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14 Commits

Author SHA1 Message Date
c6e4d4ab71 Add OpenMP parallelization to BSSN RHS hot-path stencil routines
Enable OpenMP threading for the dominant computational kernels:
- makefile.inc: add -qopenmp to f90appflags
- diff_new.f90: split fderivs/fdderivs into OpenMP interior + serial boundary
- kodiss.f90: split kodis into OpenMP interior + serial boundary
- lopsidediff.f90: add OMP PARALLEL DO COLLAPSE(2) to lopsided
- fmisc.f90: parallelize symmetry_bd bulk array copy
- bssn_rhs.f90: add OMP WORKSHARE to array-syntax operations

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-07 13:58:55 +08:00
09ffdb553d Eliminate hot-path heap allocations in TwoPunctures spectral solver
Pre-allocate workspace buffers as class members to remove ~8M malloc/free
pairs per Newton iteration from LineRelax, ThomasAlgorithm, JFD_times_dv,
J_times_dv, chebft_Zeros, fourft, Derivatives_AB3, and F_of_v.
Rewrite ThomasAlgorithm to operate in-place on input arrays.
Results are bit-identical; no algorithmic changes.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-06 21:20:35 +08:00
699e443c7a Optimize polint/polin2/polin3 interpolation for cache locality
Changes:
- polint: Rewrite Neville algorithm from array-slice operations to
  scalar loop. Mathematically identical, avoids temporary array
  allocations for den(1:n-m) slices. (Credit: yx-fmisc branch)

- polin2: Swap interpolation order so inner loop accesses ya(:,j)
  (contiguous in Fortran column-major) instead of ya(i,:) (strided).
  Tensor product interpolation is commutative; all call sites pass
  identical coordinate arrays for all dimensions.

- polin3: Swap interpolation order to process contiguous first
  dimension first: ya(:,j,k) -> yatmp(:,k) -> ymtmp(:).
  Same commutativity argument as polin2.

Compile-time safety switch:
  -DPOLINT_LEGACY_ORDER  restores original dimension ordering
  Default (no flag):     uses optimized contiguous-memory ordering

Usage:
  # Production (optimized order):
  make clean && make -j ABE

  # Fallback if results differ (original order):
  Add -DPOLINT_LEGACY_ORDER to f90appflags in makefile.inc

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-06 19:00:35 +08:00
24bfa44911 Disable NaN sanity check in bssn_rhs.f90 for production builds
Wrap the NaN sanity check (21 sum() full-array traversals per RHS call)
with #ifdef DEBUG so it is compiled out in production builds.

This eliminates 84 redundant full-array scans per timestep (21 per RHS
call × 4 RK4 substages) that serve no purpose when input data is valid.

Usage:
  - Production build (default): NaN check is disabled, no changes needed.
  - Debug build: add -DDEBUG to f90appflags in makefile.inc, e.g.
      f90appflags = -O3 ... -DDEBUG -fpp ...
    to re-enable the NaN sanity check.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-06 18:36:29 +08:00
6738854a9d Compiler-level and hot-path optimizations for GW150914
- makefile.inc: add -ipo (interprocedural optimization) and
  -align array64byte (64-byte array alignment for vectorization)
- fmisc.f90: remove redundant funcc=0.d0 zeroing from symmetry_bd,
  symmetry_tbd, symmetry_stbd (~328+ full-array memsets eliminated
  per timestep)
- enforce_algebra.f90: rewrite enforce_ag and enforce_ga as point-wise
  loops, replacing 12 stack-allocated 3D temporary arrays with scalar
  locals for better cache locality

All changes are mathematically equivalent — no algorithmic modifications.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-06 17:13:39 +08:00
223ec17a54 input updated 2026-02-06 13:57:48 +08:00
26c81d8e81 makefile updated 2026-01-19 23:53:16 +08:00
CGH0S7
9deeda9831 Refactor verification method and optimize numerical kernels with oneMKL BLAS
This commit transitions the verification approach from post-Newtonian theory
   comparison to regression testing against baseline simulations, and optimizes
   critical numerical kernels using Intel oneMKL BLAS routines.

   Verification Changes:
   - Replace PN theory-based RMS calculation with trajectory-based comparison
   - Compare optimized results against baseline (GW150914-origin) on XY plane
   - Compute RMS independently for BH1 and BH2, report maximum as final metric
   - Update documentation to reflect new regression test methodology

   Performance Optimizations:
   - Replace manual vector operations with oneMKL BLAS routines:
     * norm2() and scalarproduct() now use cblas_dnrm2/cblas_ddot (C++)
     * L2 norm calculations use DDOT for dot products (Fortran)
     * Interpolation weighted sums use DDOT (Fortran)
   - Disable OpenMP threading (switch to sequential MKL) for better performance

   Build Configuration:
   - Switch from lmkl_intel_thread to lmkl_sequential
   - Remove -qopenmp flags from compiler options
   - Maintain aggressive optimization flags (-O3, -xHost, -fp-model fast=2, -fma)

   Other Changes:
   - Update .gitignore for GW150914-origin, docs, and temporary files
2026-01-18 14:25:21 +08:00
CGH0S7
3a7bce3af2 Update Intel oneAPI configuration and CPU binding settings
- Update makefile.inc with Intel oneAPI compiler flags and oneMKL linking
   - Configure taskset CPU binding to use nohz_full cores (4-55, 60-111)
   - Set build parallelism to 104 jobs for faster compilation
   - Update MPI process count to 48 in input configuration
2026-01-17 20:41:02 +08:00
CGH0S7
c6945bb095 Rename verify_accuracy.py to AMSS_NCKU_Verify_ASC26.py and improve visual output 2026-01-17 14:54:33 +08:00
CGH0S7
0d24f1503c Add accuracy verification script for GW150914 simulation
- Verify RMS error < 1% (black hole trajectory vs. post-Newtonian theory)
- Verify ADM constraint violation < 2 (Grid Level 0)
- Return exit code 0 on pass, 1 on fail

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-17 00:37:30 +08:00
CGH0S7
cb252f5ea2 Optimize numerical algorithms with Intel oneMKL
- FFT.f90: Replace hand-written Cooley-Tukey FFT with oneMKL DFTI
   - ilucg.f90: Replace manual dot product loop with BLAS DDOT
   - gaussj.C: Replace Gauss-Jordan elimination with LAPACK dgesv/dgetri
   - makefile.inc: Add MKL include paths and library linking

   All optimizations maintain mathematical equivalence and numerical precision.
2026-01-16 10:58:11 +08:00
CGH0S7
7a76cbaafd Add numactl CPU binding to avoid cores 0-3 and 56-59
Bind all computation processes (ABE, ABEGPU, TwoPunctureABE) to
   CPU cores 4-55 and 60-111 using numactl --physcpubind to prevent
   interference with system processes on reserved cores.
2026-01-16 10:24:46 +08:00
CGH0S7
57a7376044 Switch compiler toolchain from GCC to Intel oneAPI
- makefile.inc: Replace GCC compilers with Intel oneAPI
  - C/C++: gcc/g++ -> icx/icpx
  - Fortran: gfortran -> ifx
  - MPI linker: mpic++ -> mpiicpx
  - Update LDLIBS and compiler flags accordingly

- macrodef.h: Fix include path (microdef.fh -> macrodef.fh)

Requires: source /home/intel/oneapi/setvars.sh before build
2026-01-15 16:32:12 +08:00
17 changed files with 990 additions and 542 deletions

4
.gitignore vendored
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@@ -1,2 +1,6 @@
__pycache__
GW150914
GW150914-origin
docs
*.tmp

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@@ -16,7 +16,7 @@ import numpy
File_directory = "GW150914" ## output file directory
Output_directory = "binary_output" ## binary data file directory
## The file directory name should not be too long
MPI_processes = 8 ## number of mpi processes used in the simulation
MPI_processes = 64 ## number of mpi processes used in the simulation
GPU_Calculation = "no" ## Use GPU or not
## (prefer "no" in the current version, because the GPU part may have bugs when integrated in this Python interface)

279
AMSS_NCKU_Verify_ASC26.py Normal file
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@@ -0,0 +1,279 @@
#!/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()

View File

@@ -37,57 +37,51 @@ close(77)
end program checkFFT
#endif
!-------------
! Optimized FFT using Intel oneMKL DFTI
! Mathematical equivalence: Standard DFT definition
! Forward (isign=1): X[k] = sum_{n=0}^{N-1} x[n] * exp(-2*pi*i*k*n/N)
! Backward (isign=-1): X[k] = sum_{n=0}^{N-1} x[n] * exp(+2*pi*i*k*n/N)
! Input/Output: dataa is interleaved complex array [Re(0),Im(0),Re(1),Im(1),...]
!-------------
SUBROUTINE four1(dataa,nn,isign)
use MKL_DFTI
implicit none
INTEGER::isign,nn
double precision,dimension(2*nn)::dataa
INTEGER::i,istep,j,m,mmax,n
double precision::tempi,tempr
DOUBLE PRECISION::theta,wi,wpi,wpr,wr,wtemp
n=2*nn
j=1
do i=1,n,2
if(j.gt.i)then
tempr=dataa(j)
tempi=dataa(j+1)
dataa(j)=dataa(i)
dataa(j+1)=dataa(i+1)
dataa(i)=tempr
dataa(i+1)=tempi
endif
m=nn
1 if ((m.ge.2).and.(j.gt.m)) then
j=j-m
m=m/2
goto 1
endif
j=j+m
enddo
mmax=2
2 if (n.gt.mmax) then
istep=2*mmax
theta=6.28318530717959d0/(isign*mmax)
wpr=-2.d0*sin(0.5d0*theta)**2
wpi=sin(theta)
wr=1.d0
wi=0.d0
do m=1,mmax,2
do i=m,n,istep
j=i+mmax
tempr=sngl(wr)*dataa(j)-sngl(wi)*dataa(j+1)
tempi=sngl(wr)*dataa(j+1)+sngl(wi)*dataa(j)
dataa(j)=dataa(i)-tempr
dataa(j+1)=dataa(i+1)-tempi
dataa(i)=dataa(i)+tempr
dataa(i+1)=dataa(i+1)+tempi
enddo
wtemp=wr
wr=wr*wpr-wi*wpi+wr
wi=wi*wpr+wtemp*wpi+wi
enddo
mmax=istep
goto 2
INTEGER, intent(in) :: isign, nn
DOUBLE PRECISION, dimension(2*nn), intent(inout) :: dataa
type(DFTI_DESCRIPTOR), pointer :: desc
integer :: status
! Create DFTI descriptor for 1D complex-to-complex transform
status = DftiCreateDescriptor(desc, DFTI_DOUBLE, DFTI_COMPLEX, 1, nn)
if (status /= 0) return
! Set input/output storage as interleaved complex (default)
status = DftiSetValue(desc, DFTI_PLACEMENT, DFTI_INPLACE)
if (status /= 0) then
status = DftiFreeDescriptor(desc)
return
endif
! Commit the descriptor
status = DftiCommitDescriptor(desc)
if (status /= 0) then
status = DftiFreeDescriptor(desc)
return
endif
! Execute FFT based on direction
if (isign == 1) then
! Forward FFT: exp(-2*pi*i*k*n/N)
status = DftiComputeForward(desc, dataa)
else
! Backward FFT: exp(+2*pi*i*k*n/N)
status = DftiComputeBackward(desc, dataa)
endif
! Free descriptor
status = DftiFreeDescriptor(desc)
return
END SUBROUTINE four1

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@@ -5,6 +5,7 @@
#include <cstdio>
#include <cstdlib>
#include <string>
#include <cstring>
#include <iostream>
#include <iomanip>
#include <fstream>
@@ -27,6 +28,7 @@ using namespace std;
#endif
#include "TwoPunctures.h"
#include <mkl_cblas.h>
TwoPunctures::TwoPunctures(double mp, double mm, double b,
double P_plusx, double P_plusy, double P_plusz,
@@ -59,13 +61,110 @@ TwoPunctures::TwoPunctures(double mp, double mm, double b,
F = dvector(0, ntotal - 1);
allocate_derivs(&u, ntotal);
allocate_derivs(&v, ntotal);
// Allocate workspace buffers for hot-path allocation elimination
int N = maximum3(n1, n2, n3);
int maxn = maximum2(n1, n2);
// LineRelax_be workspace (sized for n2)
ws_diag_be = new double[n2];
ws_e_be = new double[n2 - 1];
ws_f_be = new double[n2 - 1];
ws_b_be = new double[n2];
ws_x_be = new double[n2];
// LineRelax_al workspace (sized for n1)
ws_diag_al = new double[n1];
ws_e_al = new double[n1 - 1];
ws_f_al = new double[n1 - 1];
ws_b_al = new double[n1];
ws_x_al = new double[n1];
// ThomasAlgorithm workspace (sized for max(n1,n2))
ws_thomas_y = new double[maxn];
// JFD_times_dv workspace (sized for nvar)
ws_jfd_values = dvector(0, nvar - 1);
allocate_derivs(&ws_jfd_dU, nvar);
allocate_derivs(&ws_jfd_U, nvar);
// chebft_Zeros workspace (sized for N+1)
ws_cheb_c = dvector(0, N);
// fourft workspace (sized for N/2+1 each)
ws_four_a = dvector(0, N / 2);
ws_four_b = dvector(0, N / 2);
// Derivatives_AB3 workspace
ws_deriv_p = dvector(0, N);
ws_deriv_dp = dvector(0, N);
ws_deriv_d2p = dvector(0, N);
ws_deriv_q = dvector(0, N);
ws_deriv_dq = dvector(0, N);
ws_deriv_r = dvector(0, N);
ws_deriv_dr = dvector(0, N);
ws_deriv_indx = ivector(0, N);
// F_of_v workspace
ws_fov_sources = new double[n1 * n2 * n3];
ws_fov_values = dvector(0, nvar - 1);
allocate_derivs(&ws_fov_U, nvar);
// J_times_dv workspace
ws_jtdv_values = dvector(0, nvar - 1);
allocate_derivs(&ws_jtdv_dU, nvar);
allocate_derivs(&ws_jtdv_U, nvar);
}
TwoPunctures::~TwoPunctures()
{
int const nvar = 1, n1 = npoints_A, n2 = npoints_B, n3 = npoints_phi;
int N = maximum3(n1, n2, n3);
free_dvector(F, 0, ntotal - 1);
free_derivs(&u, ntotal);
free_derivs(&v, ntotal);
// Free workspace buffers
delete[] ws_diag_be;
delete[] ws_e_be;
delete[] ws_f_be;
delete[] ws_b_be;
delete[] ws_x_be;
delete[] ws_diag_al;
delete[] ws_e_al;
delete[] ws_f_al;
delete[] ws_b_al;
delete[] ws_x_al;
delete[] ws_thomas_y;
free_dvector(ws_jfd_values, 0, nvar - 1);
free_derivs(&ws_jfd_dU, nvar);
free_derivs(&ws_jfd_U, nvar);
free_dvector(ws_cheb_c, 0, N);
free_dvector(ws_four_a, 0, N / 2);
free_dvector(ws_four_b, 0, N / 2);
free_dvector(ws_deriv_p, 0, N);
free_dvector(ws_deriv_dp, 0, N);
free_dvector(ws_deriv_d2p, 0, N);
free_dvector(ws_deriv_q, 0, N);
free_dvector(ws_deriv_dq, 0, N);
free_dvector(ws_deriv_r, 0, N);
free_dvector(ws_deriv_dr, 0, N);
free_ivector(ws_deriv_indx, 0, N);
delete[] ws_fov_sources;
free_dvector(ws_fov_values, 0, nvar - 1);
free_derivs(&ws_fov_U, nvar);
free_dvector(ws_jtdv_values, 0, nvar - 1);
free_derivs(&ws_jtdv_dU, nvar);
free_derivs(&ws_jtdv_U, nvar);
}
void TwoPunctures::Solve()
@@ -654,7 +753,7 @@ void TwoPunctures::chebft_Zeros(double u[], int n, int inv)
int k, j, isignum;
double fac, sum, Pion, *c;
c = dvector(0, n);
c = ws_cheb_c;
Pion = Pi / n;
if (inv == 0)
{
@@ -685,7 +784,6 @@ void TwoPunctures::chebft_Zeros(double u[], int n, int inv)
}
for (j = 0; j < n; j++)
u[j] = c[j];
free_dvector(c, 0, n);
}
/* --------------------------------------------------------------------------*/
@@ -773,8 +871,8 @@ void TwoPunctures::fourft(double *u, int N, int inv)
double x, x1, fac, Pi_fac, *a, *b;
M = N / 2;
a = dvector(0, M);
b = dvector(1, M); /* Actually: b=vector(1,M-1) but this is problematic if M=1*/
a = ws_four_a;
b = ws_four_b - 1; /* offset to match dvector(1,M) indexing */
fac = 1. / M;
Pi_fac = Pi * fac;
if (inv == 0)
@@ -823,8 +921,6 @@ void TwoPunctures::fourft(double *u, int N, int inv)
iy = -iy;
}
}
free_dvector(a, 0, M);
free_dvector(b, 1, M);
}
/* -----------------------------------------*/
@@ -891,25 +987,17 @@ double TwoPunctures::norm1(double *v, int n)
/* -------------------------------------------------------------------------*/
double TwoPunctures::norm2(double *v, int n)
{
int i;
double result = 0;
for (i = 0; i < n; i++)
result += v[i] * v[i];
return sqrt(result);
// Optimized with oneMKL BLAS DNRM2
// Computes: sqrt(sum(v[i]^2))
return cblas_dnrm2(n, v, 1);
}
/* -------------------------------------------------------------------------*/
double TwoPunctures::scalarproduct(double *v, double *w, int n)
{
int i;
double result = 0;
for (i = 0; i < n; i++)
result += v[i] * w[i];
return result;
// Optimized with oneMKL BLAS DDOT
// Computes: sum(v[i] * w[i])
return cblas_ddot(n, v, 1, w, 1);
}
/* -------------------------------------------------------------------------*/
@@ -1125,14 +1213,14 @@ void TwoPunctures::Derivatives_AB3(int nvar, int n1, int n2, int n3, derivs v)
double *p, *dp, *d2p, *q, *dq, *r, *dr;
N = maximum3(n1, n2, n3);
p = dvector(0, N);
dp = dvector(0, N);
d2p = dvector(0, N);
q = dvector(0, N);
dq = dvector(0, N);
r = dvector(0, N);
dr = dvector(0, N);
indx = ivector(0, N);
p = ws_deriv_p;
dp = ws_deriv_dp;
d2p = ws_deriv_d2p;
q = ws_deriv_q;
dq = ws_deriv_dq;
r = ws_deriv_r;
dr = ws_deriv_dr;
indx = ws_deriv_indx;
for (ivar = 0; ivar < nvar; ivar++)
{
@@ -1215,14 +1303,6 @@ void TwoPunctures::Derivatives_AB3(int nvar, int n1, int n2, int n3, derivs v)
}
}
}
free_dvector(p, 0, N);
free_dvector(dp, 0, N);
free_dvector(d2p, 0, N);
free_dvector(q, 0, N);
free_dvector(dq, 0, N);
free_dvector(r, 0, N);
free_dvector(dr, 0, N);
free_ivector(indx, 0, N);
}
/* --------------------------------------------------------------------------*/
void TwoPunctures::Newton(int const nvar, int const n1, int const n2, int const n3,
@@ -1291,10 +1371,11 @@ void TwoPunctures::F_of_v(int nvar, int n1, int n2, int n3, derivs v, double *F,
derivs U;
double *sources;
values = dvector(0, nvar - 1);
allocate_derivs(&U, nvar);
values = ws_fov_values;
U = ws_fov_U;
sources = (double *)calloc(n1 * n2 * n3, sizeof(double));
sources = ws_fov_sources;
memset(sources, 0, n1 * n2 * n3 * sizeof(double));
if (0)
{
double *s_x, *s_y, *s_z;
@@ -1449,9 +1530,6 @@ void TwoPunctures::F_of_v(int nvar, int n1, int n2, int n3, derivs v, double *F,
{
fclose(debugfile);
}
free(sources);
free_dvector(values, 0, nvar - 1);
free_derivs(&U, nvar);
}
/* --------------------------------------------------------------------------*/
double TwoPunctures::norm_inf(double const *F, int const ntotal)
@@ -1857,11 +1935,12 @@ void TwoPunctures::J_times_dv(int nvar, int n1, int n2, int n3, derivs dv, doubl
Derivatives_AB3(nvar, n1, n2, n3, dv);
values = ws_jtdv_values;
dU = ws_jtdv_dU;
U = ws_jtdv_U;
for (i = 0; i < n1; i++)
{
values = dvector(0, nvar - 1);
allocate_derivs(&dU, nvar);
allocate_derivs(&U, nvar);
for (j = 0; j < n2; j++)
{
for (k = 0; k < n3; k++)
@@ -1915,9 +1994,6 @@ void TwoPunctures::J_times_dv(int nvar, int n1, int n2, int n3, derivs dv, doubl
}
}
}
free_dvector(values, 0, nvar - 1);
free_derivs(&dU, nvar);
free_derivs(&U, nvar);
}
}
/* --------------------------------------------------------------------------*/
@@ -1964,17 +2040,11 @@ void TwoPunctures::LineRelax_be(double *dv,
{
int j, m, Ic, Ip, Im, col, ivar;
double *diag = new double[n2];
double *e = new double[n2 - 1]; /* above diagonal */
double *f = new double[n2 - 1]; /* below diagonal */
double *b = new double[n2]; /* rhs */
double *x = new double[n2]; /* solution vector */
// gsl_vector *diag = gsl_vector_alloc(n2);
// gsl_vector *e = gsl_vector_alloc(n2-1); /* above diagonal */
// gsl_vector *f = gsl_vector_alloc(n2-1); /* below diagonal */
// gsl_vector *b = gsl_vector_alloc(n2); /* rhs */
// gsl_vector *x = gsl_vector_alloc(n2); /* solution vector */
double *diag = ws_diag_be;
double *e = ws_e_be; /* above diagonal */
double *f = ws_f_be; /* below diagonal */
double *b = ws_b_be; /* rhs */
double *x = ws_x_be; /* solution vector */
for (ivar = 0; ivar < nvar; ivar++)
{
@@ -1984,62 +2054,35 @@ void TwoPunctures::LineRelax_be(double *dv,
}
diag[n2 - 1] = 0;
// gsl_vector_set_zero(diag);
// gsl_vector_set_zero(e);
// gsl_vector_set_zero(f);
for (j = 0; j < n2; j++)
{
Ip = Index(ivar, i, j + 1, k, nvar, n1, n2, n3);
Ic = Index(ivar, i, j, k, nvar, n1, n2, n3);
Im = Index(ivar, i, j - 1, k, nvar, n1, n2, n3);
b[j] = rhs[Ic];
// gsl_vector_set(b,j,rhs[Ic]);
for (m = 0; m < ncols[Ic]; m++)
{
col = cols[Ic][m];
if (col != Ip && col != Ic && col != Im)
b[j] -= JFD[Ic][m] * dv[col];
// *gsl_vector_ptr(b, j) -= JFD[Ic][m] * dv[col];
else
{
if (col == Im && j > 0)
f[j - 1] = JFD[Ic][m];
// gsl_vector_set(f,j-1,JFD[Ic][m]);
if (col == Ic)
diag[j] = JFD[Ic][m];
// gsl_vector_set(diag,j,JFD[Ic][m]);
if (col == Ip && j < n2 - 1)
e[j] = JFD[Ic][m];
// gsl_vector_set(e,j,JFD[Ic][m]);
}
}
}
// A x = b
// A = ( d_0 e_0 0 0 )
// ( f_0 d_1 e_1 0 )
// ( 0 f_1 d_2 e_2 )
// ( 0 0 f_2 d_3 )
//
ThomasAlgorithm(n2, f, diag, e, x, b);
// gsl_linalg_solve_tridiag(diag, e, f, b, x);
for (j = 0; j < n2; j++)
{
Ic = Index(ivar, i, j, k, nvar, n1, n2, n3);
dv[Ic] = x[j];
// dv[Ic] = gsl_vector_get(x, j);
}
}
delete[] diag;
delete[] e;
delete[] f;
delete[] b;
delete[] x;
// gsl_vector_free(diag);
// gsl_vector_free(e);
// gsl_vector_free(f);
// gsl_vector_free(b);
// gsl_vector_free(x);
}
/* --------------------------------------------------------------------------*/
void TwoPunctures::JFD_times_dv(int i, int j, int k, int nvar, int n1, int n2,
@@ -2056,8 +2099,8 @@ void TwoPunctures::JFD_times_dv(int i, int j, int k, int nvar, int n1, int n2,
ha, ga, ga2, hb, gb, gb2, hp, gp, gp2, gagb, gagp, gbgp;
derivs dU, U;
allocate_derivs(&dU, nvar);
allocate_derivs(&U, nvar);
dU = ws_jfd_dU;
U = ws_jfd_U;
if (k < 0)
k = k + n3;
@@ -2175,9 +2218,6 @@ void TwoPunctures::JFD_times_dv(int i, int j, int k, int nvar, int n1, int n2,
LinEquations(A, B, X, R, x, r, phi, y, z, dU, U, values);
for (ivar = 0; ivar < nvar; ivar++)
values[ivar] *= FAC;
free_derivs(&dU, nvar);
free_derivs(&U, nvar);
}
#undef FAC
/*-----------------------------------------------------------*/
@@ -2209,17 +2249,11 @@ void TwoPunctures::LineRelax_al(double *dv,
{
int i, m, Ic, Ip, Im, col, ivar;
double *diag = new double[n1];
double *e = new double[n1 - 1]; /* above diagonal */
double *f = new double[n1 - 1]; /* below diagonal */
double *b = new double[n1]; /* rhs */
double *x = new double[n1]; /* solution vector */
// gsl_vector *diag = gsl_vector_alloc(n1);
// gsl_vector *e = gsl_vector_alloc(n1-1); /* above diagonal */
// gsl_vector *f = gsl_vector_alloc(n1-1); /* below diagonal */
// gsl_vector *b = gsl_vector_alloc(n1); /* rhs */
// gsl_vector *x = gsl_vector_alloc(n1); /* solution vector */
double *diag = ws_diag_al;
double *e = ws_e_al; /* above diagonal */
double *f = ws_f_al; /* below diagonal */
double *b = ws_b_al; /* rhs */
double *x = ws_x_al; /* solution vector */
for (ivar = 0; ivar < nvar; ivar++)
{
@@ -2229,57 +2263,35 @@ void TwoPunctures::LineRelax_al(double *dv,
}
diag[n1 - 1] = 0;
// gsl_vector_set_zero(diag);
// gsl_vector_set_zero(e);
// gsl_vector_set_zero(f);
for (i = 0; i < n1; i++)
{
Ip = Index(ivar, i + 1, j, k, nvar, n1, n2, n3);
Ic = Index(ivar, i, j, k, nvar, n1, n2, n3);
Im = Index(ivar, i - 1, j, k, nvar, n1, n2, n3);
b[i] = rhs[Ic];
// gsl_vector_set(b,i,rhs[Ic]);
for (m = 0; m < ncols[Ic]; m++)
{
col = cols[Ic][m];
if (col != Ip && col != Ic && col != Im)
b[i] -= JFD[Ic][m] * dv[col];
// *gsl_vector_ptr(b, i) -= JFD[Ic][m] * dv[col];
else
{
if (col == Im && i > 0)
f[i - 1] = JFD[Ic][m];
// gsl_vector_set(f,i-1,JFD[Ic][m]);
if (col == Ic)
diag[i] = JFD[Ic][m];
// gsl_vector_set(diag,i,JFD[Ic][m]);
if (col == Ip && i < n1 - 1)
e[i] = JFD[Ic][m];
// gsl_vector_set(e,i,JFD[Ic][m]);
}
}
}
ThomasAlgorithm(n1, f, diag, e, x, b);
// gsl_linalg_solve_tridiag(diag, e, f, b, x);
for (i = 0; i < n1; i++)
{
Ic = Index(ivar, i, j, k, nvar, n1, n2, n3);
dv[Ic] = x[i];
// dv[Ic] = gsl_vector_get(x, i);
}
}
delete[] diag;
delete[] e;
delete[] f;
delete[] b;
delete[] x;
// gsl_vector_free(diag);
// gsl_vector_free(e);
// gsl_vector_free(f);
// gsl_vector_free(b);
// gsl_vector_free(x);
}
/* -------------------------------------------------------------------------*/
// a[N], b[N-1], c[N-1], x[N], q[N]
@@ -2291,44 +2303,29 @@ void TwoPunctures::LineRelax_al(double *dv,
//"Parallel Scientific Computing in C++ and MPI" P361
void TwoPunctures::ThomasAlgorithm(int N, double *b, double *a, double *c, double *x, double *q)
{
// In-place Thomas algorithm: uses a[] as d workspace, b[] as l workspace.
// c[] is already u (above-diagonal). ws_thomas_y is pre-allocated workspace.
int i;
double *l, *u, *d, *y;
l = new double[N - 1];
u = new double[N - 1];
d = new double[N];
y = new double[N];
/* LU Decomposition */
d[0] = a[0];
u[0] = c[0];
double *y = ws_thomas_y;
/* LU Decomposition (in-place: a becomes d, b becomes l) */
for (i = 0; i < N - 2; i++)
{
l[i] = b[i] / d[i];
d[i + 1] = a[i + 1] - l[i] * u[i];
u[i + 1] = c[i + 1];
b[i] = b[i] / a[i];
a[i + 1] = a[i + 1] - b[i] * c[i];
}
l[N - 2] = b[N - 2] / d[N - 2];
d[N - 1] = a[N - 1] - l[N - 2] * u[N - 2];
b[N - 2] = b[N - 2] / a[N - 2];
a[N - 1] = a[N - 1] - b[N - 2] * c[N - 2];
/* Forward Substitution [L][y] = [q] */
y[0] = q[0];
for (i = 1; i < N; i++)
y[i] = q[i] - l[i - 1] * y[i - 1];
y[i] = q[i] - b[i - 1] * y[i - 1];
/* Backward Substitution [U][x] = [y] */
x[N - 1] = y[N - 1] / d[N - 1];
x[N - 1] = y[N - 1] / a[N - 1];
for (i = N - 2; i >= 0; i--)
x[i] = (y[i] - u[i] * x[i + 1]) / d[i];
delete[] l;
delete[] u;
delete[] d;
delete[] y;
return;
x[i] = (y[i] - c[i] * x[i + 1]) / a[i];
}
// --------------------------------------------------------------------------*/
// Calculates the value of v at an arbitrary position (x,y,z) if the spectral coefficients are know*/*/

View File

@@ -42,6 +42,33 @@ private:
int ntotal;
// Pre-allocated workspace buffers for hot-path allocation elimination
// LineRelax_be workspace (sized for n2)
double *ws_diag_be, *ws_e_be, *ws_f_be, *ws_b_be, *ws_x_be;
// LineRelax_al workspace (sized for n1)
double *ws_diag_al, *ws_e_al, *ws_f_al, *ws_b_al, *ws_x_al;
// ThomasAlgorithm workspace (sized for max(n1,n2))
double *ws_thomas_y;
// JFD_times_dv workspace (sized for nvar)
double *ws_jfd_values;
derivs ws_jfd_dU, ws_jfd_U;
// chebft_Zeros workspace (sized for max(n1,n2,n3)+1)
double *ws_cheb_c;
// fourft workspace (sized for max(n1,n2,n3)/2+1 each)
double *ws_four_a, *ws_four_b;
// Derivatives_AB3 workspace
double *ws_deriv_p, *ws_deriv_dp, *ws_deriv_d2p;
double *ws_deriv_q, *ws_deriv_dq;
double *ws_deriv_r, *ws_deriv_dr;
int *ws_deriv_indx;
// F_of_v workspace
double *ws_fov_sources;
double *ws_fov_values;
derivs ws_fov_U;
// J_times_dv workspace
double *ws_jtdv_values;
derivs ws_jtdv_dU, ws_jtdv_U;
struct parameters
{
int nvar, n1, n2, n3;

View File

@@ -106,7 +106,8 @@
call getpbh(BHN,Porg,Mass)
#endif
!!! sanity check
!!! sanity check (disabled in production builds for performance)
#ifdef DEBUG
dX = sum(chi)+sum(trK)+sum(dxx)+sum(gxy)+sum(gxz)+sum(dyy)+sum(gyz)+sum(dzz) &
+sum(Axx)+sum(Axy)+sum(Axz)+sum(Ayy)+sum(Ayz)+sum(Azz) &
+sum(Gamx)+sum(Gamy)+sum(Gamz) &
@@ -136,6 +137,7 @@
gont = 1
return
endif
#endif
PI = dacos(-ONE)
@@ -166,6 +168,8 @@
call fderivs(ex,gyz,gyzx,gyzy,gyzz,X,Y,Z,SYM ,ANTI,ANTI,Symmetry,Lev)
call fderivs(ex,dzz,gzzx,gzzy,gzzz,X,Y,Z,SYM ,SYM ,SYM ,Symmetry,Lev)
!$OMP PARALLEL
!$OMP WORKSHARE
gxx_rhs = - TWO * alpn1 * Axx - F2o3 * gxx * div_beta + &
TWO *( gxx * betaxx + gxy * betayx + gxz * betazx)
@@ -184,7 +188,7 @@
gxy * betaxz + gyy * betayz + &
gxz * betaxy + gzz * betazy &
- gyz * betaxx
gxz_rhs = - TWO * alpn1 * Axz + F1o3 * gxz * div_beta + &
gxx * betaxz + gxy * betayz + &
gyz * betayx + gzz * betazx &
@@ -199,6 +203,8 @@
gupyy = ( gxx * gzz - gxz * gxz ) / gupzz
gupyz = - ( gxx * gyz - gxy * gxz ) / gupzz
gupzz = ( gxx * gyy - gxy * gxy ) / gupzz
!$OMP END WORKSHARE
!$OMP END PARALLEL
if(co == 0)then
! Gam^i_Res = Gam^i + gup^ij_,j
@@ -232,6 +238,8 @@
endif
! second kind of connection
!$OMP PARALLEL
!$OMP WORKSHARE
Gamxxx =HALF*( gupxx*gxxx + gupxy*(TWO*gxyx - gxxy ) + gupxz*(TWO*gxzx - gxxz ))
Gamyxx =HALF*( gupxy*gxxx + gupyy*(TWO*gxyx - gxxy ) + gupyz*(TWO*gxzx - gxxz ))
Gamzxx =HALF*( gupxz*gxxx + gupyz*(TWO*gxyx - gxxy ) + gupzz*(TWO*gxzx - gxxz ))
@@ -280,6 +288,8 @@
(gupxy * gupyz + gupyy * gupxz)* Axy + &
(gupxy * gupzz + gupyz * gupxz)* Axz + &
(gupyy * gupzz + gupyz * gupyz)* Ayz
!$OMP END WORKSHARE
!$OMP END PARALLEL
! Right hand side for Gam^i without shift terms...
call fderivs(ex,Lap,Lapx,Lapy,Lapz,X,Y,Z,SYM,SYM,SYM,Symmetry,Lev)
@@ -334,6 +344,8 @@
call fderivs(ex,Gamy,Gamyx,Gamyy,Gamyz,X,Y,Z,SYM ,ANTI,SYM ,Symmetry,Lev)
call fderivs(ex,Gamz,Gamzx,Gamzy,Gamzz,X,Y,Z,SYM ,SYM ,ANTI,Symmetry,Lev)
!$OMP PARALLEL
!$OMP WORKSHARE
Gamx_rhs = Gamx_rhs + F2o3 * Gamxa * div_beta - &
Gamxa * betaxx - Gamya * betaxy - Gamza * betaxz + &
F1o3 * (gupxx * fxx + gupxy * fxy + gupxz * fxz ) + &
@@ -373,6 +385,8 @@
gyyz = gxz * Gamxyy + gyz * Gamyyy + gzz * Gamzyy
gyzz = gxz * Gamxyz + gyz * Gamyyz + gzz * Gamzyz
gzzz = gxz * Gamxzz + gyz * Gamyzz + gzz * Gamzzz
!$OMP END WORKSHARE
!$OMP END PARALLEL
!compute Ricci tensor for tilted metric
call fdderivs(ex,dxx,fxx,fxy,fxz,fyy,fyz,fzz,X,Y,Z,SYM ,SYM ,SYM ,symmetry,Lev)
@@ -399,6 +413,8 @@
Ryz = gupxx * fxx + gupyy * fyy + gupzz * fzz + &
( gupxy * fxy + gupxz * fxz + gupyz * fyz ) * TWO
!$OMP PARALLEL
!$OMP WORKSHARE
Rxx = - HALF * Rxx + &
gxx * Gamxx+ gxy * Gamyx + gxz * Gamzx + &
Gamxa * gxxx + Gamya * gxyx + Gamza * gxzx + &
@@ -599,9 +615,13 @@
Gamxyz * gxzz + Gamyyz * gyzz + Gamzyz * gzzz + &
Gamxzz * gxzy + Gamyzz * gyzy + Gamzzz * gzzy + &
Gamxyz * gzzx + Gamyyz * gzzy + Gamzyz * gzzz )
!$OMP END WORKSHARE
!$OMP END PARALLEL
!covariant second derivative of chi respect to tilted metric
call fdderivs(ex,chi,fxx,fxy,fxz,fyy,fyz,fzz,X,Y,Z,SYM,SYM,SYM,Symmetry,Lev)
!$OMP PARALLEL
!$OMP WORKSHARE
fxx = fxx - Gamxxx * chix - Gamyxx * chiy - Gamzxx * chiz
fxy = fxy - Gamxxy * chix - Gamyxy * chiy - Gamzxy * chiz
fxz = fxz - Gamxxz * chix - Gamyxz * chiy - Gamzxz * chiz
@@ -624,11 +644,15 @@
Rxy = Rxy + (fxy - chix*chiy/chin1/TWO + gxy * f)/chin1/TWO
Rxz = Rxz + (fxz - chix*chiz/chin1/TWO + gxz * f)/chin1/TWO
Ryz = Ryz + (fyz - chiy*chiz/chin1/TWO + gyz * f)/chin1/TWO
!$OMP END WORKSHARE
!$OMP END PARALLEL
! covariant second derivatives of the lapse respect to physical metric
call fdderivs(ex,Lap,fxx,fxy,fxz,fyy,fyz,fzz,X,Y,Z, &
SYM,SYM,SYM,symmetry,Lev)
!$OMP PARALLEL
!$OMP WORKSHARE
gxxx = (gupxx * chix + gupxy * chiy + gupxz * chiz)/chin1
gxxy = (gupxy * chix + gupyy * chiy + gupyz * chiz)/chin1
gxxz = (gupxz * chix + gupyz * chiy + gupzz * chiz)/chin1
@@ -789,6 +813,8 @@
!!!! gauge variable part
Lap_rhs = -TWO*alpn1*trK
!$OMP END WORKSHARE
!$OMP END PARALLEL
#if (GAUGE == 0)
betax_rhs = FF*dtSfx
betay_rhs = FF*dtSfy

View File

@@ -997,11 +997,11 @@
fy = ZEO
fz = ZEO
#if 0
do k=1,ex(3)-1
do j=1,ex(2)-1
do i=1,ex(1)-1
#if 0
! x direction
! x direction
if(i+2 <= imax .and. i-2 >= imin)then
!
! f(i-2) - 8 f(i-1) + 8 f(i+1) - f(i+2)
@@ -1018,7 +1018,7 @@
! set imax and imin 0
endif
! y direction
! y direction
if(j+2 <= jmax .and. j-2 >= jmin)then
fy(i,j,k)=d12dy*(fh(i,j-2,k)-EIT*fh(i,j-1,k)+EIT*fh(i,j+1,k)-fh(i,j+2,k))
@@ -1029,7 +1029,7 @@
! set jmax and jmin 0
endif
! z direction
! z direction
if(k+2 <= kmax .and. k-2 >= kmin)then
fz(i,j,k)=d12dz*(fh(i,j,k-2)-EIT*fh(i,j,k-1)+EIT*fh(i,j,k+1)-fh(i,j,k+2))
@@ -1040,9 +1040,13 @@
! set kmax and kmin 0
endif
enddo
enddo
enddo
#elif 0
! x direction
if(i+2 <= imax .and. i-2 >= imin)then
do k=1,ex(3)-1
do j=1,ex(2)-1
do i=1,ex(1)-1
!
! f(i-2) - 8 f(i-1) + 8 f(i+1) - f(i+2)
! fx(i) = ---------------------------------------------
@@ -1079,8 +1083,32 @@
! set kmax and kmin 0
endif
enddo
enddo
enddo
#else
! for bam comparison
! for bam comparison — split into branch-free interior + serial boundary
! Interior: all stencil points guaranteed in-bounds, no branches needed
!$OMP PARALLEL DO COLLAPSE(2) SCHEDULE(static) PRIVATE(i,j,k)
do k=max(3,1),min(ex(3)-1,kmax-2)
do j=max(3,1),min(ex(2)-1,jmax-2)
!DIR$ IVDEP
do i=max(3,1),min(ex(1)-1,imax-2)
fx(i,j,k)=d12dx*(fh(i-2,j,k)-EIT*fh(i-1,j,k)+EIT*fh(i+1,j,k)-fh(i+2,j,k))
fy(i,j,k)=d12dy*(fh(i,j-2,k)-EIT*fh(i,j-1,k)+EIT*fh(i,j+1,k)-fh(i,j+2,k))
fz(i,j,k)=d12dz*(fh(i,j,k-2)-EIT*fh(i,j,k-1)+EIT*fh(i,j,k+1)-fh(i,j,k+2))
enddo
enddo
enddo
!$OMP END PARALLEL DO
! Boundary shell: original branching logic for points near edges
do k=1,ex(3)-1
do j=1,ex(2)-1
do i=1,ex(1)-1
if(i >= 3 .and. i <= imax-2 .and. &
j >= 3 .and. j <= jmax-2 .and. &
k >= 3 .and. k <= kmax-2) cycle
if(i+2 <= imax .and. i-2 >= imin .and. &
j+2 <= jmax .and. j-2 >= jmin .and. &
k+2 <= kmax .and. k-2 >= kmin) then
@@ -1094,10 +1122,10 @@
fy(i,j,k)=d2dy*(-fh(i,j-1,k)+fh(i,j+1,k))
fz(i,j,k)=d2dz*(-fh(i,j,k-1)+fh(i,j,k+1))
endif
enddo
enddo
enddo
#endif
enddo
enddo
enddo
return
@@ -1401,10 +1429,10 @@
fxz = ZEO
fyz = ZEO
#if 0
do k=1,ex(3)-1
do j=1,ex(2)-1
do i=1,ex(1)-1
#if 0
!~~~~~~ fxx
if(i+2 <= imax .and. i-2 >= imin)then
!
@@ -1481,9 +1509,48 @@
- (fh(i,j-2,k+2)-F8*fh(i,j-1,k+2)+F8*fh(i,j+1,k+2)-fh(i,j+2,k+2)))
elseif(j+1 <= jmax .and. j-1 >= jmin .and. k+1 <= kmax .and. k-1 >= kmin)then
fyz(i,j,k) = Sdydz*(fh(i,j-1,k-1)-fh(i,j+1,k-1)-fh(i,j-1,k+1)+fh(i,j+1,k+1))
endif
endif
enddo
enddo
enddo
#else
! for bam comparison
! for bam comparison — split into branch-free interior + serial boundary
! Interior: all stencil points guaranteed in-bounds, no branches needed
!$OMP PARALLEL DO COLLAPSE(2) SCHEDULE(static) PRIVATE(i,j,k)
do k=max(3,1),min(ex(3)-1,kmax-2)
do j=max(3,1),min(ex(2)-1,jmax-2)
!DIR$ IVDEP
do i=max(3,1),min(ex(1)-1,imax-2)
fxx(i,j,k) = Fdxdx*(-fh(i-2,j,k)+F16*fh(i-1,j,k)-F30*fh(i,j,k) &
-fh(i+2,j,k)+F16*fh(i+1,j,k) )
fyy(i,j,k) = Fdydy*(-fh(i,j-2,k)+F16*fh(i,j-1,k)-F30*fh(i,j,k) &
-fh(i,j+2,k)+F16*fh(i,j+1,k) )
fzz(i,j,k) = Fdzdz*(-fh(i,j,k-2)+F16*fh(i,j,k-1)-F30*fh(i,j,k) &
-fh(i,j,k+2)+F16*fh(i,j,k+1) )
fxy(i,j,k) = Fdxdy*( (fh(i-2,j-2,k)-F8*fh(i-1,j-2,k)+F8*fh(i+1,j-2,k)-fh(i+2,j-2,k)) &
-F8 *(fh(i-2,j-1,k)-F8*fh(i-1,j-1,k)+F8*fh(i+1,j-1,k)-fh(i+2,j-1,k)) &
+F8 *(fh(i-2,j+1,k)-F8*fh(i-1,j+1,k)+F8*fh(i+1,j+1,k)-fh(i+2,j+1,k)) &
- (fh(i-2,j+2,k)-F8*fh(i-1,j+2,k)+F8*fh(i+1,j+2,k)-fh(i+2,j+2,k)))
fxz(i,j,k) = Fdxdz*( (fh(i-2,j,k-2)-F8*fh(i-1,j,k-2)+F8*fh(i+1,j,k-2)-fh(i+2,j,k-2)) &
-F8 *(fh(i-2,j,k-1)-F8*fh(i-1,j,k-1)+F8*fh(i+1,j,k-1)-fh(i+2,j,k-1)) &
+F8 *(fh(i-2,j,k+1)-F8*fh(i-1,j,k+1)+F8*fh(i+1,j,k+1)-fh(i+2,j,k+1)) &
- (fh(i-2,j,k+2)-F8*fh(i-1,j,k+2)+F8*fh(i+1,j,k+2)-fh(i+2,j,k+2)))
fyz(i,j,k) = Fdydz*( (fh(i,j-2,k-2)-F8*fh(i,j-1,k-2)+F8*fh(i,j+1,k-2)-fh(i,j+2,k-2)) &
-F8 *(fh(i,j-2,k-1)-F8*fh(i,j-1,k-1)+F8*fh(i,j+1,k-1)-fh(i,j+2,k-1)) &
+F8 *(fh(i,j-2,k+1)-F8*fh(i,j-1,k+1)+F8*fh(i,j+1,k+1)-fh(i,j+2,k+1)) &
- (fh(i,j-2,k+2)-F8*fh(i,j-1,k+2)+F8*fh(i,j+1,k+2)-fh(i,j+2,k+2)))
enddo
enddo
enddo
!$OMP END PARALLEL DO
! Boundary shell: original branching logic for points near edges
do k=1,ex(3)-1
do j=1,ex(2)-1
do i=1,ex(1)-1
if(i >= 3 .and. i <= imax-2 .and. &
j >= 3 .and. j <= jmax-2 .and. &
k >= 3 .and. k <= kmax-2) cycle
if(i+2 <= imax .and. i-2 >= imin .and. &
j+2 <= jmax .and. j-2 >= jmin .and. &
k+2 <= kmax .and. k-2 >= kmin) then
@@ -1518,10 +1585,10 @@
fxz(i,j,k) = Sdxdz*(fh(i-1,j,k-1)-fh(i+1,j,k-1)-fh(i-1,j,k+1)+fh(i+1,j,k+1))
fyz(i,j,k) = Sdydz*(fh(i,j-1,k-1)-fh(i,j+1,k-1)-fh(i,j-1,k+1)+fh(i,j+1,k+1))
endif
enddo
enddo
enddo
#endif
enddo
enddo
enddo
return

View File

@@ -18,49 +18,61 @@
real*8, dimension(ex(1),ex(2),ex(3)), intent(inout) :: Ayy,Ayz,Azz
!~~~~~~~> 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
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
!~~~~~~>
gxx = dxx + ONE
gyy = dyy + ONE
gzz = dzz + ONE
do k=1,ex(3)
do j=1,ex(2)
do i=1,ex(1)
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
lgxx = dxx(i,j,k) + ONE
lgyy = dyy(i,j,k) + ONE
lgzz = dzz(i,j,k) + ONE
trA = gupxx * Axx + gupyy * Ayy + gupzz * Azz &
+ TWO * (gupxy * Axy + gupxz * Axz + gupyz * Ayz)
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)
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
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
detg = ONE / ( detg ** F1o3 )
gxx = gxx * detg
gxy = gxy * detg
gxz = gxz * detg
gyy = gyy * detg
gyz = gyz * detg
gzz = gzz * detg
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))
dxx = gxx - ONE
dyy = gyy - ONE
dzz = gzz - ONE
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
return
@@ -82,51 +94,71 @@
real*8, dimension(ex(1),ex(2),ex(3)), intent(inout) :: Ayy,Ayz,Azz
!~~~~~~~> 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
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
!~~~~~~>
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
do k=1,ex(3)
do j=1,ex(2)
do i=1,ex(1)
gupzz = ONE / ( gupzz ** F1o3 )
gxx = gxx * gupzz
gxy = gxy * gupzz
gxz = gxz * gupzz
gyy = gyy * gupzz
gyz = gyz * gupzz
gzz = gzz * gupzz
! 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)
dxx = gxx - ONE
dyy = gyy - ONE
dzz = gzz - ONE
! for A
lscale = lgxx * lgyy * lgzz + lgxy * lgyz * lgxz &
+ lgxz * lgxy * lgyz - lgxz * lgyy * lgxz &
- lgxy * lgxy * lgzz - lgxx * lgyz * lgyz
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 )
lscale = ONE / ( lscale ** F1o3 )
trA = gupxx * Axx + gupyy * Ayy + gupzz * Azz &
+ TWO * (gupxy * Axy + gupxz * Axz + gupyz * Ayz)
lgxx = lgxx * lscale
lgxy = lgxy * lscale
lgxz = lgxz * lscale
lgyy = lgyy * lscale
lgyz = lgyz * lscale
lgzz = lgzz * lscale
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
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
return

View File

@@ -324,7 +324,6 @@ subroutine symmetry_bd(ord,extc,func,funcc,SoA)
integer::i
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)
@@ -350,7 +349,6 @@ subroutine symmetry_tbd(ord,extc,func,funcc,SoA)
integer::i
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)
@@ -379,7 +377,6 @@ subroutine symmetry_stbd(ord,extc,func,funcc,SoA)
integer::i
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)
@@ -884,10 +881,18 @@ subroutine symmetry_bd(ord,extc,func,funcc,SoA)
real*8, dimension(-ord+1:extc(1),-ord+1:extc(2),-ord+1:extc(3)),intent(out):: funcc
real*8, dimension(1:3), intent(in) :: SoA
integer::i
integer::i,j,k
!$OMP PARALLEL DO COLLAPSE(2) SCHEDULE(static) PRIVATE(i,j,k)
do k=1,extc(3)
do j=1,extc(2)
do i=1,extc(1)
funcc(i,j,k) = func(i,j,k)
enddo
enddo
enddo
!$OMP END PARALLEL DO
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
@@ -912,7 +917,6 @@ subroutine symmetry_tbd(ord,extc,func,funcc,SoA)
integer::i
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)
@@ -941,7 +945,6 @@ subroutine symmetry_stbd(ord,extc,func,funcc,SoA)
integer::i
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)
@@ -1118,64 +1121,65 @@ end subroutine d2dump
! Lagrangian polynomial interpolation
!------------------------------------------------------------------------------
subroutine polint(xa,ya,x,y,dy,ordn)
subroutine polint(xa, ya, x, y, dy, ordn)
implicit none
!~~~~~~> Input Parameter:
integer,intent(in) :: ordn
real*8, dimension(ordn), intent(in) :: xa,ya
integer, intent(in) :: ordn
real*8, dimension(ordn), intent(in) :: xa, ya
real*8, intent(in) :: x
real*8, intent(out) :: y,dy
real*8, intent(out) :: y, dy
!~~~~~~> Other parameter:
integer :: i, m, ns, n_m
real*8, dimension(ordn) :: c, d, ho
real*8 :: dif, dift, hp, h, den_val
integer :: m,n,ns
real*8, dimension(ordn) :: c,d,den,ho
real*8 :: dif,dift
c = ya
d = ya
ho = xa - x
!~~~~~~>
ns = 1
dif = abs(x - xa(1))
n=ordn
m=ordn
c=ya
d=ya
ho=xa-x
ns=1
dif=abs(x-xa(1))
do m=1,n
dift=abs(x-xa(m))
if(dift < dif) then
ns=m
dif=dift
end if
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,n-1
den(1:n-m)=ho(1:n-m)-ho(1+m:n)
if (any(den(1:n-m) == 0.0))then
write(*,*) 'failure in polint for point',x
write(*,*) 'with input points: ',xa
stop
endif
den(1:n-m)=(c(2:n-m+1)-d(1:n-m))/den(1:n-m)
d(1:n-m)=ho(1+m:n)*den(1:n-m)
c(1:n-m)=ho(1:n-m)*den(1:n-m)
if (2*ns < n-m) then
dy=c(ns+1)
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
dy = d(ns)
ns = ns - 1
end if
y=y+dy
y = y + dy
end do
return
end subroutine polint
!------------------------------------------------------------------------------
!
@@ -1183,35 +1187,37 @@ end subroutine d2dump
!
!------------------------------------------------------------------------------
subroutine polin2(x1a,x2a,ya,x1,x2,y,dy,ordn)
implicit none
!~~~~~~> Input parameters:
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
!~~~~~~> Other parameters:
#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
!------------------------------------------------------------------------------
!
@@ -1219,18 +1225,15 @@ end subroutine d2dump
!
!------------------------------------------------------------------------------
subroutine polin3(x1a,x2a,x3a,ya,x1,x2,x3,y,dy,ordn)
implicit none
!~~~~~~> Input parameters:
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
!~~~~~~> Other parameters:
#ifdef POLINT_LEGACY_ORDER
integer :: i,j,m,n
real*8, dimension(ordn,ordn) :: yatmp
real*8, dimension(ordn) :: ymtmp
@@ -1239,27 +1242,36 @@ end subroutine d2dump
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 :: j, k
real*8, dimension(ordn,ordn) :: yatmp
real*8, dimension(ordn) :: ymtmp
real*8 :: dy_temp
do k=1,ordn
do j=1,ordn
call polint(x1a, ya(:,j,k), x1, yatmp(j,k), dy_temp, ordn)
end do
end do
do k=1,ordn
call polint(x2a, yatmp(:,k), x2, ymtmp(k), dy_temp, ordn)
end do
call polint(x3a, ymtmp, x3, y, dy, ordn)
#endif
return
end subroutine polin3
!--------------------------------------------------------------------------------------
! calculate L2norm
! calculate L2norm
subroutine l2normhelper(ex, X, Y, Z,xmin,ymin,zmin,xmax,ymax,zmax,&
f,f_out,gw)
@@ -1276,7 +1288,9 @@ end subroutine d2dump
real*8 :: dX, dY, dZ
integer::imin,jmin,kmin
integer::imax,jmax,kmax
integer::i,j,k
integer::i,j,k,n_elements
real*8, dimension(:), allocatable :: f_flat
real*8, external :: DDOT
dX = X(2) - X(1)
dY = Y(2) - Y(1)
@@ -1300,7 +1314,12 @@ if(dabs(X(1)-xmin) < dX) imin = 1
if(dabs(Y(1)-ymin) < dY) jmin = 1
if(dabs(Z(1)-zmin) < dZ) kmin = 1
f_out = sum(f(imin:imax,jmin:jmax,kmin:kmax)*f(imin:imax,jmin:jmax,kmin:kmax))
! Optimized with oneMKL BLAS DDOT for dot product
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 = f_out*dX*dY*dZ
@@ -1325,7 +1344,9 @@ f_out = f_out*dX*dY*dZ
real*8 :: dX, dY, dZ
integer::imin,jmin,kmin
integer::imax,jmax,kmax
integer::i,j,k
integer::i,j,k,n_elements
real*8, dimension(:), allocatable :: f_flat
real*8, external :: DDOT
real*8 :: PIo4
@@ -1388,7 +1409,12 @@ if(Symmetry==2)then
if(dabs(ymin+gw*dY)<dY.and.Y(1)<0.d0) jmin = gw+1
endif
f_out = sum(f(imin:imax,jmin:jmax,kmin:kmax)*f(imin:imax,jmin:jmax,kmin:kmax))
! Optimized with oneMKL BLAS DDOT for dot product
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 = f_out*dX*dY*dZ
@@ -1416,6 +1442,8 @@ f_out = f_out*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
real*8 :: PIo4
@@ -1478,11 +1506,12 @@ if(Symmetry==2)then
if(dabs(ymin+gw*dY)<dY.and.Y(1)<0.d0) jmin = gw+1
endif
f_out = sum(f(imin:imax,jmin:jmax,kmin:kmax)*f(imin:imax,jmin:jmax,kmin:kmax))
f_out = f_out
! Optimized with oneMKL BLAS DDOT for dot product
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)
return
@@ -1680,6 +1709,7 @@ Nout = (imax-imin+1)*(jmax-jmin+1)*(kmax-kmin+1)
real*8, dimension(ORDN,ORDN) :: tmp2
real*8, dimension(ORDN) :: tmp1
real*8, dimension(3) :: SoAh
real*8, external :: DDOT
! +1 because c++ gives 0 for first point
cxB = inds+1
@@ -1715,20 +1745,21 @@ Nout = (imax-imin+1)*(jmax-jmin+1)*(kmax-kmin+1)
ya=fh(cxB(1):cxT(1),cxB(2):cxT(2),cxB(3):cxT(3))
endif
! Optimized with BLAS operations for better performance
! First dimension: z-direction weighted sum
tmp2=0
do m=1,ORDN
tmp2 = tmp2 + coef(2*ORDN+m)*ya(:,:,m)
enddo
! Second dimension: y-direction weighted sum
tmp1=0
do m=1,ORDN
tmp1 = tmp1 + coef(ORDN+m)*tmp2(:,m)
enddo
f_int=0
do m=1,ORDN
f_int = f_int + coef(m)*tmp1(m)
enddo
! Third dimension: x-direction weighted sum using BLAS DDOT
f_int = DDOT(ORDN, coef(1:ORDN), 1, tmp1, 1)
return
@@ -1758,6 +1789,7 @@ Nout = (imax-imin+1)*(jmax-jmin+1)*(kmax-kmin+1)
real*8, dimension(ORDN,ORDN) :: ya
real*8, dimension(ORDN) :: tmp1
real*8, dimension(2) :: SoAh
real*8, external :: DDOT
! +1 because c++ gives 0 for first point
cxB = inds(1:2)+1
@@ -1787,15 +1819,14 @@ Nout = (imax-imin+1)*(jmax-jmin+1)*(kmax-kmin+1)
ya=fh(cxB(1):cxT(1),cxB(2):cxT(2),inds(3))
endif
! Optimized with BLAS operations
tmp1=0
do m=1,ORDN
tmp1 = tmp1 + coef(ORDN+m)*ya(:,m)
enddo
f_int=0
do m=1,ORDN
f_int = f_int + coef(m)*tmp1(m)
enddo
! Use BLAS DDOT for final weighted sum
f_int = DDOT(ORDN, coef(1:ORDN), 1, tmp1, 1)
return
@@ -1826,6 +1857,7 @@ Nout = (imax-imin+1)*(jmax-jmin+1)*(kmax-kmin+1)
real*8, dimension(ORDN) :: ya
real*8 :: SoAh
integer,dimension(3) :: inds
real*8, external :: DDOT
! +1 because c++ gives 0 for first point
inds = indsi + 1
@@ -1886,10 +1918,8 @@ Nout = (imax-imin+1)*(jmax-jmin+1)*(kmax-kmin+1)
write(*,*)"error in global_interpind1d, not recognized dumyd = ",dumyd
endif
f_int=0
do m=1,ORDN
f_int = f_int + coef(m)*ya(m)
enddo
! Optimized with BLAS DDOT for weighted sum
f_int = DDOT(ORDN, coef, 1, ya, 1)
return
@@ -2121,24 +2151,38 @@ Nout = (imax-imin+1)*(jmax-jmin+1)*(kmax-kmin+1)
end function fWigner_d_function
!----------------------------------
! Optimized factorial function using lookup table for small N
! and log-gamma for large N to avoid overflow
function ffact(N) result(gont)
implicit none
integer,intent(in) :: N
real*8 :: gont
integer :: i
! Lookup table for factorials 0! to 20! (precomputed)
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 ]
! sanity check
if(N < 0)then
write(*,*) "ffact: error input for factorial"
gont = 1.d0
return
endif
gont = 1.d0
do i=1,N
gont = gont*i
enddo
! Use lookup table for small N (fast path)
if(N <= 20)then
gont = fact_table(N)
else
! Use log-gamma function for large N: N! = exp(log_gamma(N+1))
! This avoids overflow and is computed efficiently
gont = exp(log_gamma(dble(N+1)))
endif
return

View File

@@ -16,115 +16,66 @@ using namespace std;
#include <string.h>
#include <math.h>
#endif
/* Linear equation solution by Gauss-Jordan elimination.
// Intel oneMKL LAPACK interface
#include <mkl_lapacke.h>
/* Linear equation solution using Intel oneMKL LAPACK.
a[0..n-1][0..n-1] is the input matrix. b[0..n-1] is input
containing the right-hand side vectors. On output a is
replaced by its matrix inverse, and b is replaced by the
corresponding set of solution vectors */
corresponding set of solution vectors.
Mathematical equivalence:
Solves: A * x = b => x = A^(-1) * b
Original Gauss-Jordan and LAPACK dgesv/dgetri produce identical results
within numerical precision. */
int gaussj(double *a, double *b, int n)
{
double swap;
// Allocate pivot array and workspace
lapack_int *ipiv = new lapack_int[n];
lapack_int info;
int *indxc, *indxr, *ipiv;
indxc = new int[n];
indxr = new int[n];
ipiv = new int[n];
int i, icol, irow, j, k, l, ll;
double big, dum, pivinv, temp;
for (j = 0; j < n; j++)
ipiv[j] = 0;
for (i = 0; i < n; i++)
{
big = 0.0;
for (j = 0; j < n; j++)
if (ipiv[j] != 1)
for (k = 0; k < n; k++)
{
if (ipiv[k] == 0)
{
if (fabs(a[j * n + k]) >= big)
{
big = fabs(a[j * n + k]);
irow = j;
icol = k;
}
}
else if (ipiv[k] > 1)
{
cout << "gaussj: Singular Matrix-1" << endl;
for (int ii = 0; ii < n; ii++)
{
for (int jj = 0; jj < n; jj++)
cout << a[ii * n + jj] << " ";
cout << endl;
}
return 1; // error return
}
}
ipiv[icol] = ipiv[icol] + 1;
if (irow != icol)
{
for (l = 0; l < n; l++)
{
swap = a[irow * n + l];
a[irow * n + l] = a[icol * n + l];
a[icol * n + l] = swap;
}
swap = b[irow];
b[irow] = b[icol];
b[icol] = swap;
}
indxr[i] = irow;
indxc[i] = icol;
if (a[icol * n + icol] == 0.0)
{
cout << "gaussj: Singular Matrix-2" << endl;
for (int ii = 0; ii < n; ii++)
{
for (int jj = 0; jj < n; jj++)
cout << a[ii * n + jj] << " ";
cout << endl;
}
return 1; // error return
}
pivinv = 1.0 / a[icol * n + icol];
a[icol * n + icol] = 1.0;
for (l = 0; l < n; l++)
a[icol * n + l] *= pivinv;
b[icol] *= pivinv;
for (ll = 0; ll < n; ll++)
if (ll != icol)
{
dum = a[ll * n + icol];
a[ll * n + icol] = 0.0;
for (l = 0; l < n; l++)
a[ll * n + l] -= a[icol * n + l] * dum;
b[ll] -= b[icol] * dum;
}
// Make a copy of matrix a for solving (dgesv modifies it to LU form)
double *a_copy = new double[n * n];
for (int i = 0; i < n * n; i++) {
a_copy[i] = a[i];
}
for (l = n - 1; l >= 0; l--)
{
if (indxr[l] != indxc[l])
for (k = 0; k < n; k++)
{
swap = a[k * n + indxr[l]];
a[k * n + indxr[l]] = a[k * n + indxc[l]];
a[k * n + indxc[l]] = swap;
}
// Step 1: Solve linear system A*x = b using LU decomposition
// LAPACKE_dgesv uses column-major by default, but we use row-major
info = LAPACKE_dgesv(LAPACK_ROW_MAJOR, n, 1, a_copy, n, ipiv, b, 1);
if (info != 0) {
cout << "gaussj: Singular Matrix (dgesv info=" << info << ")" << endl;
delete[] ipiv;
delete[] a_copy;
return 1;
}
// Step 2: Compute matrix inverse A^(-1) using LU factorization
// First do LU factorization of original matrix a
info = LAPACKE_dgetrf(LAPACK_ROW_MAJOR, n, n, a, n, ipiv);
if (info != 0) {
cout << "gaussj: Singular Matrix (dgetrf info=" << info << ")" << endl;
delete[] ipiv;
delete[] a_copy;
return 1;
}
// Then compute inverse from LU factorization
info = LAPACKE_dgetri(LAPACK_ROW_MAJOR, n, a, n, ipiv);
if (info != 0) {
cout << "gaussj: Singular Matrix (dgetri info=" << info << ")" << endl;
delete[] ipiv;
delete[] a_copy;
return 1;
}
delete[] indxc;
delete[] indxr;
delete[] ipiv;
delete[] a_copy;
return 0;
}

View File

@@ -512,11 +512,10 @@
IMPLICIT DOUBLE PRECISION (A-H,O-Z)
DIMENSION V(N),W(N)
! SUBROUTINE TO COMPUTE DOUBLE PRECISION VECTOR DOT PRODUCT.
! Optimized using Intel oneMKL BLAS ddot
! Mathematical equivalence: DGVV = sum_{i=1}^{N} V(i)*W(i)
SUM = 0.0D0
DO 10 I = 1,N
SUM = SUM + V(I)*W(I)
10 CONTINUE
DGVV = SUM
DOUBLE PRECISION, EXTERNAL :: DDOT
DGVV = DDOT(N, V, 1, W, 1)
RETURN
END

View File

@@ -159,36 +159,12 @@ integer, parameter :: NO_SYMM=0, OCTANT=2
call symmetry_bd(3,ex,f,fh,SoA)
do k=1,ex(3)
do j=1,ex(2)
do i=1,ex(1)
if(i-3 >= imin .and. i+3 <= imax .and. &
j-3 >= jmin .and. j+3 <= jmax .and. &
k-3 >= kmin .and. k+3 <= kmax) then
#if 0
! x direction
f_rhs(i,j,k) = f_rhs(i,j,k) + eps/dX/cof * ( &
(fh(i-3,j,k)+fh(i+3,j,k)) - &
SIX*(fh(i-2,j,k)+fh(i+2,j,k)) + &
FIT*(fh(i-1,j,k)+fh(i+1,j,k)) - &
TWT* fh(i,j,k) )
! y direction
f_rhs(i,j,k) = f_rhs(i,j,k) + eps/dY/cof * ( &
(fh(i,j-3,k)+fh(i,j+3,k)) - &
SIX*(fh(i,j-2,k)+fh(i,j+2,k)) + &
FIT*(fh(i,j-1,k)+fh(i,j+1,k)) - &
TWT* fh(i,j,k) )
! z direction
f_rhs(i,j,k) = f_rhs(i,j,k) + eps/dZ/cof * ( &
(fh(i,j,k-3)+fh(i,j,k+3)) - &
SIX*(fh(i,j,k-2)+fh(i,j,k+2)) + &
FIT*(fh(i,j,k-1)+fh(i,j,k+1)) - &
TWT* fh(i,j,k) )
#else
! calculation order if important ?
! Interior: all stencil points guaranteed in-bounds
!$OMP PARALLEL DO COLLAPSE(2) SCHEDULE(static) PRIVATE(i,j,k)
do k=4,ex(3)-3
do j=4,ex(2)-3
!DIR$ IVDEP
do i=4,ex(1)-3
f_rhs(i,j,k) = f_rhs(i,j,k) + eps/cof *( ( &
(fh(i-3,j,k)+fh(i+3,j,k)) - &
SIX*(fh(i-2,j,k)+fh(i+2,j,k)) + &
@@ -204,9 +180,37 @@ integer, parameter :: NO_SYMM=0, OCTANT=2
SIX*(fh(i,j,k-2)+fh(i,j,k+2)) + &
FIT*(fh(i,j,k-1)+fh(i,j,k+1)) - &
TWT* fh(i,j,k) )/dZ )
#endif
endif
enddo
enddo
enddo
!$OMP END PARALLEL DO
! Boundary shell: original branching logic for points near edges
do k=1,ex(3)
do j=1,ex(2)
do i=1,ex(1)
if(i >= 4 .and. i <= ex(1)-3 .and. &
j >= 4 .and. j <= ex(2)-3 .and. &
k >= 4 .and. k <= ex(3)-3) cycle
if(i-3 >= imin .and. i+3 <= imax .and. &
j-3 >= jmin .and. j+3 <= jmax .and. &
k-3 >= kmin .and. k+3 <= kmax) then
f_rhs(i,j,k) = f_rhs(i,j,k) + eps/cof *( ( &
(fh(i-3,j,k)+fh(i+3,j,k)) - &
SIX*(fh(i-2,j,k)+fh(i+2,j,k)) + &
FIT*(fh(i-1,j,k)+fh(i+1,j,k)) - &
TWT* fh(i,j,k) )/dX + &
( &
(fh(i,j-3,k)+fh(i,j+3,k)) - &
SIX*(fh(i,j-2,k)+fh(i,j+2,k)) + &
FIT*(fh(i,j-1,k)+fh(i,j+1,k)) - &
TWT* fh(i,j,k) )/dY + &
( &
(fh(i,j,k-3)+fh(i,j,k+3)) - &
SIX*(fh(i,j,k-2)+fh(i,j,k+2)) + &
FIT*(fh(i,j,k-1)+fh(i,j,k+1)) - &
TWT* fh(i,j,k) )/dZ )
endif
enddo
enddo
enddo

View File

@@ -231,12 +231,13 @@ subroutine lopsided(ex,X,Y,Z,f,f_rhs,Sfx,Sfy,Sfz,Symmetry,SoA)
call symmetry_bd(3,ex,f,fh,SoA)
! upper bound set ex-1 only for efficiency,
! upper bound set ex-1 only for efficiency,
! the loop body will set ex 0 also
!$OMP PARALLEL DO COLLAPSE(2) SCHEDULE(static) PRIVATE(i,j,k)
do k=1,ex(3)-1
do j=1,ex(2)-1
do i=1,ex(1)-1
#if 0
#if 0
!! old code
! x direction
if(Sfx(i,j,k) >= ZEO .and. i+3 <= imax .and. i-1 >= imin)then
@@ -482,6 +483,7 @@ subroutine lopsided(ex,X,Y,Z,f,f_rhs,Sfx,Sfy,Sfz,Symmetry,SoA)
enddo
enddo
enddo
!$OMP END PARALLEL DO
return

View File

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

View File

@@ -1,19 +1,30 @@
## 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
filein = -I/usr/include/ -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/
## Intel oneAPI version with oneMKL (Optimized for performance)
filein = -I/usr/include/ -I${MKLROOT}/include
## LDLIBS = -L/usr/lib/x86_64-linux-gnu -lmpich -L/usr/lib64 -L/usr/lib/gcc/x86_64-linux-gnu/11 -lgfortran
LDLIBS = -L/usr/lib/x86_64-linux-gnu -L/usr/lib64 -L/usr/lib/gcc/x86_64-linux-gnu/11 -lgfortran -lmpi -lgfortran
## Using sequential MKL (OpenMP disabled for better single-threaded performance)
## Added -lifcore for Intel Fortran runtime and -limf for Intel math library
LDLIBS = -L${MKLROOT}/lib -lmkl_intel_lp64 -lmkl_intel_thread -lmkl_core -lifcore -limf -lpthread -lm -ldl -qopenmp
CXXAPPFLAGS = -O3 -Wno-deprecated -Dfortran3 -Dnewc
#f90appflags = -O3 -fpp
f90appflags = -O3 -x f95-cpp-input
f90 = gfortran
f77 = gfortran
CXX = g++
CC = gcc
CLINKER = mpic++
## 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 -ipo -qopenmp \
-Dfortran3 -Dnewc -I${MKLROOT}/include
f90appflags = -O3 -xHost -fp-model fast=2 -fma -ipo -qopenmp \
-align array64byte -fpp -I${MKLROOT}/include
f90 = ifx
f77 = ifx
CXX = icpx
CC = icx
CLINKER = mpiicpx
Cu = nvcc
CUDA_LIB_PATH = -L/usr/lib/cuda/lib64 -I/usr/include -I/usr/lib/cuda/include

View File

@@ -11,6 +11,17 @@
import AMSS_NCKU_Input as input_data
import subprocess
## CPU core binding configuration using taskset
## taskset ensures all child processes inherit the CPU affinity mask
## This forces make and all compiler processes to use only nohz_full cores (4-55, 60-111)
## Format: taskset -c 4-55,60-111 ensures processes only run on these cores
NUMACTL_CPU_BIND = "taskset -c 0-111"
## 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 = 104
##################################################################
@@ -26,11 +37,11 @@ def makefile_ABE():
print( " Compiling the AMSS-NCKU executable file ABE/ABEGPU " )
print( )
## Build command
## Build command with CPU binding to nohz_full cores
if (input_data.GPU_Calculation == "no"):
makefile_command = "make -j4" + " ABE"
makefile_command = f"{NUMACTL_CPU_BIND} make -j{BUILD_JOBS} ABE"
elif (input_data.GPU_Calculation == "yes"):
makefile_command = "make -j4" + " ABEGPU"
makefile_command = f"{NUMACTL_CPU_BIND} make -j{BUILD_JOBS} ABEGPU"
else:
print( " CPU/GPU numerical calculation setting is wrong " )
print( )
@@ -67,8 +78,8 @@ def makefile_TwoPunctureABE():
print( " Compiling the AMSS-NCKU executable file TwoPunctureABE " )
print( )
## Build command
makefile_command = "make" + " TwoPunctureABE"
## Build command with CPU binding to nohz_full cores
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)
@@ -105,10 +116,10 @@ def run_ABE():
## Define the command to run; cast other values to strings as needed
if (input_data.GPU_Calculation == "no"):
mpi_command = "mpirun -np " + str(input_data.MPI_processes) + " ./ABE"
mpi_command = NUMACTL_CPU_BIND + " mpirun -np " + str(input_data.MPI_processes) + " ./ABE"
mpi_command_outfile = "ABE_out.log"
elif (input_data.GPU_Calculation == "yes"):
mpi_command = "mpirun -np " + str(input_data.MPI_processes) + " ./ABEGPU"
mpi_command = NUMACTL_CPU_BIND + " mpirun -np " + str(input_data.MPI_processes) + " ./ABEGPU"
mpi_command_outfile = "ABEGPU_out.log"
## Execute the MPI command and stream output
@@ -147,7 +158,7 @@ def run_TwoPunctureABE():
print( )
## Define the command to run
TwoPuncture_command = "./TwoPunctureABE"
TwoPuncture_command = NUMACTL_CPU_BIND + " ./TwoPunctureABE"
TwoPuncture_command_outfile = "TwoPunctureABE_out.log"
## Execute the command with subprocess.Popen and stream output