gyz
gupzz = ONE / ( gupzz ** F1o3 )
gxx = gxx * gupzz
gxy = gxy * gupzz
gxz = gxz * gupzz
gyy = gyy * gupzz
gyz = gyz * gupzz
gzz = gzz * gupzz
dxx = gxx - ONE
dyy = gyy - ONE
dzz = gzz - ONE
! for A
gupxx = ( gyy * gzz - gyz * gyz )
gupxy = - ( gxy * gzz - gyz * gxz )
gupxz = ( gxy * gyz - gyy * gxz )
gupyy = ( gxx * gzz - gxz * gxz )
gupyz = - ( gxx * gyz - gxy * gxz )
gupzz = ( gxx * gyy - gxy * gxy )
trA = gupxx * Axx + gupyy * Ayy + gupzz * Azz &
+ TWO * (gupxy * Axy + gupxz * Axz + gupyz * Ayz)
Axx = Axx - F1o3 * gxx * trA
Axy = Axy - F1o3 * gxy * trA
Axz = Axz - F1o3 * gxz * trA
Ayy = Ayy - F1o3 * gyy * trA
Ayz = Ayz - F1o3 * gyz * trA
Azz = Azz - F1o3 * gzz * trA
return

View File

@@ -324,7 +324,8 @@ subroutine symmetry_bd(ord,extc,func,funcc,SoA)
integer::i
funcc(1:extc(1),1:extc(2),1:extc(3)) = func
funcc = 0.d0
funcc(1:extc(1),1:extc(2),1:extc(3)) = func
do i=0,ord-1
funcc(-i,1:extc(2),1:extc(3)) = funcc(i+2,1:extc(2),1:extc(3))*SoA(1)
enddo
@@ -349,7 +350,8 @@ subroutine symmetry_tbd(ord,extc,func,funcc,SoA)
integer::i
funcc(1:extc(1),1:extc(2),1:extc(3)) = func
funcc = 0.d0
funcc(1:extc(1),1:extc(2),1:extc(3)) = func
do i=0,ord-1
funcc(-i,1:extc(2),1:extc(3)) = funcc(i+2,1:extc(2),1:extc(3))*SoA(1)
funcc(extc(1)+1+i,1:extc(2),1:extc(3)) = funcc(extc(1)-1-i,1:extc(2),1:extc(3))*SoA(1)
@@ -377,7 +379,8 @@ subroutine symmetry_stbd(ord,extc,func,funcc,SoA)
integer::i
funcc(1:extc(1),1:extc(2),1:extc(3)) = func
funcc = 0.d0
funcc(1:extc(1),1:extc(2),1:extc(3)) = func
do i=0,ord-1
funcc(-i,1:extc(2),1:extc(3)) = funcc(i+2,1:extc(2),1:extc(3))*SoA(1)
funcc(extc(1)+1+i,1:extc(2),1:extc(3)) = funcc(extc(1)-1-i,1:extc(2),1:extc(3))*SoA(1)
@@ -883,20 +886,17 @@ subroutine symmetry_bd(ord,extc,func,funcc,SoA)
integer::i
!DIR$ SIMD VECTORLENGTHFOR(KNOWN_INTEGER=8)
funcc(1:extc(1),1:extc(2),1:extc(3)) = func
!DIR$ SIMD VECTORLENGTHFOR(KNOWN_INTEGER=8)
do i=0,ord-1
funcc(-i,1:extc(2),1:extc(3)) = funcc(i+1,1:extc(2),1:extc(3))*SoA(1)
enddo
!DIR$ SIMD VECTORLENGTHFOR(KNOWN_INTEGER=8)
do i=0,ord-1
funcc(:,-i,1:extc(3)) = funcc(:,i+1,1:extc(3))*SoA(2)
enddo
!DIR$ SIMD VECTORLENGTHFOR(KNOWN_INTEGER=8)
do i=0,ord-1
funcc(:,:,-i) = funcc(:,:,i+1)*SoA(3)
enddo
funcc = 0.d0
funcc(1:extc(1),1:extc(2),1:extc(3)) = func
do i=0,ord-1
funcc(-i,1:extc(2),1:extc(3)) = funcc(i+1,1:extc(2),1:extc(3))*SoA(1)
enddo
do i=0,ord-1
funcc(:,-i,1:extc(3)) = funcc(:,i+1,1:extc(3))*SoA(2)
enddo
do i=0,ord-1
funcc(:,:,-i) = funcc(:,:,i+1)*SoA(3)
enddo
end subroutine symmetry_bd
@@ -912,7 +912,8 @@ subroutine symmetry_tbd(ord,extc,func,funcc,SoA)
integer::i
funcc(1:extc(1),1:extc(2),1:extc(3)) = func
funcc = 0.d0
funcc(1:extc(1),1:extc(2),1:extc(3)) = func
do i=0,ord-1
funcc(-i,1:extc(2),1:extc(3)) = funcc(i+1,1:extc(2),1:extc(3))*SoA(1)
funcc(extc(1)+1+i,1:extc(2),1:extc(3)) = funcc(extc(1)-i,1:extc(2),1:extc(3))*SoA(1)
@@ -940,7 +941,8 @@ subroutine symmetry_stbd(ord,extc,func,funcc,SoA)
integer::i
funcc(1:extc(1),1:extc(2),1:extc(3)) = func
funcc = 0.d0
funcc(1:extc(1),1:extc(2),1:extc(3)) = func
do i=0,ord-1
funcc(-i,1:extc(2),1:extc(3)) = funcc(i+1,1:extc(2),1:extc(3))*SoA(1)
funcc(extc(1)+1+i,1:extc(2),1:extc(3)) = funcc(extc(1)-i,1:extc(2),1:extc(3))*SoA(1)
@@ -1111,353 +1113,142 @@ end subroutine d2dump
!~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
!~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
!~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
! common code for cell and vertex
!------------------------------------------------------------------------------
! Lagrangian polynomial interpolation
!------------------------------------------------------------------------------
#ifndef POLINT6_USE_BARYCENTRIC
#define POLINT6_USE_BARYCENTRIC 1
#endif
!DIR$ ATTRIBUTES FORCEINLINE :: polint6_neville
subroutine polint6_neville(xa, ya, x, y, dy)
implicit none
real*8, dimension(6), intent(in) :: xa, ya
real*8, intent(in) :: x
real*8, intent(out) :: y, dy
integer :: i, m, ns, n_m
real*8, dimension(6) :: c, d, ho
real*8 :: dif, dift, hp, h, den_val
c = ya
d = ya
ho = xa - x
ns = 1
dif = abs(x - xa(1))
do i = 2, 6
dift = abs(x - xa(i))
if (dift < dif) then
ns = i
dif = dift
end if
end do
y = ya(ns)
ns = ns - 1
do m = 1, 5
n_m = 6 - m
do i = 1, n_m
hp = ho(i)
h = ho(i+m)
den_val = hp - h
if (den_val == 0.0d0) then
write(*,*) 'failure in polint for point',x
write(*,*) 'with input points: ',xa
stop
end if
den_val = (c(i+1) - d(i)) / den_val
d(i) = h * den_val
c(i) = hp * den_val
end do
if (2 * ns < n_m) then
dy = c(ns + 1)
else
dy = d(ns)
ns = ns - 1
end if
y = y + dy
end do
return
end subroutine polint6_neville
!DIR$ ATTRIBUTES FORCEINLINE :: polint6_barycentric
subroutine polint6_barycentric(xa, ya, x, y, dy)
implicit none
real*8, dimension(6), intent(in) :: xa, ya
real*8, intent(in) :: x
real*8, intent(out) :: y, dy
integer :: i, j
logical :: is_uniform
real*8, dimension(6) :: lambda
real*8 :: dx, den_i, term, num, den, step, tol
real*8, parameter :: c_uniform(6) = (/ -1.d0, 5.d0, -10.d0, 10.d0, -5.d0, 1.d0 /)
do i = 1, 6
if (x == xa(i)) then
y = ya(i)
dy = 0.d0
return
end if
end do
step = xa(2) - xa(1)
is_uniform = (step /= 0.d0)
if (is_uniform) then
tol = 64.d0 * epsilon(1.d0) * max(1.d0, abs(step))
do i = 3, 6
if (abs((xa(i) - xa(i-1)) - step) > tol) then
is_uniform = .false.
exit
end if
end do
end if
if (is_uniform) then
num = 0.d0
den = 0.d0
do i = 1, 6
term = c_uniform(i) / (x - xa(i))
num = num + term * ya(i)
den = den + term
end do
y = num / den
dy = 0.d0
return
end if
do i = 1, 6
den_i = 1.d0
do j = 1, 6
if (j /= i) then
dx = xa(i) - xa(j)
if (dx == 0.0d0) then
write(*,*) 'failure in polint for point',x
write(*,*) 'with input points: ',xa
stop
end if
den_i = den_i * dx
end if
end do
lambda(i) = 1.d0 / den_i
end do
num = 0.d0
den = 0.d0
do i = 1, 6
term = lambda(i) / (x - xa(i))
num = num + term * ya(i)
den = den + term
end do
y = num / den
dy = 0.d0
return
end subroutine polint6_barycentric
!DIR$ ATTRIBUTES FORCEINLINE :: polint
subroutine polint(xa, ya, x, y, dy, ordn)
implicit none
integer, intent(in) :: ordn
real*8, dimension(ordn), intent(in) :: xa, ya
real*8, intent(in) :: x
real*8, intent(out) :: y, dy
integer :: i, m, ns, n_m
real*8, dimension(ordn) :: c, d, ho
real*8 :: dif, dift, hp, h, den_val
if (ordn == 6) then
#if POLINT6_USE_BARYCENTRIC
call polint6_barycentric(xa, ya, x, y, dy)
#else
call polint6_neville(xa, ya, x, y, dy)
#endif
return
end if
c = ya
d = ya
ho = xa - x
ns = 1
dif = abs(x - xa(1))
do i = 2, ordn
dift = abs(x - xa(i))
if (dift < dif) then
ns = i
dif = dift
end if
end do
y = ya(ns)
ns = ns - 1
do m = 1, ordn - 1
n_m = ordn - m
do i = 1, n_m
hp = ho(i)
h = ho(i+m)
den_val = hp - h
if (den_val == 0.0d0) then
write(*,*) 'failure in polint for point',x
write(*,*) 'with input points: ',xa
stop
end if
den_val = (c(i+1) - d(i)) / den_val
d(i) = h * den_val
c(i) = hp * den_val
end do
if (2 * ns < n_m) then
dy = c(ns + 1)
else
dy = d(ns)
ns = ns - 1
end if
y = y + dy
end do
return
end subroutine polint
!------------------------------------------------------------------------------
! Compute Lagrange interpolation basis weights for one target point.
!------------------------------------------------------------------------------
!DIR$ ATTRIBUTES FORCEINLINE :: polint_lagrange_weights
subroutine polint_lagrange_weights(xa, x, w, ordn)
implicit none
integer, intent(in) :: ordn
real*8, dimension(1:ordn), intent(in) :: xa
real*8, intent(in) :: x
real*8, dimension(1:ordn), intent(out) :: w
integer :: i, j
real*8 :: num, den, dx
do i = 1, ordn
num = 1.d0
den = 1.d0
do j = 1, ordn
if (j /= i) then
dx = xa(i) - xa(j)
if (dx == 0.0d0) then
write(*,*) 'failure in polint for point',x
write(*,*) 'with input points: ',xa
stop
end if
num = num * (x - xa(j))
den = den * dx
end if
end do
w(i) = num / den
end do
return
end subroutine polint_lagrange_weights
!------------------------------------------------------------------------------
!
! interpolation in 2 dimensions, follow yx order
!
!------------------------------------------------------------------------------
subroutine polin2(x1a,x2a,ya,x1,x2,y,dy,ordn)
implicit none
integer,intent(in) :: ordn
real*8, dimension(1:ordn), intent(in) :: x1a,x2a
real*8, dimension(1:ordn,1:ordn), intent(in) :: ya
real*8, intent(in) :: x1,x2
real*8, intent(out) :: y,dy
#ifdef POLINT_LEGACY_ORDER
integer :: i,m
real*8, dimension(ordn) :: ymtmp
real*8, dimension(ordn) :: yntmp
m=size(x1a)
do i=1,m
yntmp=ya(i,:)
call polint(x2a,yntmp,x2,ymtmp(i),dy,ordn)
end do
call polint(x1a,ymtmp,x1,y,dy,ordn)
#else
integer :: j
real*8, dimension(ordn) :: ymtmp
real*8 :: dy_temp
do j=1,ordn
call polint(x1a, ya(:,j), x1, ymtmp(j), dy_temp, ordn)
end do
call polint(x2a, ymtmp, x2, y, dy, ordn)
#endif
return
end subroutine polin2
!------------------------------------------------------------------------------
!
! interpolation in 3 dimensions, follow zyx order
!
!------------------------------------------------------------------------------
subroutine polin3(x1a,x2a,x3a,ya,x1,x2,x3,y,dy,ordn)
implicit none
integer,intent(in) :: ordn
real*8, dimension(1:ordn), intent(in) :: x1a,x2a,x3a
real*8, dimension(1:ordn,1:ordn,1:ordn), intent(in) :: ya
real*8, intent(in) :: x1,x2,x3
real*8, intent(out) :: y,dy
#ifdef POLINT_LEGACY_ORDER
integer :: i,j,m,n
real*8, dimension(ordn,ordn) :: yatmp
real*8, dimension(ordn) :: ymtmp
real*8, dimension(ordn) :: yntmp
real*8, dimension(ordn) :: yqtmp
m=size(x1a)
n=size(x2a)
do i=1,m
do j=1,n
yqtmp=ya(i,j,:)
call polint(x3a,yqtmp,x3,yatmp(i,j),dy,ordn)
end do
yntmp=yatmp(i,:)
call polint(x2a,yntmp,x2,ymtmp(i),dy,ordn)
end do
call polint(x1a,ymtmp,x1,y,dy,ordn)
#else
integer :: i, j, k
real*8, dimension(ordn) :: w1, w2
real*8, dimension(ordn) :: ymtmp
real*8 :: yx_sum, x_sum
call polint_lagrange_weights(x1a, x1, w1, ordn)
call polint_lagrange_weights(x2a, x2, w2, ordn)
do k = 1, ordn
yx_sum = 0.d0
do j = 1, ordn
x_sum = 0.d0
do i = 1, ordn
x_sum = x_sum + w1(i) * ya(i,j,k)
end do
yx_sum = yx_sum + w2(j) * x_sum
end do
ymtmp(k) = yx_sum
end do
call polint(x3a, ymtmp, x3, y, dy, ordn)
#endif
return
end subroutine polin3
! common code for cell and vertex
!------------------------------------------------------------------------------
! Lagrangian polynomial interpolation
!------------------------------------------------------------------------------
subroutine polint(xa, ya, x, y, dy, ordn)
implicit none
integer, intent(in) :: ordn
real*8, dimension(ordn), intent(in) :: xa, ya
real*8, intent(in) :: x
real*8, intent(out) :: y, dy
integer :: i, m, ns, n_m
real*8, dimension(ordn) :: c, d, ho
real*8 :: dif, dift, hp, h, den_val
! Initialization
c = ya
d = ya
ho = xa - x
ns = 1
dif = abs(x - xa(1))
! Find the index of the closest table entry
do i = 2, ordn
dift = abs(x - xa(i))
if (dift < dif) then
ns = i
dif = dift
end if
end do
y = ya(ns)
ns = ns - 1
! Main Neville's algorithm loop
do m = 1, ordn - 1
n_m = ordn - m
do i = 1, n_m
hp = ho(i)
h = ho(i+m)
den_val = hp - h
! Check for division by zero locally
if (den_val == 0.0d0) then
write(*,*) 'failure in polint for point',x
write(*,*) 'with input points: ',xa
stop
end if
! Reuse den_val to avoid redundant divisions
den_val = (c(i+1) - d(i)) / den_val
! Update c and d in place
d(i) = h * den_val
c(i) = hp * den_val
end do
! Decide which path (up or down the tableau) to take
if (2 * ns < n_m) then
dy = c(ns + 1)
else
dy = d(ns)
ns = ns - 1
end if
y = y + dy
end do
return
end subroutine polint
!------------------------------------------------------------------------------
!
! interpolation in 2 dimensions, follow yx order
!
!------------------------------------------------------------------------------
subroutine polin2(x1a,x2a,ya,x1,x2,y,dy,ordn)
implicit none
integer,intent(in) :: ordn
real*8, dimension(ordn), intent(in) :: x1a,x2a
real*8, dimension(ordn,ordn), intent(in) :: ya
real*8, intent(in) :: x1,x2
real*8, intent(out) :: y,dy
integer :: j
real*8, dimension(ordn) :: ymtmp
real*8 :: dy_temp ! Local variable to prevent overwriting result
! Optimized sequence: Loop over columns (j)
! ya(:,j) is a contiguous memory block in Fortran
do j=1,ordn
call polint(x1a, ya(:,j), x1, ymtmp(j), dy_temp, ordn)
end do
! Final interpolation on the results
call polint(x2a, ymtmp, x2, y, dy, ordn)
return
end subroutine polin2
!------------------------------------------------------------------------------
!
! interpolation in 3 dimensions, follow zyx order
!
!------------------------------------------------------------------------------
subroutine polin3(x1a,x2a,x3a,ya,x1,x2,x3,y,dy,ordn)
implicit none
integer,intent(in) :: ordn
real*8, dimension(ordn), intent(in) :: x1a,x2a,x3a
real*8, dimension(ordn,ordn,ordn), intent(in) :: ya
real*8, intent(in) :: x1,x2,x3
real*8, intent(out) :: y,dy
integer :: j, k
real*8, dimension(ordn,ordn) :: yatmp
real*8, dimension(ordn) :: ymtmp
real*8 :: dy_temp
! Sequence change: Process the contiguous first dimension (x1) first.
! We loop through the 'slow' planes (j, k) to extract 'fast' columns.
do k=1,ordn
do j=1,ordn
! ya(:,j,k) is contiguous; much faster than ya(i,j,:)
call polint(x1a, ya(:,j,k), x1, yatmp(j,k), dy_temp, ordn)
end do
end do
! Now process the second dimension
do k=1,ordn
call polint(x2a, yatmp(:,k), x2, ymtmp(k), dy_temp, ordn)
end do
! Final dimension
call polint(x3a, ymtmp, x3, y, dy, ordn)
return
end subroutine polin3
!--------------------------------------------------------------------------------------
! calculate L2norm
subroutine l2normhelper(ex, X, Y, Z,xmin,ymin,zmin,xmax,ymax,zmax,&
@@ -1476,9 +1267,7 @@ end subroutine d2dump
real*8 :: dX, dY, dZ
integer::imin,jmin,kmin
integer::imax,jmax,kmax
integer::i,j,k,n_elements
real*8, dimension(:), allocatable :: f_flat
real*8, external :: DDOT
integer::i,j,k
dX = X(2) - X(1)
dY = Y(2) - Y(1)
@@ -1502,91 +1291,15 @@ if(dabs(X(1)-xmin) < dX) imin = 1
if(dabs(Y(1)-ymin) < dY) jmin = 1
if(dabs(Z(1)-zmin) < dZ) kmin = 1
n_elements = (imax-imin+1)*(jmax-jmin+1)*(kmax-kmin+1)
allocate(f_flat(n_elements))
f_flat = reshape(f(imin:imax,jmin:jmax,kmin:kmax), [n_elements])
f_out = DDOT(n_elements, f_flat, 1, f_flat, 1)
deallocate(f_flat)
f_out = sum(f(imin:imax,jmin:jmax,kmin:kmax)*f(imin:imax,jmin:jmax,kmin:kmax))
f_out = f_out*dX*dY*dZ
return
end subroutine l2normhelper
!--------------------------------------------------------------------------------------
subroutine l2normhelper7(ex, X, Y, Z,xmin,ymin,zmin,xmax,ymax,zmax,&
f1,f2,f3,f4,f5,f6,f7,f_out,gw)
implicit none
!~~~~~~> Input parameters:
integer,intent(in ):: ex(1:3)
real*8, intent(in ):: X(1:ex(1)),Y(1:ex(2)),Z(1:ex(3)),xmin,ymin,zmin,xmax,ymax,zmax
integer,intent(in)::gw
real*8, dimension(ex(1),ex(2),ex(3)),intent(in) :: f1,f2,f3,f4,f5,f6,f7
real*8, intent(out) :: f_out(7)
!~~~~~~> Other variables:
real*8 :: dX, dY, dZ
integer::imin,jmin,kmin
integer::imax,jmax,kmax
integer::i,j,k
real*8 :: s1,s2,s3,s4,s5,s6,s7
dX = X(2) - X(1)
dY = Y(2) - Y(1)
dZ = Z(2) - Z(1)
imin = gw+1
jmin = gw+1
kmin = gw+1
imax = ex(1) - gw
jmax = ex(2) - gw
kmax = ex(3) - gw
if(dabs(X(ex(1))-xmax) < dX) imax = ex(1)
if(dabs(Y(ex(2))-ymax) < dY) jmax = ex(2)
if(dabs(Z(ex(3))-zmax) < dZ) kmax = ex(3)
if(dabs(X(1)-xmin) < dX) imin = 1
if(dabs(Y(1)-ymin) < dY) jmin = 1
if(dabs(Z(1)-zmin) < dZ) kmin = 1
s1 = 0.d0
s2 = 0.d0
s3 = 0.d0
s4 = 0.d0
s5 = 0.d0
s6 = 0.d0
s7 = 0.d0
do k=kmin,kmax
do j=jmin,jmax
!DIR$ SIMD REDUCTION(+:s1,s2,s3,s4,s5,s6,s7)
do i=imin,imax
s1 = s1 + f1(i,j,k)*f1(i,j,k)
s2 = s2 + f2(i,j,k)*f2(i,j,k)
s3 = s3 + f3(i,j,k)*f3(i,j,k)
s4 = s4 + f4(i,j,k)*f4(i,j,k)
s5 = s5 + f5(i,j,k)*f5(i,j,k)
s6 = s6 + f6(i,j,k)*f6(i,j,k)
s7 = s7 + f7(i,j,k)*f7(i,j,k)
enddo
enddo
enddo
f_out(1) = s1*dX*dY*dZ
f_out(2) = s2*dX*dY*dZ
f_out(3) = s3*dX*dY*dZ
f_out(4) = s4*dX*dY*dZ
f_out(5) = s5*dX*dY*dZ
f_out(6) = s6*dX*dY*dZ
f_out(7) = s7*dX*dY*dZ
return
end subroutine l2normhelper7
!--------------------------------------------------------------------------------------
! calculate L2norm especially for shell Blocks
!--------------------------------------------------------------------------------------
! calculate L2norm especially for shell Blocks
subroutine l2normhelper_sh(ex, X, Y, Z,xmin,ymin,zmin,xmax,ymax,zmax,&
f,f_out,gw,ogw,Symmetry)
@@ -1603,9 +1316,7 @@ if(dabs(Z(1)-zmin) < dZ) kmin = 1
real*8 :: dX, dY, dZ
integer::imin,jmin,kmin
integer::imax,jmax,kmax
integer::i,j,k,n_elements
real*8, dimension(:), allocatable :: f_flat
real*8, external :: DDOT
integer::i,j,k
real*8 :: PIo4
@@ -1668,11 +1379,7 @@ if(Symmetry==2)then
if(dabs(ymin+gw*dY)<dY.and.Y(1)<0.d0) jmin = gw+1
endif
n_elements = (imax-imin+1)*(jmax-jmin+1)*(kmax-kmin+1)
allocate(f_flat(n_elements))
f_flat = reshape(f(imin:imax,jmin:jmax,kmin:kmax), [n_elements])
f_out = DDOT(n_elements, f_flat, 1, f_flat, 1)
deallocate(f_flat)
f_out = sum(f(imin:imax,jmin:jmax,kmin:kmax)*f(imin:imax,jmin:jmax,kmin:kmax))
f_out = f_out*dX*dY*dZ
@@ -1699,9 +1406,7 @@ f_out = f_out*dX*dY*dZ
real*8 :: dX, dY, dZ
integer::imin,jmin,kmin
integer::imax,jmax,kmax
integer::i,j,k
real*8, dimension(:), allocatable :: f_flat
real*8, external :: DDOT
integer::i,j,k
real*8 :: PIo4
@@ -1764,11 +1469,11 @@ if(Symmetry==2)then
if(dabs(ymin+gw*dY)<dY.and.Y(1)<0.d0) jmin = gw+1
endif
Nout = (imax-imin+1)*(jmax-jmin+1)*(kmax-kmin+1)
allocate(f_flat(Nout))
f_flat = reshape(f(imin:imax,jmin:jmax,kmin:kmax), [Nout])
f_out = DDOT(Nout, f_flat, 1, f_flat, 1)
deallocate(f_flat)
f_out = sum(f(imin:imax,jmin:jmax,kmin:kmax)*f(imin:imax,jmin:jmax,kmin:kmax))
f_out = f_out
Nout = (imax-imin+1)*(jmax-jmin+1)*(kmax-kmin+1)
return
@@ -1869,12 +1574,9 @@ Nout = (imax-imin+1)*(jmax-jmin+1)*(kmax-kmin+1)
! ^
! f=3/8*f_1 + 3/4*f_2 - 1/8*f_3
real*8,parameter::C1=3.d0/8.d0,C2=3.d0/4.d0,C3=-1.d0/8.d0
integer :: i,j,k
do concurrent (k=1:ext(3), j=1:ext(2), i=1:ext(1))
fout(i,j,k) = C1*f1(i,j,k)+C2*f2(i,j,k)+C3*f3(i,j,k)
end do
real*8,parameter::C1=3.d0/8.d0,C2=3.d0/4.d0,C3=-1.d0/8.d0
fout = C1*f1+C2*f2+C3*f3
return
@@ -1968,8 +1670,7 @@ Nout = (imax-imin+1)*(jmax-jmin+1)*(kmax-kmin+1)
real*8, dimension(ORDN,ORDN,ORDN) :: ya
real*8, dimension(ORDN,ORDN) :: tmp2
real*8, dimension(ORDN) :: tmp1
real*8, dimension(3) :: SoAh
real*8, external :: DDOT
real*8, dimension(3) :: SoAh
! +1 because c++ gives 0 for first point
cxB = inds+1
@@ -2015,7 +1716,10 @@ Nout = (imax-imin+1)*(jmax-jmin+1)*(kmax-kmin+1)
tmp1 = tmp1 + coef(ORDN+m)*tmp2(:,m)
enddo
f_int = DDOT(ORDN, coef(1:ORDN), 1, tmp1, 1)
f_int=0
do m=1,ORDN
f_int = f_int + coef(m)*tmp1(m)
enddo
return
@@ -2044,8 +1748,7 @@ Nout = (imax-imin+1)*(jmax-jmin+1)*(kmax-kmin+1)
integer,dimension(2) :: cxB,cxT
real*8, dimension(ORDN,ORDN) :: ya
real*8, dimension(ORDN) :: tmp1
real*8, dimension(2) :: SoAh
real*8, external :: DDOT
real*8, dimension(2) :: SoAh
! +1 because c++ gives 0 for first point
cxB = inds(1:2)+1
@@ -2080,7 +1783,10 @@ Nout = (imax-imin+1)*(jmax-jmin+1)*(kmax-kmin+1)
tmp1 = tmp1 + coef(ORDN+m)*ya(:,m)
enddo
f_int = DDOT(ORDN, coef(1:ORDN), 1, tmp1, 1)
f_int=0
do m=1,ORDN
f_int = f_int + coef(m)*tmp1(m)
enddo
return
@@ -2106,12 +1812,11 @@ Nout = (imax-imin+1)*(jmax-jmin+1)*(kmax-kmin+1)
!~~~~~~> Other parameters:
real*8, dimension(-ORDN+1:ex(1)+ORDN,-ORDN+1:ex(2)+ORDN,ex(3)) :: fh
integer :: m
integer :: cxB,cxT
real*8, dimension(ORDN) :: ya
real*8 :: SoAh
integer,dimension(3) :: inds
real*8, external :: DDOT
integer :: m
integer :: cxB,cxT
real*8, dimension(ORDN) :: ya
real*8 :: SoAh
integer,dimension(3) :: inds
! +1 because c++ gives 0 for first point
inds = indsi + 1
@@ -2172,7 +1877,10 @@ Nout = (imax-imin+1)*(jmax-jmin+1)*(kmax-kmin+1)
write(*,*)"error in global_interpind1d, not recognized dumyd = ",dumyd
endif
f_int = DDOT(ORDN, coef, 1, ya, 1)
f_int=0
do m=1,ORDN
f_int = f_int + coef(m)*ya(m)
enddo
return
@@ -2408,28 +2116,20 @@ Nout = (imax-imin+1)*(jmax-jmin+1)*(kmax-kmin+1)
implicit none
integer,intent(in) :: N
real*8 :: gont
integer :: i
real*8, parameter, dimension(0:20) :: fact_table = [ &
1.d0, 1.d0, 2.d0, 6.d0, 24.d0, 120.d0, 720.d0, 5040.d0, 40320.d0, &
362880.d0, 3628800.d0, 39916800.d0, 479001600.d0, 6227020800.d0, &
87178291200.d0, 1307674368000.d0, 20922789888000.d0, &
355687428096000.d0, 6402373705728000.d0, 121645100408832000.d0, &
2432902008176640000.d0 ]
real*8 :: gont
integer :: i
! sanity check
if(N < 0)then
write(*,*) "ffact: error input for factorial"
gont = 1.d0
return
endif
if(N <= 20)then
gont = fact_table(N)
else
gont = exp(log_gamma(dble(N+1)))
endif
if(N < 0)then
write(*,*) "ffact: error input for factorial"
return
endif
gont = 1.d0
do i=1,N
gont = gont*i
enddo
return
@@ -2563,3 +2263,4 @@ subroutine find_maximum(ext,X,Y,Z,fun,val,pos,llb,uub)
return
end subroutine

View File

@@ -12,10 +12,9 @@
#define f_global_interpind global_interpind
#define f_global_interpind2d global_interpind2d
#define f_global_interpind1d global_interpind1d
#define f_l2normhelper l2normhelper
#define f_l2normhelper7 l2normhelper7
#define f_l2normhelper_sh l2normhelper_sh
#define f_l2normhelper_sh_rms l2normhelper_sh_rms
#define f_l2normhelper l2normhelper
#define f_l2normhelper_sh l2normhelper_sh
#define f_l2normhelper_sh_rms l2normhelper_sh_rms
#define f_average average
#define f_average3 average3
#define f_average2 average2
@@ -42,10 +41,9 @@
#define f_global_interpind GLOBAL_INTERPIND
#define f_global_interpind2d GLOBAL_INTERPIND2D
#define f_global_interpind1d GLOBAL_INTERPIND1D
#define f_l2normhelper L2NORMHELPER
#define f_l2normhelper7 L2NORMHELPER7
#define f_l2normhelper_sh L2NORMHELPER_SH
#define f_l2normhelper_sh_rms L2NORMHELPER_SH_RMS
#define f_l2normhelper L2NORMHELPER
#define f_l2normhelper_sh L2NORMHELPER_SH
#define f_l2normhelper_sh_rms L2NORMHELPER_SH_RMS
#define f_average AVERAGE
#define f_average3 AVERAGE3
#define f_average2 AVERAGE2
@@ -72,10 +70,9 @@
#define f_global_interpind global_interpind_
#define f_global_interpind2d global_interpind2d_
#define f_global_interpind1d global_interpind1d_
#define f_l2normhelper l2normhelper_
#define f_l2normhelper7 l2normhelper7_
#define f_l2normhelper_sh l2normhelper_sh_
#define f_l2normhelper_sh_rms l2normhelper_sh_rms_
#define f_l2normhelper l2normhelper_
#define f_l2normhelper_sh l2normhelper_sh_
#define f_l2normhelper_sh_rms l2normhelper_sh_rms_
#define f_average average_
#define f_average3 average3_
#define f_average2 average2_
@@ -159,30 +156,21 @@ extern "C"
int *, double *, int &, int &);
}
extern "C"
{
void f_l2normhelper(int *, double *, double *, double *,
double &, double &, double &,
double &, double &, double &,
double *, double &, int &);
}
extern "C"
{
void f_l2normhelper7(int *, double *, double *, double *,
double &, double &, double &,
double &, double &, double &,
double *, double *, double *, double *,
double *, double *, double *, double *, int &);
}
extern "C"
{
void f_l2normhelper_sh(int *, double *, double *, double *,
double &, double &, double &,
double &, double &, double &,
double *, double &, int &, int &, int &);
}
extern "C"
{
void f_l2normhelper(int *, double *, double *, double *,
double &, double &, double &,
double &, double &, double &,
double *, double &, int &);
}
extern "C"
{
void f_l2normhelper_sh(int *, double *, double *, double *,
double &, double &, double &,
double &, double &, double &,
double *, double &, int &, int &, int &);
}
extern "C"
{

View File

@@ -2,7 +2,7 @@
#ifndef MICRODEF_H
#define MICRODEF_H
#include "macrodef.fh"
#include "microdef.fh"
// application parameters

View File

@@ -1,25 +1,11 @@
include makefile.inc
## polint(ordn=6) kernel selector:
## 1 (default): barycentric fast path
## 0 : fallback to Neville path
POLINT6_USE_BARY ?= 1
POLINT6_FLAG = -DPOLINT6_USE_BARYCENTRIC=$(POLINT6_USE_BARY)
ARCH_OPT = -march=x86-64-v4
CXXAPPFLAGS = -O3 $(ARCH_OPT) -fp-model fast=2 -fma -ipo \
-Dfortran3 -Dnewc -I${MKLROOT}/include
f90appflags = -O3 $(ARCH_OPT) -fp-model fast=2 -fma -ipo \
-align array64byte -fpp -I${MKLROOT}/include $(POLINT6_FLAG)
TP_OPTFLAGS = -O3 $(ARCH_OPT) -fp-model fast=2 -fma -ipo \
-Dfortran3 -Dnewc -I${MKLROOT}/include
.SUFFIXES: .o .f90 .C .for .cu
.f90.o:
$(f90) $(f90appflags) -c $< -o $@
include makefile.inc
.SUFFIXES: .o .f90 .C .for .cu
.f90.o:
$(f90) $(f90appflags) -c $< -o $@
.C.o:
${CXX} $(CXXAPPFLAGS) -c $< $(filein) -o $@
@@ -27,14 +13,8 @@ TP_OPTFLAGS = -O3 $(ARCH_OPT) -fp-model fast=2 -fma -ipo \
.for.o:
$(f77) -c $< -o $@
.cu.o:
$(Cu) $(CUDA_APP_FLAGS) -c $< -o $@ $(CUDA_LIB_PATH)
TwoPunctures.o: TwoPunctures.C
${CXX} $(TP_OPTFLAGS) -qopenmp -c $< -o $@
TwoPunctureABE.o: TwoPunctureABE.C
${CXX} $(TP_OPTFLAGS) -qopenmp -c $< -o $@
.cu.o:
$(Cu) $(CUDA_APP_FLAGS) -c $< -o $@ $(CUDA_LIB_PATH)
# Input files
C++FILES = ABE.o Ansorg.o Block.o misc.o monitor.o Parallel.o MPatch.o var.o\
@@ -115,8 +95,8 @@ ABE: $(C++FILES) $(F90FILES) $(F77FILES) $(AHFDOBJS)
ABEGPU: $(C++FILES_GPU) $(F90FILES) $(F77FILES) $(AHFDOBJS) $(CUDAFILES)
$(CLINKER) $(CXXAPPFLAGS) -o $@ $(C++FILES_GPU) $(F90FILES) $(F77FILES) $(AHFDOBJS) $(CUDAFILES) $(LDLIBS)
TwoPunctureABE: $(TwoPunctureFILES)
$(CLINKER) $(TP_OPTFLAGS) -qopenmp -o $@ $(TwoPunctureFILES) $(LDLIBS)
TwoPunctureABE: $(TwoPunctureFILES)
$(CLINKER) $(CXXAPPFLAGS) -o $@ $(TwoPunctureFILES) $(LDLIBS)
clean:
rm *.o ABE ABEGPU TwoPunctureABE make.log -f

View File

@@ -1,34 +1,33 @@
## GCC version (commented out)
## filein = -I/usr/include -I/usr/lib/x86_64-linux-gnu/mpich/include -I/usr/lib/x86_64-linux-gnu/openmpi/lib/ -I/usr/lib/gcc/x86_64-linux-gnu/11/ -I/usr/include/c++/11/
## filein = -I/usr/include/ -I/usr/include/openmpi-x86_64/ -I/usr/lib/x86_64-linux-gnu/openmpi/include/ -I/usr/lib/x86_64-linux-gnu/openmpi/lib/ -I/usr/lib/gcc/x86_64-linux-gnu/11/ -I/usr/include/c++/11/
## LDLIBS = -L/usr/lib/x86_64-linux-gnu -L/usr/lib64 -L/usr/lib/gcc/x86_64-linux-gnu/11 -lgfortran -lmpi -lgfortran
## Intel oneAPI version with oneMKL
## Intel oneAPI version with oneMKL (Optimized for performance)
filein = -I/usr/include/ -I${MKLROOT}/include
## Use sequential oneMKL to avoid introducing extra OpenMP behavior into ABE.
LDLIBS = -L${MKLROOT}/lib -lmkl_intel_lp64 -lmkl_sequential -lmkl_core -lifcore -limf -lpthread -lm -ldl -liomp5
## Optional Intel oneTBB allocator, kept aligned with main's build environment.
USE_TBBMALLOC ?= 1
TBBMALLOC_SO ?= /home/intel/oneapi/2025.3/lib/libtbbmalloc.so
ifneq ($(wildcard $(TBBMALLOC_SO)),)
TBBMALLOC_LIBS = -Wl,--no-as-needed $(TBBMALLOC_SO) -Wl,--as-needed
else
TBBMALLOC_LIBS = -Wl,--no-as-needed -ltbbmalloc -Wl,--as-needed
endif
ifeq ($(USE_TBBMALLOC),1)
LDLIBS := $(TBBMALLOC_LIBS) $(LDLIBS)
endif
## Using sequential MKL (OpenMP disabled for better single-threaded performance)
## Added -lifcore for Intel Fortran runtime and -limf for Intel math library
LDLIBS = -L${MKLROOT}/lib -lmkl_intel_lp64 -lmkl_sequential -lmkl_core -lifcore -limf -lpthread -lm -ldl
## Aggressive optimization flags:
## -O3: Maximum optimization
## -xHost: Optimize for the host CPU architecture (Intel/AMD compatible)
## -fp-model fast=2: Aggressive floating-point optimizations
## -fma: Enable fused multiply-add instructions
## Note: OpenMP has been disabled (-qopenmp removed) due to performance issues
CXXAPPFLAGS = -O3 -xHost -fp-model fast=2 -fma \
-Dfortran3 -Dnewc -I${MKLROOT}/include
f90appflags = -O3 -xHost -fp-model fast=2 -fma \
-fpp -I${MKLROOT}/include
f90 = ifx
f77 = ifx
CXX = icpx
CC = icx
CLINKER = mpiicpx
CLINKER = mpiicpx
Cu = nvcc
CUDA_LIB_PATH = -L/usr/lib/cuda/lib64 -I/usr/include -I/usr/lib/cuda/include
#CUDA_APP_FLAGS = -c -g -O3 --ptxas-options=-v -arch compute_13 -code compute_13,sm_13 -Dfortran3 -Dnewc
CUDA_APP_FLAGS = -c -g -O3 --ptxas-options=-v -Dfortran3 -Dnewc

View File

@@ -28,7 +28,7 @@ def makefile_ABE():
## Build command
if (input_data.GPU_Calculation == "no"):
makefile_command = "make -j96" + " ABE"
makefile_command = "make -j4" + " ABE"
elif (input_data.GPU_Calculation == "yes"):
makefile_command = "make -j4" + " ABEGPU"
else:

View File

@@ -1,12 +0,0 @@
import multiprocessing
def run_plot_task(task):
func, args = task
return func(*args)
def run_plot_tasks_parallel(plot_tasks):
ctx = multiprocessing.get_context('fork')
with ctx.Pool() as pool:
pool.map(run_plot_task, plot_tasks)

View File

@@ -8,13 +8,11 @@
##
#################################################
import numpy ## numpy for array operations
import scipy ## scipy for interpolation and signal processing
import math
import matplotlib
matplotlib.use('Agg') ## use non-interactive backend for multiprocessing safety
import matplotlib.pyplot as plt ## matplotlib for plotting
import os ## os for system/file operations
import numpy ## numpy for array operations
import scipy ## scipy for interpolation and signal processing
import math
import matplotlib.pyplot as plt ## matplotlib for plotting
import os ## os for system/file operations
import AMSS_NCKU_Input as input_data

View File

@@ -6,22 +6,17 @@
## Author: Xiaoqu
## Dates: 2024/10/01 --- 2025/09/14
##
#################################################
## Restrict OpenMP to one thread per process so that parallel
## subprocess plotting does not multiply BLAS thread counts.
import os
os.environ.setdefault("OMP_NUM_THREADS", "1")
import numpy
import scipy
import matplotlib
matplotlib.use('Agg') ## use non-interactive backend for multiprocessing safety
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm
from mpl_toolkits.mplot3d import Axes3D
## import torch
import AMSS_NCKU_Input as input_data
#################################################
import numpy
import scipy
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm
from mpl_toolkits.mplot3d import Axes3D
## import torch
import AMSS_NCKU_Input as input_data
import os
#########################################################################################
@@ -97,9 +92,9 @@ def plot_binary_data( filename, binary_outdir, figure_outdir ):
####################################################################################
# Plot a single binary dataset (2D slices and 3D surface)
####################################################################################
# Plot a single binary dataset (2D slices and 3D surface)
def get_data_xy( Rmin, Rmax, n, data0, time, figure_title, figure_outdir ):
@@ -193,15 +188,7 @@ def get_data_xy( Rmin, Rmax, n, data0, time, figure_title, figure_outdir ):
plt.savefig( os.path.join(figure_surfaceplot_outdir, figure_title + " time = " + str(time) + " surface_plot.pdf") ) # save figure
plt.close()
return
####################################################################################
## Allow standalone subprocess execution for parallel binary-data plotting.
if __name__ == '__main__':
import sys
if len(sys.argv) != 4:
print(f"Usage: {sys.argv[0]} <filename> <binary_outdir> <figure_outdir>")
sys.exit(1)
plot_binary_data(sys.argv[1], sys.argv[2], sys.argv[3])
return
####################################################################################

View File

@@ -6,20 +6,15 @@
## 2024/10/01 --- 2025/09/14
##
#################################################
import numpy ## numpy for array operations
import matplotlib
matplotlib.use('Agg') ## use non-interactive backend for multiprocessing safety
import matplotlib.pyplot as plt ## matplotlib for plotting
from mpl_toolkits.mplot3d import Axes3D ## needed for 3D plots
import glob
import os ## operating system utilities
import plot_binary_data
import AMSS_NCKU_Input as input_data
import subprocess
import sys
import multiprocessing
import numpy ## numpy for array operations
import matplotlib.pyplot as plt ## matplotlib for plotting
from mpl_toolkits.mplot3d import Axes3D ## needed for 3D plots
import glob
import os ## operating system utilities
import plot_binary_data
import AMSS_NCKU_Input as input_data
# plt.rcParams['text.usetex'] = True ## enable LaTeX fonts in plots
@@ -55,37 +50,13 @@ def generate_binary_data_plot( binary_outdir, figure_outdir ):
file_list.append(x)
print(x)
## Plot each file in parallel using subprocesses.
## Each subprocess starts with BLAS thread limits in plot_binary_data.py.
script = os.path.join( os.path.dirname(__file__), "plot_binary_data.py" )
max_workers = min( multiprocessing.cpu_count(), len(file_list) ) if file_list else 0
running = []
failed = []
for filename in file_list:
print(filename)
proc = subprocess.Popen(
[sys.executable, script, filename, binary_outdir, figure_outdir],
)
running.append( (proc, filename) )
if len(running) >= max_workers:
p, fn = running.pop(0)
p.wait()
if p.returncode != 0:
failed.append(fn)
for p, fn in running:
p.wait()
if p.returncode != 0:
failed.append(fn)
if failed:
print( " WARNING: the following binary data plots failed:" )
for fn in failed:
print( " ", fn )
print( )
print( " Binary Data Plot Has been Finished " )
## Plot each file in the list
for filename in file_list:
print(filename)
plot_binary_data.plot_binary_data(filename, binary_outdir, figure_outdir)
print( )
print( " Binary Data Plot Has been Finished " )
print( )
return