'Mpath' : Mpath_hdfs,
'wPath' : wPath_hdfs,
'Npath' : Npath_hdfs,
'nodes' : nodes,
'savestub': gb,
'tableStub' : '{}_{}'.format(gb, mattype_m)}
cmd_params_disk['opType'] = op
cmd_params_hdfs['opType'] = op
args_disk = cmd_args.format(**cmd_params_disk)
args_hdfs = cmd_args.format(**cmd_params_hdfs)
if 'SYSTEMML' in systems:
utils.run_spark(program = 'SystemMLMatrixOps',
sbt_dir = './systemml',
cmd_args = args_hdfs)
if 'MLLIB' in systems:
utils.run_spark(program = 'SparkMatrixOps',
sbt_dir = './mllib',
cmd_args = args_hdfs)
if 'MADLIB' in systems:
utils.run_python(program = 'madlib_matrix_ops.py',
cmd_args = args_disk)
if 'R' in systems:
utils.run_pbdR(program = 'R_matrix_ops.R',
cmd_args = args_disk)
if 'SCIDB' in systems:
utils.run_python(program = 'scidb_matrix_ops.py',
cmd_args = args_disk)
if (project_root is None):
msg = 'Pease set environment variable "BENCHMARK_PROJECT_ROOT"'
raise StandardError(msg)
externals = {
'lib': '/lib',
'disk_data': '/tests/SimpleMatrixOps (Disk Data)/output'
}
for name in externals:
os.symlink(project_root + externals[name], '../external/' + name)
sys.path.append('../external/lib/python')
import make_utils as utils
import global_params as params
# start logging
start_make_logging()
# compile
makelog = '../../output/make.log'
utils.run_sbt('./spark', makelog=makelog)
utils.run_python(program='get_data.py')
os.putenv('SAVE_STUB', '_1')
utils.run_spark(program='SparkPreclean',
sbt_dir='./spark',
cmd_args='/scratch/day_1.gz true')
# stop logging
end_make_logging()
feature_names = 'dense_features_scaled' if typ == 'dense' else 'features'
for op in ops:
args_disk = cmd_arg_params.format(opType=op,
inputPath=path_disk,
nodes=nodes,
featureNames='ignored',
stub=stub)
args_hdfs = cmd_arg_params.format(opType=op,
inputPath=path_hdfs,
nodes=nodes,
featureNames=feature_names,
stub=stub)
os.system('rm -rf /tmp/systemml')
if 'TF' in systems:
utils.run_python(program='tf_algs.py', cmd_args=args_disk)
if 'MLLIB' in systems:
utils.run_spark(program='SparkMLAlgorithms',
sbt_dir='./mllib',
cmd_args=args_hdfs)
if 'SYSTEMML' in systems:
utils.run_spark(program='SystemMLMLAlgorithms',
sbt_dir='./systemml',
driver_memory='64G',
cmd_args=args_hdfs)
utils.run_spark(program='SystemMLMLAlgorithms',
sbt_dir='./systemml',
driver_memory='32G',
cmd_args=args_hdfs + ' execSpark=true')
if 'MADLIB' in systems:
if typ == 'dense':
# start logging
start_make_logging()
test_type = args.test_type
nodes = args.nodes
sparsity = args.sparsity
systems = args.systems
op_types = args.operators
sparse_gb = args.sparse_gb
# compile
makelog = '../../output/make.log'
utils.run_sbt('./systemml', makelog=makelog)
utils.run_sbt('./mllib', makelog=makelog)
if test_type == 'scale_nodes':
utils.run_python(program='node_scaling_tests.py',
cmd_args='{} "{}" "{}" "{}" {}'.format(
nodes, sparsity, systems, op_types, sparse_gb))
elif test_type == 'scale_mat':
utils.run_python(program='msize_scaling_tests.py',
cmd_args='{} "{}" "{}" "{}" {}'.format(
nodes, sparsity, systems, op_types, sparse_gb))
else:
raise StandardError('TEST_TYPE must be one of: "scale_nodes", "scale_mat"')
remove_dir('scratch_space')
# stop logging
end_make_logging()
# create symlinks to external resources
project_root = os.getenv('BENCHMARK_PROJECT_ROOT')
if (project_root is None):
msg = 'Pease set environment variable "BENCHMARK_PROJECT_ROOT"'
raise StandardError(msg)
externals = {
'lib': '/lib',
'disk_data': '/tests/SimpleMatrixOps (Disk Data)/output'
}
for name in externals:
os.symlink(project_root + externals[name], '../external/' + name)
sys.path.append('../external/lib/python')
import make_utils as utils
import global_params as params
# start logging
start_make_logging()
# compile
makelog = '../../output/make.log'
utils.run_sbt('./spark', makelog=makelog)
utils.run_spark(program='SparkPreclean', sbt_dir='./spark', cmd_args='_1 true')
utils.run_python(program='postprocess.py', cmd_args='--sparse False --stub _1')
utils.run_python(program='build_tables.py', cmd_args='_1')
# stop logging
end_make_logging()
type=str,
default=systems,
help='Space delimited list of systems to compare. May be any of "{}"'.
format(systems))
args = parser.parse_args()
# start logging
start_make_logging()
# compile
makelog = '../../output/make.log'
utils.run_sbt('./systemml', makelog=makelog)
utils.run_sbt('./mllib', makelog=makelog)
if args.test_type == 'criteo':
utils.run_python(program='run_criteo_tests.py',
cmd_args='{} {} "{}" "{}"'.format(args.stub, args.nodes,
args.systems,
args.algorithms))
if args.test_type == 'scale':
utils.run_python(program='run_scale_tests.py',
cmd_args='{} {} "{}" "{}" "{}" {}'.format(
args.stub, args.nodes, args.algorithms, args.systems,
args.sparsity, args.sparse_gb))
remove_dir('scratch_space')
# stop logging
end_make_logging()
ytable_name = 'adclick_y_array{}'
else:
ytable_name = 'adclick_y_mat{}'
argv = {'stub': stub,
'nodes': nodes,
'op': alg,
'gb': gb}
cmd_args_R = args_R.format(**argv)
cmd_args_madlib = args_madlib.format(**argv)
cmd_args_hdfs = args_hdfs.format(**argv)
if 'R' in systems:
utils.run_pbdR(program='ml_algs.R',
cmd_args=cmd_args_R)
if 'SYSTEMML' in systems:
utils.run_spark(program='SystemMLMLAlgorithms',
sbt_dir='./systemml',
driver_memory='32G',
cmd_args=cmd_args_hdfs)
if 'MLLIB' in systems:
utils.run_spark(program='SparkMLAlgorithms',
sbt_dir='./mllib',
driver_memory='32G',
cmd_args=cmd_args_hdfs)
if 'MADLIB' in systems:
utils.run_python(program='madlib_algs.py',
cmd_args=cmd_args_madlib)
if 'SCIDB' in systems:
utils.run_python(program='scidb_algs.py',
cmd_args=cmd_args_madlib)
# start logging
start_make_logging()
nodes = args.nodes
matsize = args.matsize
systems = args.systems
test_type = args.test_type
op_types = args.operators
# compile
makelog = '../../output/make.log'
utils.run_sbt('./systemml', makelog=makelog)
utils.run_sbt('./mllib', makelog=makelog)
if test_type == 'scale_nodes':
utils.run_python(program='node_scaling_tests.py',
cmd_args='{} "{}" "{}" "{}"'.format(
nodes, matsize, systems, op_types))
elif test_type == 'scale_mat':
utils.run_python(program='msize_scaling_tests.py',
cmd_args='{} "{}" "{}" "{}"'.format(
nodes, matsize, systems, op_types))
else:
raise StandardError('TEST_TYPE must be one of: "scale_nodes", "scale_mat"')
remove_dir('scratch_space')
# stop logging
end_make_logging()
# compile
makelog = '../../output/make.log'
utils.run_sbt('./systemml', makelog=makelog)
utils.run_sbt('./mllib', makelog=makelog)
cmd_args_template = 'opType={} mattype={} nrows="{}"'
mattype = 'tall'
if test_type == 'matrix-ops':
for op in op_types:
args = (op, mattype, nrows)
cmd_args = cmd_args_template.format(*args)
cmd_args += ' fixedAxis=100 step=10'
if 'NUMPY' in systems:
utils.run_python(program='np_matrix_ops.py', cmd_args=cmd_args)
if 'TF' in systems:
utils.run_python(program='tf_matrix_ops.py', cmd_args=cmd_args)
if 'R' in systems:
utils.run_R(program='R_matrix_ops.R', cmd_args=cmd_args)
if 'SYSTEMML' in systems:
utils.run_spark(program='SystemMLMatrixOps',
sbt_dir='./systemml',
cmd_args=cmd_args)
if 'MLLIB' in systems:
utils.run_spark(program='MLLibMatrixOps',
sbt_dir='./mllib',
cmd_args=cmd_args)
if 'MADLIB' in systems:
utils.run_python(program='madlib_matrix_ops.py', cmd_args=cmd_args)
if 'SCIDB' in systems:
'nodes={nodes} opType={op}')
for alg in algorithms:
if alg == 'logit':
ytable_name = 'adclick_y_array{}'
else:
ytable_name = 'adclick_y_mat{}'
argv = {
'stub': stub,
'nodes': nodes,
'op': alg,
'ytable': ytable_name.format(stub)
}
cmd_args_R = args_R.format(**argv)
cmd_args_madlib = args_madlib.format(**argv)
cmd_args_hdfs = args_hdfs.format(**argv)
if 'SYSTEMML' in systems:
utils.run_spark(program='SystemMLMLAlgorithms',
sbt_dir='./systemml',
driver_memory='32G',
cmd_args=cmd_args_hdfs)
if 'MLLIB' in systems:
utils.run_spark(program='SparkMLAlgorithms',
sbt_dir='./mllib',
driver_memory='32G',
cmd_args=cmd_args_hdfs)
if 'MADLIB' in systems:
utils.run_python(program='madlib_bigmat_algs.py',
cmd_args=cmd_args_madlib)
# utils.run_sbt('./systemml', makelog=makelog)
# utils.run_sbt('./mllib', makelog=makelog)
cmd_args_template = 'opType={} mattype={} nrow="{}" ncol=100'
mattype = 'tall'
nproc = [1, 2, 4, 8, 16, 24]
for op in op_types:
for num_proc in nproc:
# This will force the process to execute only on a subset of processors
utils.set_nproc(num_proc)
args = (op, mattype, nrows)
cmd_args = cmd_args_template.format(*args)
cmd_args += ' fixedAxis=100 step=10 nproc={}'.format(num_proc)
if 'NUMPY' in systems:
utils.run_python(program='np_algs.py', cmd_args=cmd_args)
if ('TF' in systems) and (op != 'logit'):
utils.run_python(program='tf_algorithms.py', cmd_args=cmd_args)
if 'R' in systems:
utils.run_R(program='ml_algs.R', cmd_args=cmd_args)
if 'SYSTEMML' in systems:
utils.run_spark(program='SystemMLMLAlgorithms',
sbt_dir='./systemml',
driver_cores=str(num_proc),
cmd_args=cmd_args)
if 'MLLIB' in systems:
utils.run_spark(program='SparkMLAlgorithms',
sbt_dir='./mllib',
driver_cores=str(num_proc),
cmd_args=cmd_args)
utils.set_nproc(999)
