def plot(sids, value, label='', paper=False):
colors = [cmap(i) for i in np.linspace(0, 1, len(sids))]
labels = []
first = True
for sid in sids:
if sid.startswith('rp.session'):
rp = True
else:
rp = False
session_dir = os.path.join(PICKLE_DIR, sid)
unit_info_df = pd.read_pickle(os.path.join(session_dir, 'unit_info.pkl'))
pilot_info_df = pd.read_pickle(os.path.join(session_dir, 'pilot_info.pkl'))
unit_prof_df = pd.read_pickle(os.path.join(session_dir, 'unit_prof.pkl'))
session_info_df = pd.read_pickle(os.path.join(session_dir, 'session_info.pkl'))
# Legend info
info = session_info_df.loc[sid]
if rp:
# For this call assume that there is only one pilot per session
resources = get_resources(unit_info_df, pilot_info_df, sid)
assert len(resources) == 1
resource_label = resources.values()[0]
else:
resource_label = 'bogus'
# Get only the entries for this session
#uf = unit_prof_df[unit_prof_df['sid'] == sid]
# We sort the units based on the order they arrived at the agent
#ufs = uf.sort('awo_get_u_pend')
cores = info['metadata.effective_cores']
#cores = 32
if value == 'cc_fork':
spec = {
'in': [
{'info' : 'aec_start_script'}
],
'out' : [
{'info' : 'aec_after_exec'}
]
}
rpu.add_concurrency (unit_prof_df, 'cc_fork', spec)
elif value == 'cc_exit':
spec = {
'in': [
{'info' : 'aec_after_exec'}
],
'out' : [
{'state': rps.AGENT_STAGING_OUTPUT_PENDING, 'event': 'advance'},
]
}
rpu.add_concurrency (unit_prof_df, 'cc_exit', spec)
df = unit_prof_df[
(unit_prof_df[value] >= 0) &
#(unit_prof_df.event == 'advance') &
(unit_prof_df.sid == sid)
][['time', value]]
df.columns = ['time', cores]
df['time'] -= df['time'].min()
if first:
df_all = df
else:
df_all = pd.merge(df_all, df, on='time', how='outer')
#labels.append("Cores: %d" % cores)
# labels.append("%d" % cores)
#labels.append("%d - %s" % (cores, 'RP' if rp else 'ORTE'))
#labels.append(sid[-4:])
labels.append("%d" % info['metadata.cu_runtime'])
first = False
df_all.set_index('time', inplace=True)
print df_all.head()
#df_all.plot(colormap='Paired')
#df_all.plot(drawstyle='steps-post')
#ax = df_all.plot(drawstyle='steps-pre', fontsize=TICK_FONTSIZE, linewidth=LINEWIDTH, colors=colors)
ax = df_all.plot(fontsize=TICK_FONTSIZE, linewidth=LINEWIDTH, colors=colors)
# Vertial reference
#x_ref = info['metadata.generations'] * info['metadata.cu_runtime']
#mp.pyplot.plot((x_ref, x_ref),(0, 1000), 'k--')
#labels.append("Optimal")
location = 'upper right'
legend = mp.pyplot.legend(labels, loc=location, fontsize=LEGEND_FONTSIZE, labelspacing=0)
legend.get_frame().set_linewidth(BORDERWIDTH)
if not paper:
mp.pyplot.title("Concurrent number of CUs in stage '%s'.\n"
"%d generations of a variable number of 'concurrent' CUs of %d core(s) with a %ss payload on a variable core pilot on %s.\n"
"Constant number of %d sub-agent with %d ExecWorker(s) each.\n"
"RP: %s - RS: %s - RU: %s"
% (value,
info['metadata.generations'], info['metadata.cu_cores'], info['metadata.cu_runtime'], resource_label,
info['metadata.num_sub_agents'], info['metadata.num_exec_instances_per_sub_agent'],
info['metadata.radical_stack.rp'], info['metadata.radical_stack.rs'], info['metadata.radical_stack.ru']
), fontsize=TITLE_FONTSIZE)
mp.pyplot.xlabel("Time (s)", fontsize=LABEL_FONTSIZE)
mp.pyplot.ylabel("\# Concurrent Units", fontsize=LABEL_FONTSIZE)
# mp.pyplot.ylim(0, 200)
mp.pyplot.ylim(-50,)
mp.pyplot.xlim(0, 600)
#ax.get_xaxis().set_ticks([])
print dir(ax)
[i.set_linewidth(BORDERWIDTH) for i in ax.spines.itervalues()]
plt.setp(ax.yaxis.get_ticklines(), 'markeredgewidth', BORDERWIDTH)
plt.setp(ax.xaxis.get_ticklines(), 'markeredgewidth', BORDERWIDTH)
# width = 3.487
width = 3.3
height = width / 1.618
# height = 2.5
fig = mp.pyplot.gcf()
fig.set_size_inches(width, height)
# fig.subplots_adjust(left=0, right=1, top=1, bottom=1)
# fig.tight_layout(w_pad=0.0, h_pad=0.0, pad=0.1)
fig.tight_layout(pad=0.1)
mp.pyplot.savefig('plot_concurrency.pdf')
mp.pyplot.close()
def preprocess(sid):
session_dir = os.path.join(PICKLE_DIR, sid)
if os.path.isdir(session_dir):
report.warn("Session dir '%s' already exists, skipping session." %
session_dir)
return
try:
sid_profiles = find_profiles(sid)
print sid_profiles
report.info("Combining profiles for session: %s.\n" % sid)
combined_profiles = rpu.combine_profiles(sid_profiles)
uids = set()
for p in combined_profiles:
uids.add(p['uid'])
report.info("Converting profiles to frames for session: %s.\n" % sid)
frames = rpu.prof2frame(combined_profiles)
print frames
report.info("Head of Combined DF for session %s:\n" % sid)
print frames.entity.unique()
ses_prof_fr, pilot_prof_fr, cu_prof_fr = rpu.split_frame(frames)
report.info("Head of CU Profiling DF for session %s:\n" % sid)
print cu_prof_fr.head()
report.info("Head of Session DF for session %s:\n" % sid)
ses_prof_fr.insert(0, 'sid', sid)
print ses_prof_fr.head()
report.info("Head of Pilot DF for session %s:\n" % sid)
pilot_prof_fr.insert(0, 'sid', sid)
print pilot_prof_fr.head()
report.info("Head of CU DF for session %s:\n" % sid)
rpu.add_states(cu_prof_fr)
report.info("Head of CU DF for session %s (after states added):\n" %
sid)
print cu_prof_fr.head()
report.info("Head of CU DF for session %s (after info added):\n" % sid)
rpu.add_info(cu_prof_fr)
print cu_prof_fr.head()
report.info(
"Head of CU DF for session %s (after concurrency added):\n" % sid)
# Add a column with the number of concurrent populating the database
spec = {
'in': [{
'state': rps.STAGING_INPUT,
'event': 'advance'
}],
'out': [{
'state': rps.AGENT_STAGING_INPUT_PENDING,
'event': 'advance'
}, {
'state': rps.FAILED,
'event': 'advance'
}, {
'state': rps.CANCELED,
'event': 'advance'
}]
}
rpu.add_concurrency(cu_prof_fr, 'cc_populating', spec)
# Add a column with the number of concurrent staging in units
spec = {
'in': [{
'state': rps.AGENT_STAGING_INPUT,
'event': 'advance'
}],
'out': [{
'state': rps.ALLOCATING_PENDING,
'event': 'advance'
}, {
'state': rps.FAILED,
'event': 'advance'
}, {
'state': rps.CANCELED,
'event': 'advance'
}]
}
rpu.add_concurrency(cu_prof_fr, 'cc_stage_in', spec)
# Add a column with the number of concurrent scheduling units
spec = {
'in': [{
'state': rps.ALLOCATING,
'event': 'advance'
}],
'out': [{
'state': rps.EXECUTING_PENDING,
'event': 'advance'
}, {
'state': rps.FAILED,
'event': 'advance'
}, {
'state': rps.CANCELED,
'event': 'advance'
}]
}
rpu.add_concurrency(cu_prof_fr, 'cc_sched', spec)
# Add a column with the number of concurrent Executing units
spec = {
'in': [{
'state': rps.EXECUTING,
'event': 'advance'
}],
'out': [{
'state': rps.AGENT_STAGING_OUTPUT_PENDING,
'event': 'advance'
}, {
'state': rps.FAILED,
'event': 'advance'
}, {
'state': rps.CANCELED,
'event': 'advance'
}]
}
rpu.add_concurrency(cu_prof_fr, 'cc_exec', spec)
# Add a column with the number of concurrent Executing units
spec = {
'in': [{
'state': rps.AGENT_STAGING_OUTPUT,
'event': 'advance'
}],
'out': [{
'state': rps.PENDING_OUTPUT_STAGING,
'event': 'advance'
}, {
'state': rps.FAILED,
'event': 'advance'
}, {
'state': rps.CANCELED,
'event': 'advance'
}]
}
rpu.add_concurrency(cu_prof_fr, 'cc_stage_out', spec)
print cu_prof_fr.head()
report.info("Head of CU DF for session %s (after sid added):\n" % sid)
cu_prof_fr.insert(0, 'sid', sid)
print cu_prof_fr.head()
report.info("CU DF columns for session %s:\n" % sid)
print cu_prof_fr['info'].unique()
# transpose
report.info("Head of Transposed CU DF for session %s:\n" % sid)
tr_cu_prof_fr = rpu.get_info_df(cu_prof_fr)
tr_cu_prof_fr.insert(0, 'sid', sid)
print tr_cu_prof_fr.head()
report.info("Head of json Docs for session %s:\n" % sid)
ses_info_fr, pilot_info_fr, unit_info_fr = json2frame(db=None, sid=sid)
print ses_info_fr.head()
except Exception as e:
report.error("Failed to pre-process data for session %s (%s)" %
(sid, e))
return
report.header("Writing dataframes to disk.\n")
try:
os.mkdir(session_dir)
tr_cu_prof_fr.to_pickle(os.path.join(session_dir, 'tr_unit_prof.pkl'))
ses_info_fr.to_pickle(os.path.join(session_dir, 'session_info.pkl'))
pilot_info_fr.to_pickle(os.path.join(session_dir, 'pilot_info.pkl'))
unit_info_fr.to_pickle(os.path.join(session_dir, 'unit_info.pkl'))
ses_prof_fr.to_pickle(os.path.join(session_dir, 'session_prof.pkl'))
pilot_prof_fr.to_pickle(os.path.join(session_dir, 'pilot_prof.pkl'))
cu_prof_fr.to_pickle(os.path.join(session_dir, 'unit_prof.pkl'))
except Exception as e:
report.error("Failed to write data: %s" % e)
return
'update' : event_filter['update' ]['in']
}
for exp in sorted(exp_frames.keys()):
print "plotting '%s'" % exp
# these are the franes we want to plot for this experiment
plot_frames = list()
for frame, label in exp_frames[exp]:
# we add a data frame column for CU concurrency for the component of
# interest. Also, we calibrate t0 to when the first unit enters that
# component.
rpu.add_concurrency (frame, tgt='cu_num', spec=event_filter[exp])
rpu.calibrate_frame (frame, spec=calib_filter[exp])
# plot_frames.append([frame, label])
plot_frames.append([frame, None])
# create the plots for CU concurrency over time, and also show the plots in the notebook
fig, _ = rpu.frame_plot(plot_frames, logx=False, logy=False,
title=exp, legend=False, figdir=figdir,
axis=[['time', 'time (s)'],
['cu_num', "number of concurrent CUs in '%s'" % exp]])
# fig.show()
#
# # inverse axis, use logar. scale for time
# fig, _ = rpu.frame_plot(plot_frames, logx=False, logy=True, title=exp,
# title=exp, legend=False, figdir=figdir,
# axis=[['cu_num', 'number of concurrent CUs'],
def preprocess(sid):
session_dir = os.path.join(PICKLE_DIR, sid)
if os.path.isdir(session_dir):
report.warn("Session dir '%s' already exists, skipping session." % session_dir)
return
try:
sid_profiles = find_profiles(sid)
print sid_profiles
report.info("Combining profiles for session: %s.\n" % sid)
combined_profiles = rpu.combine_profiles(sid_profiles)
uids = set()
for p in combined_profiles:
uids.add(p['uid'])
report.info("Converting profiles to frames for session: %s.\n" % sid)
frames = rpu.prof2frame(combined_profiles)
report.info("Head of Combined DF for session %s:\n" % sid)
print frames.entity.unique()
ses_prof_fr, pilot_prof_fr, cu_prof_fr = rpu.split_frame(frames)
report.info("Head of Session DF for session %s:\n" % sid)
ses_prof_fr.insert(0, 'sid', sid)
print ses_prof_fr.head()
report.info("Head of Pilot DF for session %s:\n" % sid)
pilot_prof_fr.insert(0, 'sid', sid)
print pilot_prof_fr.head()
report.info("Head of CU DF for session %s:\n" % sid)
rpu.add_states(cu_prof_fr)
print cu_prof_fr.head()
report.info("Head of CU DF for session %s (after states added):\n" % sid)
rpu.add_info(cu_prof_fr)
print cu_prof_fr.head()
report.info("Head of CU DF for session %s (after info added):\n" % sid)
print cu_prof_fr.head()
report.info("Head of CU DF for session %s (after concurrency added):\n" % sid)
# Add a column with the number of concurrent populating the database
spec = {
'in': [
{'state': rps.STAGING_INPUT, 'event': 'advance'}
],
'out' : [
{'state':rps.AGENT_STAGING_INPUT_PENDING, 'event': 'advance'},
{'state':rps.FAILED, 'event': 'advance'},
{'state':rps.CANCELED, 'event': 'advance'}
]
}
rpu.add_concurrency (cu_prof_fr, 'cc_populating', spec)
# Add a column with the number of concurrent staging in units
spec = {
'in': [
{'state': rps.AGENT_STAGING_INPUT, 'event': 'advance'}
],
'out' : [
{'state':rps.ALLOCATING_PENDING, 'event': 'advance'},
{'state':rps.FAILED, 'event': 'advance'},
{'state':rps.CANCELED, 'event': 'advance'}
]
}
rpu.add_concurrency (cu_prof_fr, 'cc_stage_in', spec)
# Add a column with the number of concurrent scheduling units
spec = {
'in': [
{'state': rps.ALLOCATING, 'event': 'advance'}
],
'out' : [
{'state':rps.EXECUTING_PENDING, 'event': 'advance'},
{'state':rps.FAILED, 'event': 'advance'},
{'state':rps.CANCELED, 'event': 'advance'}
]
}
rpu.add_concurrency (cu_prof_fr, 'cc_sched', spec)
# Add a column with the number of concurrent Executing units
spec = {
'in': [
{'state': rps.EXECUTING, 'event': 'advance'}
],
'out' : [
{'state':rps.AGENT_STAGING_OUTPUT_PENDING, 'event': 'advance'},
{'state':rps.FAILED, 'event': 'advance'},
{'state':rps.CANCELED, 'event': 'advance'}
]
}
rpu.add_concurrency (cu_prof_fr, 'cc_exec', spec)
# Add a column with the number of concurrent Executing units
spec = {
'in': [
{'state': rps.AGENT_STAGING_OUTPUT, 'event': 'advance'}
],
'out' : [
{'state':rps.PENDING_OUTPUT_STAGING, 'event': 'advance'},
{'state':rps.FAILED, 'event': 'advance'},
{'state':rps.CANCELED, 'event': 'advance'}
]
}
rpu.add_concurrency (cu_prof_fr, 'cc_stage_out', spec)
print cu_prof_fr.head()
report.info("Head of CU DF for session %s (after sid added):\n" % sid)
cu_prof_fr.insert(0, 'sid', sid)
print cu_prof_fr.head()
report.info("CU DF columns for session %s:\n" % sid)
print cu_prof_fr['info'].unique()
# transpose
tr_cu_prof_fr = rpu.get_info_df(cu_prof_fr)
tr_cu_prof_fr.insert(0, 'sid', sid)
report.info("Head of Transposed CU DF for session %s:\n" % sid)
print tr_cu_prof_fr.head()
ses_info_fr, pilot_info_fr, unit_info_fr = json2frame(db=None, sid=sid)
report.info("Head of json Docs for session %s:\n" % sid)
print ses_info_fr.head()
except:
report.error("Failed to pre-process data for session %s" % sid)
return
report.header("Writing dataframes to disk.\n")
try:
os.mkdir(session_dir)
ses_info_fr.to_pickle(os.path.join(session_dir, 'session_info.pkl'))
pilot_info_fr.to_pickle(os.path.join(session_dir, 'pilot_info.pkl'))
unit_info_fr.to_pickle(os.path.join(session_dir, 'unit_info.pkl'))
ses_prof_fr.to_pickle(os.path.join(session_dir, 'session_prof.pkl'))
pilot_prof_fr.to_pickle(os.path.join(session_dir, 'pilot_prof.pkl'))
cu_prof_fr.to_pickle(os.path.join(session_dir, 'unit_prof.pkl'))
tr_cu_prof_fr.to_pickle(os.path.join(session_dir, 'tr_unit_prof.pkl'))
except:
report.error("Failed to write data")
return
def plot(sids, value, label='', paper=False):
colors = [cmap(i) for i in np.linspace(0, 1, len(sids))]
labels = []
first = True
for sid in sids:
if sid.startswith('rp.session'):
rp = True
else:
rp = False
session_dir = os.path.join(PICKLE_DIR, sid)
unit_info_df = pd.read_pickle(
os.path.join(session_dir, 'unit_info.pkl'))
pilot_info_df = pd.read_pickle(
os.path.join(session_dir, 'pilot_info.pkl'))
unit_prof_df = pd.read_pickle(
os.path.join(session_dir, 'unit_prof.pkl'))
session_info_df = pd.read_pickle(
os.path.join(session_dir, 'session_info.pkl'))
# Legend info
info = session_info_df.loc[sid]
if rp:
# For this call assume that there is only one pilot per session
resources = get_resources(unit_info_df, pilot_info_df, sid)
assert len(resources) == 1
resource_label = resources.values()[0]
else:
resource_label = 'bogus'
# Get only the entries for this session
#uf = unit_prof_df[unit_prof_df['sid'] == sid]
# We sort the units based on the order they arrived at the agent
#ufs = uf.sort('awo_get_u_pend')
cores = info['metadata.effective_cores']
#cores = 32
if value == 'cc_fork':
spec = {
'in': [{
'info': 'aec_start_script'
}],
'out': [{
'info': 'aec_after_exec'
}]
}
rpu.add_concurrency(unit_prof_df, 'cc_fork', spec)
elif value == 'cc_exit':
spec = {
'in': [{
'info': 'aec_after_exec'
}],
'out': [
{
'state': rps.AGENT_STAGING_OUTPUT_PENDING,
'event': 'advance'
},
]
}
rpu.add_concurrency(unit_prof_df, 'cc_exit', spec)
df = unit_prof_df[(unit_prof_df[value] >= 0) &
#(unit_prof_df.event == 'advance') &
(unit_prof_df.sid == sid)][['time', value]]
df.columns = ['time', cores]
df['time'] -= df['time'].min()
if first:
df_all = df
else:
df_all = pd.merge(df_all, df, on='time', how='outer')
#labels.append("Cores: %d" % cores)
# labels.append("%d" % cores)
#labels.append("%d - %s" % (cores, 'RP' if rp else 'ORTE'))
#labels.append(sid[-4:])
labels.append("%d" % info['metadata.cu_runtime'])
first = False
df_all.set_index('time', inplace=True)
print df_all.head()
#df_all.plot(colormap='Paired')
#df_all.plot(drawstyle='steps-post')
#ax = df_all.plot(drawstyle='steps-pre', fontsize=TICK_FONTSIZE, linewidth=LINEWIDTH, colors=colors)
ax = df_all.plot(fontsize=TICK_FONTSIZE,
linewidth=LINEWIDTH,
colors=colors)
# Vertial reference
#x_ref = info['metadata.generations'] * info['metadata.cu_runtime']
#mp.pyplot.plot((x_ref, x_ref),(0, 1000), 'k--')
#labels.append("Optimal")
location = 'upper right'
legend = mp.pyplot.legend(labels,
loc=location,
fontsize=LEGEND_FONTSIZE,
labelspacing=0)
legend.get_frame().set_linewidth(BORDERWIDTH)
if not paper:
mp.pyplot.title(
"Concurrent number of CUs in stage '%s'.\n"
"%d generations of a variable number of 'concurrent' CUs of %d core(s) with a %ss payload on a variable core pilot on %s.\n"
"Constant number of %d sub-agent with %d ExecWorker(s) each.\n"
"RP: %s - RS: %s - RU: %s" %
(value, info['metadata.generations'], info['metadata.cu_cores'],
info['metadata.cu_runtime'], resource_label,
info['metadata.num_sub_agents'],
info['metadata.num_exec_instances_per_sub_agent'],
info['metadata.radical_stack.rp'],
info['metadata.radical_stack.rs'],
info['metadata.radical_stack.ru']),
fontsize=TITLE_FONTSIZE)
mp.pyplot.xlabel("Time (s)", fontsize=LABEL_FONTSIZE)
mp.pyplot.ylabel("\# Concurrent Units", fontsize=LABEL_FONTSIZE)
# mp.pyplot.ylim(0, 200)
mp.pyplot.ylim(-50, )
mp.pyplot.xlim(0, 600)
#ax.get_xaxis().set_ticks([])
print dir(ax)
[i.set_linewidth(BORDERWIDTH) for i in ax.spines.itervalues()]
plt.setp(ax.yaxis.get_ticklines(), 'markeredgewidth', BORDERWIDTH)
plt.setp(ax.xaxis.get_ticklines(), 'markeredgewidth', BORDERWIDTH)
# width = 3.487
width = 3.3
height = width / 1.618
# height = 2.5
fig = mp.pyplot.gcf()
fig.set_size_inches(width, height)
# fig.subplots_adjust(left=0, right=1, top=1, bottom=1)
# fig.tight_layout(w_pad=0.0, h_pad=0.0, pad=0.1)
fig.tight_layout(pad=0.1)
mp.pyplot.savefig('plot_concurrency.pdf')
mp.pyplot.close()
