diff options
Diffstat (limited to 'Tools/performance_tests/run_automated.py')
| -rw-r--r-- | Tools/performance_tests/run_automated.py | 286 |
1 files changed, 121 insertions, 165 deletions
diff --git a/Tools/performance_tests/run_automated.py b/Tools/performance_tests/run_automated.py index dca038c6c..fd771faac 100644 --- a/Tools/performance_tests/run_automated.py +++ b/Tools/performance_tests/run_automated.py @@ -1,15 +1,41 @@ -#!/usr/common/software/python/2.7-anaconda-4.4/bin/python - import os, sys, shutil, datetime, git import argparse, re, time, copy import pandas as pd from functions_perftest import store_git_hash, get_file_content, \ - run_batch_nnode, extract_dataframe + run_batch_nnode, extract_dataframe + +# Get name of supercomputer and import configuration functions from +# machine-specific file +if os.getenv("LMOD_SYSTEM_NAME") == 'summit': + machine = 'summit' + from summit import executable_name, process_analysis, \ + get_config_command, time_min, get_submit_job_command, \ + get_batch_string, get_run_string, get_test_list +if os.getenv("NERSC_HOST") == 'cori': + machine = 'cori' + from cori import executable_name, process_analysis, \ + get_config_command, time_min, get_submit_job_command, \ + get_batch_string, get_run_string, get_test_list # typical use: python run_automated.py --n_node_list='1,8,16,32' --automated # Assume warpx, picsar, amrex and perf_logs repos ar in the same directory and # environment variable AUTOMATED_PERF_TESTS contains the path to this directory +# requirements: +# - python packages: gitpython and pandas +# - AUTOMATED_PERF_TESTS: environment variables where warpx, +# amrex and picsar are installed ($AUTOMATED_PERF_TESTS/warpx etc.) +# - SCRATCH: environment variable where performance results are written. +# This script will create folder $SCRATCH/performance_warpx/ + +if "AUTOMATED_PERF_TESTS" not in os.environ: + raise ValueError("environment variable AUTOMATED_PERF_TESTS is not defined.\n" + "It should contain the path to the directory where WarpX, " + "AMReX and PICSAR repos are.") +if "SCRATCH" not in os.environ: + raise ValueError("environment variable SCRATCH is not defined.\n" + "This script will create $SCRATCH/performance_warpx/ " + "to store performance results.") # Handle parser ############### parser = argparse.ArgumentParser( description='Run performance tests and write results in files' ) @@ -24,7 +50,7 @@ parser.add_argument('--commit', parser.add_argument('--automated', dest='automated', action='store_true', - default=False, + default=False, help='Use to run the automated test list') parser.add_argument('--n_node_list', dest='n_node_list', @@ -33,23 +59,25 @@ parser.add_argument('--n_node_list', parser.add_argument('--start_date', dest='start_date' ) parser.add_argument('--compiler', - choices=['gnu', 'intel'], - default='intel', + choices=['gnu', 'intel', 'pgi'], + default='intel', help='which compiler to use') parser.add_argument('--architecture', - choices=['cpu', 'knl'], + choices=['cpu', 'knl', 'gpu'], default='knl', help='which architecture to cross-compile for NERSC machines') parser.add_argument('--mode', choices=['run', 'read', 'browse_output_files', 'write_csv'], - default='run', + default='run', help='whether to run perftests or read their perf output. run calls read') args = parser.parse_args() n_node_list_string = args.n_node_list.split(',') n_node_list = [int(i) for i in n_node_list_string] start_date = args.start_date +compiler = args.compiler +architecture = args.architecture -# Set behavior variables +# Set behavior variables ######################## write_csv = False browse_output_files = False @@ -71,70 +99,21 @@ if args.automated == True: push_on_perf_log_repo = False pull_3_repos = True recompile = True - -# Each instance of this class contains information for a single test. -class test_element(): - def __init__(self, input_file=None, n_node=None, n_mpi_per_node=None, - n_omp=None, n_cell=None, n_step=None): - self.input_file = input_file - self.n_node = n_node - self.n_mpi_per_node = n_mpi_per_node - self.n_omp = n_omp - self.n_cell = n_cell - self.n_step = n_step - - def scale_n_cell(self, n_node=0): - n_cell_scaled = copy.deepcopy(self.n_cell) - index_dim = 0 - while n_node > 1: - n_cell_scaled[index_dim] *= 2 - n_node /= 2 - index_dim = (index_dim+1) % 3 - self.n_cell = n_cell_scaled + if machine == 'summit': + compiler = 'pgi' + architecture = 'gpu' # List of tests to perform # ------------------------ -test_list_unq = [] # Each test runs n_repeat times n_repeat = 2 -# n_node is kept to None and passed in functions as an external argument -# That way, several test_element_instance run with the same n_node on the same batch job -test_list_unq.append( test_element(input_file='automated_test_1_uniform_rest_32ppc', - n_mpi_per_node=8, - n_omp=8, - n_cell=[128, 128, 128], - n_step=10) ) -test_list_unq.append( test_element(input_file='automated_test_2_uniform_rest_1ppc', - n_mpi_per_node=8, - n_omp=8, - n_cell=[256, 256, 512], - n_step=10) ) -test_list_unq.append( test_element(input_file='automated_test_3_uniform_drift_4ppc', - n_mpi_per_node=8, - n_omp=8, - n_cell=[128, 128, 128], - n_step=10) ) -test_list_unq.append( test_element(input_file='automated_test_4_labdiags_2ppc', - n_mpi_per_node=8, - n_omp=8, - n_cell=[64, 64, 128], - n_step=50) ) -test_list_unq.append( test_element(input_file='automated_test_5_loadimbalance', - n_mpi_per_node=8, - n_omp=8, - n_cell=[128, 128, 128], - n_step=10) ) -test_list_unq.append( test_element(input_file='automated_test_6_output_2ppc', - n_mpi_per_node=8, - n_omp=8, - n_cell=[128, 256, 256], - n_step=0) ) -test_list = [copy.deepcopy(item) for item in test_list_unq for _ in range(n_repeat) ] +# test_list is machine-specific +test_list = get_test_list(n_repeat) # Define directories # ------------------ source_dir_base = os.environ['AUTOMATED_PERF_TESTS'] -warpx_dir = source_dir_base + '/WarpX/' +warpx_dir = source_dir_base + '/warpx/' picsar_dir = source_dir_base + '/picsar/' amrex_dir = source_dir_base + '/amrex/' res_dir_base = os.environ['SCRATCH'] + '/performance_warpx/' @@ -142,12 +121,13 @@ perf_logs_repo = source_dir_base + 'perf_logs/' # Define dictionaries # ------------------- -compiler_name = {'intel': 'intel', 'gnu': 'gcc'} -module_name = {'cpu': 'haswell', 'knl': 'mic-knl'} -module_Cname = {'cpu': 'haswell', 'knl': 'knl,quad,cache'} +compiler_name = {'intel': 'intel', 'gnu': 'gcc', 'pgi':'pgi'} +module_Cname = {'cpu': 'haswell', 'knl': 'knl,quad,cache', 'gpu':''} +csv_file = {'cori':'cori_knl.csv', 'summit':'summit.csv'} cwd = os.getcwd() + '/' bin_dir = cwd + 'Bin/' -bin_name = 'perf_tests3d.' + args.compiler + '.' + module_name[args.architecture] + '.TPROF.MPI.OMP.ex' +bin_name = executable_name(compiler, architecture) + log_dir = cwd perf_database_file = cwd + perf_database_file day = time.strftime('%d') @@ -159,30 +139,10 @@ year = time.strftime('%Y') if args.mode == 'run': start_date = datetime.datetime.now().strftime("%Y_%m_%d_%H_%M_%S") # Set default options for compilation and execution - config_command = '' - config_command += 'module unload darshan;' - config_command += 'module load craype-hugepages4M;' - if args.architecture == 'knl': - if args.compiler == 'intel': - config_command += 'module unload PrgEnv-gnu;' - config_command += 'module load PrgEnv-intel;' - elif args.compiler == 'gnu': - config_command += 'module unload PrgEnv-intel;' - config_command += 'module load PrgEnv-gnu;' - config_command += 'module unload craype-haswell;' - config_command += 'module load craype-mic-knl;' - elif args.architecture == 'cpu': - if args.compiler == 'intel': - config_command += 'module unload PrgEnv-gnu;' - config_command += 'module load PrgEnv-intel;' - elif args.compiler == 'gnu': - config_command += 'module unload PrgEnv-intel;' - config_command += 'module load PrgEnv-gnu;' - config_command += 'module unload craype-mic-knl;' - config_command += 'module load craype-haswell;' + config_command = get_config_command(compiler, architecture) # Create main result directory if does not exist if not os.path.exists(res_dir_base): - os.mkdir(res_dir_base) + os.mkdir(res_dir_base) # Recompile if requested # ---------------------- @@ -194,59 +154,34 @@ if args.mode == 'run': git_repo.pull() git_repo = git.cmd.Git( warpx_dir ) git_repo.pull() - with open(cwd + 'GNUmakefile_perftest') as makefile_handler: - makefile_text = makefile_handler.read() - makefile_text = re.sub('\nCOMP.*', '\nCOMP=%s' %compiler_name[args.compiler], makefile_text) - with open(cwd + 'GNUmakefile_perftest', 'w') as makefile_handler: - makefile_handler.write( makefile_text ) - os.system(config_command + " make -f GNUmakefile_perftest realclean ; " + " rm -r tmp_build_dir *.mod; make -j 8 -f GNUmakefile_perftest") + + # Copy WarpX/GNUmakefile to current directory and recompile + # with specific options for automated performance tests. + # This way, performance test compilation does not mess with user's + # compilation + shutil.copyfile("../../GNUmakefile","./GNUmakefile") + make_realclean_command = " make realclean WARPX_HOME=../.. " \ + "AMREX_HOME=../../../amrex/ PICSAR_HOME=../../../picsar/ " \ + "EBASE=perf_tests COMP=%s" %compiler_name[compiler] + ";" + make_command = "make -j 16 WARPX_HOME=../.. " \ + "AMREX_HOME=../../../amrex/ PICSAR_HOME=../../../picsar/ " \ + "EBASE=perf_tests COMP=%s" %compiler_name[compiler] + if machine == 'summit': + make_command += ' USE_GPU=TRUE ' + os.system(config_command + make_realclean_command + \ + "rm -r tmp_build_dir *.mod; " + make_command ) + + # Store git hashes for WarpX, AMReX and PICSAR into file, so that + # they can be read when running the analysis. if os.path.exists( cwd + 'store_git_hashes.txt' ): os.remove( cwd + 'store_git_hashes.txt' ) store_git_hash(repo_path=picsar_dir, filename=cwd + 'store_git_hashes.txt', name='picsar') store_git_hash(repo_path=amrex_dir , filename=cwd + 'store_git_hashes.txt', name='amrex' ) store_git_hash(repo_path=warpx_dir , filename=cwd + 'store_git_hashes.txt', name='warpx' ) -# This function runs a batch script with -# dependencies to perform the analysis -# after all performance tests are done. -def process_analysis(): - dependencies = '' - f_log = open(cwd + 'log_jobids_tmp.txt' ,'r') - for line in f_log.readlines(): - dependencies += line.split()[3] + ':' - batch_string = '' - batch_string += '#!/bin/bash\n' - batch_string += '#SBATCH --job-name=warpx_1node_read\n' - batch_string += '#SBATCH --time=00:07:00\n' - batch_string += '#SBATCH -C knl\n' - batch_string += '#SBATCH -N 1\n' - batch_string += '#SBATCH -S 4\n' - batch_string += '#SBATCH -q regular\n' - batch_string += '#SBATCH -e read_error.txt\n' - batch_string += '#SBATCH -o read_output.txt\n' - batch_string += '#SBATCH --mail-type=end\n' - batch_string += '#SBATCH --account=m2852\n' - batch_string += 'module load h5py-parallel\n' - batch_string += 'python ' + __file__ + ' --compiler=' + \ - args.compiler + ' --architecture=' + args.architecture + \ - ' --mode=read' + \ - ' --n_node_list=' + '"' + args.n_node_list + '"' + \ - ' --start_date=' + start_date - if args.automated == True: - batch_string += ' --automated' - batch_string += '\n' - batch_file = 'slurm_perfread' - f_exe = open(batch_file,'w') - f_exe.write(batch_string) - f_exe.close() - os.system('chmod 700 ' + batch_file) - print( 'process_analysis line: ' + 'sbatch --dependency afterok:' + dependencies[0:-1] + ' ' + batch_file) - os.system('sbatch --dependency afterok:' + dependencies[0:-1] + ' ' + batch_file) - return 0 - # Loop over the tests and run all simulations: # One batch job submitted per n_node. Several -# tests run within the same batch job. +# tests run within the same batch job. # -------------------------------------------- if args.mode == 'run': if os.path.exists( 'log_jobids_tmp.txt' ): @@ -254,24 +189,35 @@ if args.mode == 'run': # loop on n_node. One batch script per n_node for n_node in n_node_list: res_dir = res_dir_base - res_dir += '_'.join([run_name, args.compiler, args.architecture, str(n_node)]) + '/' + res_dir += '_'.join([run_name, compiler, architecture, str(n_node)]) + '/' runtime_param_list = [] # Deep copy as we change the attribute n_cell of # each instance of class test_element test_list_n_node = copy.deepcopy(test_list) + job_time_min = time_min(len(test_list)) + batch_string = get_batch_string(test_list_n_node, job_time_min, module_Cname[architecture], n_node) # Loop on tests - for current_run in test_list_n_node: + for count, current_run in enumerate(test_list_n_node): current_run.scale_n_cell(n_node) runtime_param_string = ' amr.n_cell=' + ' '.join(str(i) for i in current_run.n_cell) + runtime_param_string += ' amr.max_grid_size=' + str(current_run.max_grid_size) + runtime_param_string += ' amr.blocking_factor=' + str(current_run.blocking_factor) runtime_param_string += ' max_step=' + str( current_run.n_step ) - runtime_param_list.append( runtime_param_string ) + # runtime_param_list.append( runtime_param_string ) + run_string = get_run_string(current_run, architecture, n_node, count, bin_name, runtime_param_string) + batch_string += run_string + batch_string += 'rm -rf plotfiles lab_frame_data diags\n' + + submit_job_command = get_submit_job_command() # Run the simulations. - run_batch_nnode(test_list_n_node, res_dir, bin_name, config_command,\ - architecture=args.architecture, Cname=module_Cname[args.architecture], \ - n_node=n_node, runtime_param_list=runtime_param_list) + run_batch_nnode(test_list_n_node, res_dir, bin_name, config_command, batch_string, submit_job_command) os.chdir(cwd) # submit batch for analysis - process_analysis() + if os.path.exists( 'read_error.txt' ): + os.remove( 'read_error.txt' ) + if os.path.exists( 'read_output.txt' ): + os.remove( 'read_output.txt' ) + process_analysis(args.automated, cwd, compiler, architecture, args.n_node_list, start_date) # read the output file from each test and store timers in # hdf5 file with pandas format @@ -279,10 +225,10 @@ if args.mode == 'run': for n_node in n_node_list: print(n_node) if browse_output_files: + res_dir = res_dir_base + res_dir += '_'.join([run_name, compiler,\ + architecture, str(n_node)]) + '/' for count, current_run in enumerate(test_list): - res_dir = res_dir_base - res_dir += '_'.join([run_name, args.compiler,\ - args.architecture, str(n_node)]) + '/' # Read performance data from the output file output_filename = 'out_' + '_'.join([current_run.input_file, str(n_node), str(current_run.n_mpi_per_node), str(current_run.n_omp), str(count)]) + '.txt' # Read data for all test to put in hdf5 a database @@ -305,33 +251,20 @@ for n_node in n_node_list: # Load file perf_database_file if exists, and # append with results from this scan if os.path.exists(perf_database_file): - df_base = pd.read_hdf(perf_database_file, 'all_data', format='table') - # df_base = pd.read_hdf(perf_database_file, 'all_data') + # df_base = pd.read_hdf(perf_database_file, 'all_data', format='table') + df_base = pd.read_hdf(perf_database_file, 'all_data') updated_df = df_base.append(df_newline, ignore_index=True) else: updated_df = df_newline - # Write dataframe to file perf_database_file + # Write dataframe to file perf_database_file # (overwrite if file exists) updated_df.to_hdf(perf_database_file, key='all_data', mode='w') - - # Rename directory with precise date+hour for archive purpose - if rename_archive == True: - loc_counter = 0 - res_dir_arch = res_dir_base - res_dir_arch += '_'.join([year, month, day, run_name, args.compiler,\ - args.architecture, str(n_node), str(loc_counter)]) + '/' - while os.path.exists( res_dir_arch ): - loc_counter += 1 - res_dir_arch = res_dir_base - res_dir_arch += '_'.join([year, month, day, run_name, args.compiler,\ - args.architecture, str(n_node), str(loc_counter)]) + '/' - os.rename( res_dir, res_dir_arch ) # Extract sub-set of pandas data frame, write it to # csv file and copy this file to perf_logs repo # ------------------------------------------------- if write_csv: - # Extract small data from data frame and write them to + # Extract small data from data frame and write them to # First, generate csv files df = pd.read_hdf( perf_database_file ) # One large file @@ -342,19 +275,42 @@ if write_csv: df_small[ df_small['input_file']=='automated_test_6_output_2ppc' ]['time_WritePlotFile'] df_small = df_small.loc[:, ['date', 'input_file', 'git_hashes', 'n_node', 'n_mpi_per_node', 'n_omp', 'rep', 'start_date', 'time_initialization', 'step_time'] ] # Write to csv - df_small.to_csv( 'cori_knl.csv' ) + df_small.to_csv( csv_file[machine] ) # Errors may occur depending on the version of pandas. I had errors with v0.21.0 solved with 0.23.0 # Second, move files to perf_logs repo if update_perf_log_repo: + # get perf_logs repo git_repo = git.Repo( perf_logs_repo ) if push_on_perf_log_repo: git_repo.git.stash('save') git_repo.git.pull() - shutil.move( 'cori_knl.csv', perf_logs_repo + '/logs_csv/cori_knl.csv' ) + # move csv file to perf_logs repon and commit the new version + shutil.move( csv_file[machine], perf_logs_repo + '/logs_csv/' + csv_file[machine] ) os.chdir( perf_logs_repo ) sys.path.append('./') import generate_index_html git_repo.git.add('./index.html') - git_repo.git.add('./logs_csv/cori_knl.csv') + git_repo.git.add('./logs_csv/' + csv_file[machine]) index = git_repo.index index.commit("automated tests") + +# Rename all result directories for archiving purposes: +# include date in the name, and a counter to avoid over-writing +for n_node in n_node_list: + if browse_output_files: + res_dir = res_dir_base + res_dir += '_'.join([run_name, compiler,\ + architecture, str(n_node)]) + '/' + # Rename directory with precise date+hour for archive purpose + if rename_archive == True: + loc_counter = 0 + res_dir_arch = res_dir_base + res_dir_arch += '_'.join([year, month, day, run_name, compiler,\ + architecture, str(n_node), str(loc_counter)]) + '/' + while os.path.exists( res_dir_arch ): + loc_counter += 1 + res_dir_arch = res_dir_base + res_dir_arch += '_'.join([year, month, day, run_name, compiler,\ + architecture, str(n_node), str(loc_counter)]) + '/' + print("renaming " + res_dir + " -> " + res_dir_arch) + os.rename( res_dir, res_dir_arch ) |