def plot(problem, **kwargs):
"""
Plotting mode to generate plots for performance analysis.
"""
backend = kwargs.pop('backend')
resultsdir = kwargs.pop('resultsdir')
max_bw = kwargs.pop('max_bw')
flop_ceils = kwargs.pop('flop_ceil')
point_runtime = kwargs.pop('point_runtime')
arch = kwargs['arch']
space_order = "[%s]" % ",".join(str(i) for i in kwargs['space_order'])
time_order = kwargs['time_order']
shape = "[%s]" % ",".join(str(i) for i in kwargs['shape'])
RooflinePlotter = get_ob_plotter()
bench = get_ob_bench(problem, resultsdir, kwargs)
bench.load()
if not bench.loaded:
warning("Could not load any results, nothing to plot. Exiting...")
sys.exit(0)
gflopss = bench.lookup(params=kwargs, measure="gflopss", event='main')
oi = bench.lookup(params=kwargs, measure="oi", event='main')
time = bench.lookup(params=kwargs, measure="timings", event='main')
# What plot am I?
modes = [
i for i in ['dse', 'dle', 'autotune']
if len(set(dict(j)[i] for j in gflopss)) > 1
]
# Filename
figname = "%s_dim%s_so%s_to%s_arch[%s]_bkend[%s].pdf" % (
problem, shape, space_order, time_order, arch, backend)
# Legend setup. Do not plot a legend if there's no variation in performance
# options (dse, dle, autotune)
if modes:
legend = {'loc': 'upper left', 'fontsize': 7, 'ncol': 4}
else:
legend = 'drop'
avail_colors = ['r', 'g', 'b', 'y', 'k', 'm']
avail_markers = ['o', 'x', '^', 'v', '<', '>']
used_colors = {}
used_markers = {}
# Find min and max runtimes for instances having the same OI
min_max = {v: [0, sys.maxsize] for v in oi.values()}
for k, v in time.items():
i = oi[k]
min_max[i][0] = v if min_max[i][0] == 0 else min(v, min_max[i][0])
min_max[i][1] = v if min_max[i][1] == sys.maxsize else max(
v, min_max[i][1])
with RooflinePlotter(figname=figname,
plotdir=resultsdir,
max_bw=max_bw,
flop_ceils=flop_ceils,
fancycolor=True,
legend=legend) as plot:
for k, v in gflopss.items():
so = dict(k)['space_order']
oi_value = oi[k]
time_value = time[k]
run = tuple(dict(k)[i] for i in modes)
label = ("<%s>" % ','.join(run)) if run else None
color = used_colors[
run] if run in used_colors else avail_colors.pop(0)
used_colors.setdefault(run, color)
marker = used_markers[
so] if so in used_markers else avail_markers.pop(0)
used_markers.setdefault(so, marker)
oi_loc = 0.076 if len(str(so)) == 1 else 0.09
oi_annotate = {
's': 'SO=%s' % so,
'size': 6,
'xy': (oi_value, oi_loc)
}
if time_value in min_max[oi_value] and point_runtime:
# Only annotate min and max runtimes on each OI line, to avoid
# polluting the plot too much
point_annotate = {
's': "%.0fs" % time_value,
'xytext': (0.0, 5.5),
'size': 6,
'rotation': 0
}
else:
point_annotate = None
oi_line = time_value == min_max[oi_value][0]
if oi_line:
perf_annotate = {'size': 6, 'xytext': (-4, 5)}
plot.add_point(gflops=v,
oi=oi_value,
marker=marker,
color=color,
oi_line=oi_line,
label=label,
perf_annotate=perf_annotate,
oi_annotate=oi_annotate,
point_annotate=point_annotate)
('aggressive', 'speculative'): ('s', 'b')
}
# Find min and max runtimes for instances having the same OI
min_max = {v: [0, sys.maxint] for v in oi.values()}
for k, v in time.items():
i = oi[k]
min_max[i][0] = v if min_max[i][0] == 0 else min(v, min_max[i][0])
min_max[i][1] = v if min_max[i][1] == sys.maxint else max(
v, min_max[i][1])
with RooflinePlotter(title=title,
figname=name,
plotdir=args.plotdir,
max_bw=args.max_bw,
max_flops=args.max_flops,
fancycolor=True,
legend={
'fontsize': 5,
'ncol': 4
}) as plot:
for key, gflopss in gflopss.items():
oi_value = oi[key]
time_value = time[key]
key = dict(key)
run = (key["dse"], key["dle"])
label = "<%s,%s>" % run
oi_loc = 0.05 if len(str(key["space_order"])) == 1 else 0.06
oi_annotate = {
's': 'SO=%s' % key["space_order"],
'size': 4,
'xy': (oi_value, oi_loc)
def plot(problem, **kwargs):
"""
Plotting mode to generate plots for performance analysis.
"""
resultsdir = kwargs.pop('resultsdir')
max_bw = kwargs.pop('max_bw')
flop_ceils = kwargs.pop('flop_ceil')
point_runtime = kwargs.pop('point_runtime')
arch = kwargs['arch']
space_order = "[%s]" % ",".join(str(i) for i in kwargs['space_order'])
time_order = kwargs['time_order']
tn = kwargs['tn']
shape = "[%s]" % ",".join(str(i) for i in kwargs['shape'])
RooflinePlotter = get_ob_plotter()
bench = get_ob_bench(problem, resultsdir, kwargs)
bench.load()
if not bench.loaded:
warning("Could not load any results, nothing to plot. Exiting...")
sys.exit(0)
gflopss = bench.lookup(params=kwargs, measure="gflopss", event='main')
oi = bench.lookup(params=kwargs, measure="oi", event='main')
time = bench.lookup(params=kwargs, measure="timings", event='main')
# Filaneme
figname = "%s_dim%s_so%s_to%s_arch[%s].pdf" % (problem, shape, space_order,
time_order, arch)
# Plot title
name = {'acoustic': 'Acoustic', 'tti': 'TTI'}[problem]
problem = "%s<grid=%s, TO=%s, sim=%sms>" % (name, shape, time_order, tn)
varying = [
i for i in ['dse', 'dle', 'autotune']
if len(set(dict(j)[i] for j in gflopss)) > 1
]
varying = ("varying<%s>" % ",".join(varying)) if varying else None
arch = "arch<%s>" % arch
backend = "backend<%s>" % configuration['backend']
title = ", ".join(i for i in [problem, varying, arch, backend] if i)
# Legend setup. Do not plot a legend if there's no variation in performance
# options (dse, dle, autotuning)
if varying is not None:
legend = {'loc': 'upper left', 'fontsize': 5, 'ncol': 4}
else:
legend = 'drop'
# Plot style setup {<dse, dle> -> <marker, color>}
styles = {
# DLE basic
('basic', 'basic'): ('D', 'r'),
('advanced', 'basic'): ('D', 'g'),
('aggressive', 'basic'): ('D', 'b'),
# DLE advanced
('basic', 'advanced'): ('o', 'r'),
('advanced', 'advanced'): ('o', 'g'),
('aggressive', 'advanced'): ('o', 'b'),
}
# Find min and max runtimes for instances having the same OI
min_max = {v: [0, sys.maxsize] for v in oi.values()}
for k, v in time.items():
i = oi[k]
min_max[i][0] = v if min_max[i][0] == 0 else min(v, min_max[i][0])
min_max[i][1] = v if min_max[i][1] == sys.maxsize else max(
v, min_max[i][1])
with RooflinePlotter(title=title,
figname=figname,
plotdir=resultsdir,
max_bw=max_bw,
flop_ceils=flop_ceils,
fancycolor=True,
legend=legend) as plot:
for key, gflopss in gflopss.items():
oi_value = oi[key]
time_value = time[key]
key = dict(key)
run = (key["dse"], key["dle"])
label = "<%s,%s>" % run
oi_loc = 0.05 if len(str(key["space_order"])) == 1 else 0.06
oi_annotate = {
's': 'SO=%s' % key["space_order"],
'size': 4,
'xy': (oi_value, oi_loc)
} if run[0] else None
if time_value in min_max[oi_value] and point_runtime:
# Only annotate min and max runtimes on each OI line, to avoid
# polluting the plot too much
point_annotate = {
's': "%.1f s" % time_value,
'xytext': (0, 5.2),
'size': 3.5,
'weight': 'bold',
'rotation': 0
}
else:
point_annotate = None
oi_line = time_value == min_max[oi_value][0]
if oi_line:
perf_annotate = {'size': 4, 'xytext': (-4, 4)}
plot.add_point(gflops=gflopss,
oi=oi_value,
marker=styles[run][0],
color=styles[run][1],
oi_line=oi_line,
label=label,
perf_annotate=perf_annotate,
oi_annotate=oi_annotate,
point_annotate=point_annotate)
used_colors = {}
used_markers = {}
# Find min and max runtimes for instances having the same OI
min_max = {v: [0, sys.maxsize] for v in oi.values()}
for k, v in time.items():
i = oi[k]
min_max[i][0] = v if min_max[i][0] == 0 else min(
v, min_max[i][0])
min_max[i][1] = (v if min_max[i][1] == sys.maxsize else max(
v, min_max[i][1]))
with RooflinePlotter(figname=figname,
plotdir=resultsdir,
max_bw=max_bw,
flop_ceils=flop_ceils,
fancycolor=True,
legend='drop') as plot:
for k, v in gflopss.items():
so = dict(k)['space_order']
oi_value = oi[k]
time_value = time[k]
label = "SO %s" % so
color = used_colors[
so] if so in used_colors else avail_colors.pop(0)
used_colors.setdefault(so, color)
marker = (used_markers[so]
if so in used_markers else avail_markers.pop(0))
used_markers.setdefault(so, marker)
def plot(problem, **kwargs):
"""
Plotting mode to generate plots for performance analysis.
"""
try:
from opescibench import Benchmark, RooflinePlotter
except:
raise ImportError(
"Could not import opescibench utility package.\n"
"Please install https://github.com/opesci/opescibench "
"and Matplotlib to plot performance results")
resultsdir = kwargs.pop('resultsdir')
plotdir = kwargs.pop('plotdir')
arch = kwargs.pop('arch')
max_bw = kwargs.pop('max_bw')
max_flops = kwargs.pop('max_flops')
point_runtime = kwargs.pop('point_runtime')
bench = Benchmark(name=problem, resultsdir=resultsdir, parameters=kwargs)
bench.load()
if not bench.loaded:
warning("Could not load any results, nothing to plot. Exiting...")
sys.exit(0)
gflopss = bench.lookup(params=kwargs, measure="gflopss", event='main')
oi = bench.lookup(params=kwargs, measure="oi", event='main')
time = bench.lookup(params=kwargs, measure="timings", event='main')
name = "%s_dim%s_so%s_to%s_arch[%s].pdf" % (problem, kwargs['shape'],
kwargs['space_order'],
kwargs['time_order'], arch)
name = name.replace(' ', '')
problem_styles = {'acoustic': 'Acoustic', 'tti': 'TTI'}
title = "%s [grid=%s, TO=%s, duration=%sms], varying <DSE,DLE> on %s" %\
(problem_styles[problem], list(kwargs['shape']), kwargs['time_order'],
kwargs['tn'], arch)
styles = { # (marker, color)
# DLE basic
('basic', 'basic'): ('D', 'r'),
('advanced', 'basic'): ('D', 'g'),
('speculative', 'basic'): ('D', 'y'),
('aggressive', 'basic'): ('D', 'b'),
# DLE advanced
('basic', 'advanced'): ('o', 'r'),
('advanced', 'advanced'): ('o', 'g'),
('speculative', 'advanced'): ('o', 'y'),
('aggressive', 'advanced'): ('o', 'b'),
# DLE speculative
('basic', 'speculative'): ('s', 'r'),
('advanced', 'speculative'): ('s', 'g'),
('speculative', 'speculative'): ('s', 'y'),
('aggressive', 'speculative'): ('s', 'b')
}
# Find min and max runtimes for instances having the same OI
min_max = {v: [0, sys.maxsize] for v in oi.values()}
for k, v in time.items():
i = oi[k]
min_max[i][0] = v if min_max[i][0] == 0 else min(v, min_max[i][0])
min_max[i][1] = v if min_max[i][1] == sys.maxsize else max(
v, min_max[i][1])
with RooflinePlotter(title=title,
figname=name,
plotdir=plotdir,
max_bw=max_bw,
max_flops=max_flops,
fancycolor=True,
legend={
'fontsize': 5,
'ncol': 4
}) as plot:
for key, gflopss in gflopss.items():
oi_value = oi[key]
time_value = time[key]
key = dict(key)
run = (key["dse"], key["dle"])
label = "<%s,%s>" % run
oi_loc = 0.05 if len(str(key["space_order"])) == 1 else 0.06
oi_annotate = {
's': 'SO=%s' % key["space_order"],
'size': 4,
'xy': (oi_value, oi_loc)
} if run[0] else None
if time_value in min_max[oi_value] and point_runtime:
# Only annotate min and max runtimes on each OI line, to avoid
# polluting the plot too much
point_annotate = {
's': "%.1f s" % time_value,
'xytext': (0, 5.2),
'size': 3.5,
'weight': 'bold',
'rotation': 0
}
else:
point_annotate = None
oi_line = time_value == min_max[oi_value][0]
if oi_line:
perf_annotate = {'size': 4, 'xytext': (-4, 4)}
plot.add_point(gflops=gflopss,
oi=oi_value,
marker=styles[run][0],
color=styles[run][1],
oi_line=oi_line,
label=label,
perf_annotate=perf_annotate,
oi_annotate=oi_annotate,
point_annotate=point_annotate)
warning("Could not load any results, nothing to plot. Exiting...")
sys.exit(0)
gflopss = bench.lookup(params=parameters,
measure="gflopss",
event="loop_body")
oi = bench.lookup(params=parameters, measure="oi", event="loop_body")
name = "%s_dim%s_so%s_to%s.pdf" % (
args.problem, parameters["dimensions"], parameters["space_order"],
parameters["time_order"])
title = "%s - grid: %s, time order: %s" % (args.problem.capitalize(),
parameters["dimensions"],
parameters["time_order"])
with RooflinePlotter(figname=name,
plotdir=args.plotdir,
max_bw=args.max_bw,
max_flops=args.max_flops) as plot:
for key, gflopss in gflopss.items():
oi_value = oi[key]
key = dict(key)
at = key["auto_tuning"]
style = '%s%s' % (plot.color[0] if at else plot.color[1],
plot.marker[0] if at else plot.marker[1])
plot.add_point(gflops=gflopss,
oi=oi_value,
style=style,
oi_line=at,
label='Auto-tuned' if at else 'No Auto-tuning',
oi_annotate='SO: %s' %
key["space_order"] if at else None)
(('basic', 'factorize'), 'speculative'): 'sg',
(('basic', 'glicm'), 'speculative'): 'sy',
('advanced', 'speculative'): 'sb',
}
# Find min and max runtimes for instances having the same OI
min_max = {v: [0, sys.maxint] for v in oi.values()}
for k, v in time.items():
i = oi[k]
min_max[i][0] = v if min_max[i][0] == 0 else min(v, min_max[i][0])
min_max[i][1] = v if min_max[i][1] == sys.maxint else max(
v, min_max[i][1])
with RooflinePlotter(title=title,
figname=name,
plotdir=args.plotdir,
max_bw=args.max_bw,
max_flops=args.max_flops,
legend={'fontsize': 7}) as plot:
for key, gflopss in gflopss.items():
oi_value = oi[key]
time_value = time[key]
key = dict(key)
run = (key["dse"], key["dle"])
label = "<%s,%s>" % run
oi_loc = 0.06 if len(str(key["space_order"])) == 1 else 0.07
oi_annotate = {
's': 'SO=%s' % key["space_order"],
'size': 5,
'xy': (oi_value, oi_loc)
} if run[0] else None
if time_value in min_max[oi_value]: