# MODULE: grass.benchmark
#
# AUTHOR(S): Aaron Saw Min Sern <aaronsms u nus edu>
# Vaclav Petras <wenzeslaus gmail com>
#
# PURPOSE: Benchmarking for GRASS GIS modules
#
# COPYRIGHT: (C) 2021 Vaclav Petras, and by the GRASS Development Team
#
# This program is free software under the GNU General Public
# License (>=v2). Read the file COPYING that comes with GRASS
# for details.
"""Basic functions for benchmarking modules"""
import random
import shutil
from types import SimpleNamespace
import grass.script as gs
[docs]def benchmark_single(module, label, repeat=5):
"""Benchmark module as is without changing anything.
*module* is an instance of PyGRASS Module class or any object which
has a *run* method which takes no arguments and executes the benchmarked code,
and attribute *time* which is set to execution time after the *run*
function returned. Additionally, the object should be convertible to *str*
for printing.
*repeat* sets how many times the each run is repeated.
*label* is a text to add to the result (for user-facing display).
Returns an object with attributes *time* (an average execution time),
*all_times* (list of measured execution times),
and *label* (the provided parameter as is).
"""
term_size = shutil.get_terminal_size()
if hasattr(module, "get_bash"):
print(module.get_bash())
else:
print(module)
min_avg = float("inf")
print("\u2500" * term_size.columns)
time_sum = 0
measured_times = []
for _ in range(repeat):
module.run()
print(f"{module.time}s")
time_sum += module.time
measured_times.append(module.time)
avg = time_sum / repeat
if avg < min_avg:
min_avg = avg
print(f"\nResult - {avg}s")
print("\u2500" * term_size.columns)
print(f"Best average time - {min_avg}s\n")
return SimpleNamespace(
all_times=measured_times,
time=avg,
label=label,
)
[docs]def benchmark_nprocs(module, label, max_nprocs, repeat=5, shuffle=True):
"""Benchmark module using values of nprocs up to *max_nprocs*.
*module* is an instance of PyGRASS Module class or any object which
has a *update* method taking *nprocs* as a keyword argument,
a *run* which takes no arguments and executes the benchmarked code,
and attribute *time* which is set to execution time after the *run*
function returned. Additionally, the object should be convertible to *str*
for printing.
The module is executed for each generated value of nprocs. *max_nprocs* is used
to generate a continuous range of integer values from 1 up to *max_nprocs*.
*repeat* sets how many times the each run is repeated.
So, the module will run ``max_nprocs * repeat`` times.
Runs are executed in random order, set *shuffle* to false if they
need to be executed in order based on number of threads.
*label* is a text to add to the result (for user-facing display).
Optional *nprocs* is passed to the module if present.
Returns an object with attributes *times* (list of average execution times),
*all_times* (list of lists of measured execution times),
*efficiency* (parallel efficiency), *nprocs* (list of *nprocs* values used),
and *label* (the provided parameter as is).
"""
term_size = shutil.get_terminal_size()
if hasattr(module, "get_bash"):
print(module.get_bash())
else:
print(module)
min_avg = float("inf")
min_time = None
serial_avg = None
avg_times = []
all_times = []
efficiency = []
nprocs_list = list(range(1, max_nprocs + 1))
nprocs_list_shuffled = sorted(nprocs_list * repeat)
if shuffle:
random.shuffle(nprocs_list_shuffled)
times = {}
print("\u2500" * term_size.columns)
for nprocs in nprocs_list_shuffled:
module.update(nprocs=nprocs)
module.run()
print(f"Run with {nprocs} thread(s) took {module.time}s\n")
if nprocs in times:
times[nprocs] += [module.time]
else:
times[nprocs] = [module.time]
for nprocs in sorted(times):
avg = sum(times[nprocs]) / repeat
avg_times.append(avg)
all_times.append(times[nprocs])
if nprocs == 1:
serial_avg = avg
if avg < min_avg:
min_avg = avg
min_time = nprocs
efficiency.append(serial_avg / (nprocs * avg))
print("\u2500" * term_size.columns)
if serial_avg is not None:
print(f"\nSerial average time - {serial_avg}s")
print(f"Best average time - {min_avg}s ({min_time} threads)\n")
return SimpleNamespace(
all_times=all_times,
times=avg_times,
efficiency=efficiency,
nprocs=nprocs_list,
label=label,
)
[docs]def benchmark_resolutions(module, resolutions, label, repeat=5, nprocs=None):
"""Benchmark module using different resolutions.
*module* is an instance of PyGRASS Module class or any object
with attributes as specified in :func:`benchmark_nprocs`
except that the *update* method is required only when *nprocs* is set.
*resolutions* is a list of resolutions to set (current region is currently
used and changed but that may change in the future).
*repeat* sets how many times the each run is repeated.
So, the module will run ``len(resolutions) * repeat`` times.
*label* is a text to add to the result (for user-facing display).
Optional *nprocs* is passed to the module if present
(the called module does not have to support nprocs parameter).
Returns an object with attributes *times* (list of average execution times),
*all_times* (list of lists of measured execution times), *resolutions*
(the provided parameter as is), *cells* (number of cells in the region),
and *label* (the provided parameter as is).
"""
term_size = shutil.get_terminal_size()
if hasattr(module, "get_bash"):
print(module.get_bash())
else:
print(module)
avg_times = []
all_times = []
n_cells = []
for resolution in resolutions:
gs.run_command("g.region", res=resolution)
region = gs.region()
n_cells.append(region["cells"])
print("\u2500" * term_size.columns)
print(f"Benchmark with {resolution} resolution...\n")
time_sum = 0
measured_times = []
for _ in range(repeat):
if nprocs:
module.update(nprocs=nprocs)
module.run()
print(f"{module.time}s")
time_sum += module.time
measured_times.append(module.time)
avg = time_sum / repeat
avg_times.append(avg)
all_times.append(measured_times)
print(f"\nResult - {avg}s")
return SimpleNamespace(
all_times=all_times,
times=avg_times,
resolutions=resolutions,
cells=n_cells,
label=label,
)
