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Author | SHA1 | Date |
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01fa00e2b6 | 3 years ago |
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96acdf7a91 | 3 years ago |
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87ef6badf8 | 3 years ago |
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f99bc338d9 | 3 years ago |
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fcf0432e89 | 3 years ago |
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9360208cb5 | 3 years ago |
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bc7af92054 | 3 years ago |
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ecf897ece7 | 3 years ago |
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8d687a5e62 | 3 years ago |
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e2ff8d395c | 3 years ago |
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30c4715f14 | 3 years ago |
@ -0,0 +1,6 @@
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petsc/
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petsc4py/
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openmpi-2.1.1/
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openmpi-2.1.1.tar.bz2
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tests/integration/tmp_output/
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output/
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SHELL:= zsh
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env:
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source ./env.sh
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install:
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source ./script_install.sh $(SHELL)
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run: env
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./run_simulation.sh
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binaries: ./script_fortran.sh
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test: env binaries
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cd tests/integration && python test.py
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@ -0,0 +1,28 @@
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#!/usr/bin/env bash
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#SBATCH -J test_fftma
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#SBATCH -N 4
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#SBATCH --ntasks-per-node 32
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#SBATCH --output %j_output.out
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#SBATCH -p free-rider
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#SBATCH -t 2-23:00:00
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#source activate_env.sh
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ulimit -v 115343360
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k=0
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for i in {1..4} # num de jobs totales divido num de cores (redondear para arriba)
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do
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for j in {1..1} #Numero de "carpetas" en donde resuelve simultanemente
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do
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mpirun -np 4 python ./tools/solver/Ndar.py $k 1 & # job, refinamiento
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k=$(($k+1))
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done
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wait
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done
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wait
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#!/usr/bin/env bash
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for i in {0..49}
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do
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mpirun python ./tools/solver/Ndar.py $i 2
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done
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#!/usr/bin/env bash
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#SBATCH -J test_fftma
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#SBATCH -N 1
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#SBATCH --ntasks-per-node 32
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#SBATCH --output %j_output.out
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#SBATCH -p free-rider
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#SBATCH -t 2-23:00:00
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source activate_env.sh
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ulimit -v 115343360
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for i in {1..4}
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do
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mpirun -np 32 python ./tools/solver/Ndar.py ./paper2_SinRef/$i/ 1 # job, refinamiento
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k=$(($k+1))
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done
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for i in {1..4}
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do
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mpirun -np 32 python ./tools/solver/Ndar.py ./paper2_ref4/$i/ 4 # job, refinamiento
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k=$(($k+1))
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done
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@ -0,0 +1,12 @@
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#!/usr/bin/env bash
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#SBATCH -J test_fftma
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#SBATCH -N 4
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#SBATCH --ntasks-per-node 32
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#SBATCH --output %j_output.out
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#SBATCH -p free-rider
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#SBATCH -t 2-23:00:00
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source activate_env.sh
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ulimit -v 115343360
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mpirun python -np 32 mpirunner.py
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export PATH=$HOME/python/Python-2.7.13/:$PATH
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export PYTHONPATH=$HOME/python/Python-2.7.13
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export PATH=$HOME/.local/bin:$PATH
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export PETSC_DIR=$HOME/soft/petsc
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#!/usr/bin/env bash
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#SBATCH -J connec3d_parte2
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#SBATCH -N 2
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#SBATCH --ntasks-per-node 32
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#SBATCH --output %j_output.out
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#SBATCH -p free-rider
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#SBATCH -t 2-23:00:00
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source activate_env.sh
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ulimit -v 115343360
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mpirun python -np 64 mpirunner.py
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#!/usr/bin/env bash
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#SBATCH -J connec3d_parte2
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#SBATCH -N 2
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#SBATCH --ntasks-per-node 32
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#SBATCH --output %j_output.out
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#SBATCH -p free-rider
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#SBATCH -t 2-23:00:00
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for i in {0..4}
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do
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mpirun -np 32 python ./tools/solver/Ndar.py ./data/$i/ 1 # job, refinamiento
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done
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[General]
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simDir=output
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startJob=0
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[Iterables]
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p=[10,39,15]
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seeds=[5462,2]
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lc=[4]
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connectivity=[1,2,3]
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variances=[1]
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[Generation]
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Nx = 16
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Ny = 16
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Nz = 16
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variogram_type=1
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binary = yes
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kh = 100
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kl = 0.01
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compute_lc = yes
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lcBin=yes
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genera=yes
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[Connectivity]
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keep_aspect= yes
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block_size = 4
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indicators_MinBlockSize =4
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Max_sample_size = 12
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compGconec= 1
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conec=yes
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[Solver]
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num_of_cores = 1
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ref = 2
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solve = yes
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rtol = 1e-4
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[K-Postprocess]
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MinBlockSize =1
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Max_sample_size = 4
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kperm=yes
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postprocess=yes
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SaveVfield=yes
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#!/bin/bash
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source ~/miniconda3/etc/profile.d/conda.sh
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conda activate py2_7
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python --version
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import numpy as np
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from mpi4py import MPI
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#from tools.realization import realization
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from tools.generation.config import DotheLoop, get_config
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import os
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import sys
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from tools.Prealization import realization
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CONFIG_FILE_PATH = 'config.ini' if 'CONFIG_FILE_PATH' not in os.environ else os.environ['CONFIG_FILE_PATH']
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def main():
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comm = MPI.COMM_WORLD
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rank = comm.Get_rank()
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pn = comm.Get_size()
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if pn==1:
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sequential()
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return
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if rank==0:
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manager()
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else:
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worker()
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return
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def sequential():
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comm = MPI.COMM_WORLD
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conffile = CONFIG_FILE_PATH
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parser,iterables = get_config(conffile)
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njobs = DotheLoop(-1,parser,iterables)
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start_job=0
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for job in range(start_job,njobs):
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realization(job)
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return
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def manager():
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comm = MPI.COMM_WORLD
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conffile = CONFIG_FILE_PATH
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parser,iterables = get_config(conffile)
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njobs = DotheLoop(-1,parser,iterables)
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start_job=0
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for job in range(start_job,njobs):
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dest=comm.recv(source=MPI.ANY_SOURCE)
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comm.send(job,dest=dest)
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for i in range(comm.Get_size()-1):
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dest=comm.recv(source=MPI.ANY_SOURCE)
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comm.send(-1,dest=dest)
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return
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def worker():
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comm = MPI.COMM_WORLD
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rank = comm.Get_rank()
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job=1
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while job!=-1:
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comm.send(rank,dest=0)
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job = comm.recv(source=0)
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realization(job)
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return
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main()
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#!/bin/bash
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mpirun python mpirunner.py
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#!/bin/bash
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rm ./tools/connec/connec2d
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rm ./tools/connec/connec2d
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cd ./tools/connec/connec-src && make clean && make all
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mv ./conec2d ..
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mv ./conec3d ..
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# nbl,ttotal,tcmaps/ttotal,PostConTime/ttotal
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4.000000000000000000e+00
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4.437680244445800781e-01
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8.036789380314167675e-01
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4.117019413334135902e-02
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@ -0,0 +1,13 @@
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# Runtime,Nx,Ny,Nz,con,lc,p,kh,kl,seed,variance,vario
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4.421949386596679688e-03
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1.600000000000000000e+01
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1.600000000000000000e+01
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1.600000000000000000e+01
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1.000000000000000000e+00
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4.000000000000000000e+00
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1.000000000000000056e-01
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1.000000000000000000e+02
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1.000000000000000021e-02
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5.462000000000000000e+03
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0.000000000000000000e+00
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1.000000000000000000e+00
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@ -0,0 +1,5 @@
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# K_diss, K_average,ttotal,tDiss/ttotal
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2.044456438450047153e-02
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2.093990598307741979e-02
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1.699991226196289062e-01
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8.312436538256562021e-03
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@ -0,0 +1,5 @@
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ref: 2
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Matrix creation: 0.322577953339
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Solver: 0.312026023865
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Keff: 0.02097657095221267
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N_cores: 1
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# Keff, ref, Runtime, N_cores
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2.097657095221266976e-02
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2.000000000000000000e+00
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6.346039772033691406e-01
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1.000000000000000000e+00
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@ -0,0 +1,4 @@
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6-CONNECTIVITY ANALYSIS
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PROPORTION OF PHASE 1 IS: 0.00000000
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@ -0,0 +1,4 @@
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# lcG, lcNst, lcBin
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4.617108983572631331e+00
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4.617108983572631331e+00
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5.221092552049793944e+00
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4.433069229125976562e-01
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1.709461212158203125e-04
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1.268386840820312500e-04
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# nbl,ttotal,tcmaps/ttotal,PostConTime/ttotal
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4.000000000000000000e+00
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4.130840301513671875e-01
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8.103774673900496772e-01
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3.892242871984301356e-02
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@ -0,0 +1,13 @@
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# Runtime,Nx,Ny,Nz,con,lc,p,kh,kl,seed,variance,vario
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6.468057632446289062e-03
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1.600000000000000000e+01
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1.600000000000000000e+01
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1.600000000000000000e+01
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1.000000000000000000e+00
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4.000000000000000000e+00
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1.000000000000000056e-01
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1.000000000000000000e+02
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1.000000000000000021e-02
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5.463000000000000000e+03
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0.000000000000000000e+00
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1.000000000000000000e+00
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@ -0,0 +1,5 @@
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# K_diss, K_average,ttotal,tDiss/ttotal
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2.226209553813355765e-02
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2.286500870826872062e-02
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4.626035690307617188e-03
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3.054682265629026228e-01
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ref: 2
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Matrix creation: 0.324597120285
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Solver: 0.276505947113
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Keff: 0.022595141113124082
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N_cores: 1
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# Keff, ref, Runtime, N_cores
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2.259514111312408216e-02
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2.000000000000000000e+00
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6.011030673980712891e-01
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1.000000000000000000e+00
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@ -0,0 +1,7 @@
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6-CONNECTIVITY ANALYSIS
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PROPORTION OF PHASE 1 IS: 0.125000000
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NCC : 1
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NCC : 2
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NCC : 3
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@ -0,0 +1,4 @@
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# lcG, lcNst, lcBin
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8.214006169837110960e+00
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8.214006169837110960e+00
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2.860537317826781223e+00
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3.183081150054931641e-01
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1.590251922607421875e-04
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# nbl,ttotal,tcmaps/ttotal,PostConTime/ttotal
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4.000000000000000000e+00
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5.578839778900146484e-01
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8.596443918313970700e-01
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2.408955804327898159e-02
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# Runtime,Nx,Ny,Nz,con,lc,p,kh,kl,seed,variance,vario
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1.008915901184082031e-02
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1.600000000000000000e+01
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1.600000000000000000e+01
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1.600000000000000000e+01
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1.000000000000000000e+00
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4.000000000000000000e+00
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2.035714285714285698e-01
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1.000000000000000000e+02
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1.000000000000000021e-02
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5.462000000000000000e+03
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0.000000000000000000e+00
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1.000000000000000000e+00
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# K_diss, K_average,ttotal,tDiss/ttotal
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4.053728556426364898e-02
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4.123944443032588614e-02
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1.776230335235595703e-01
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6.186535660834491246e-03
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@ -0,0 +1,5 @@
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ref: 2
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Matrix creation: 0.356295824051
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Solver: 0.41558098793
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Keff: 0.041274959938125966
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N_cores: 1
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