Closed okilic1 closed 8 months ago
okilic1
commented
11 months ago @andre-merzky you can find both script and the sandbox in following directories Script: https://github.com/okilic1/asyncExecution/blob/main/figures/resource_utilization-summit-Adaptive.ipynb Sandbox: https://github.com/okilic1/asyncExecution/tree/main/rawdata
andre-merzky
commented
8 months ago Ozgur - this standalone version (which is a copy of the notebook code) seems to do what is expected: it results in three valid sessions, and the entities are sorted as expected. Gan you give this a try, please?
#!/usr/bin/env python3
import os
import tarfile
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.ticker as mticker
import radical.utils as ru
import radical.pilot as rp
import radical.entk as re
import radical.analytics as ra
plt.style.use(ra.get_mplstyle('radical_mpl'))
from IPython.display import display, HTML
mpl.rcParams['figure.dpi']= 600
metrics = [
['Bootstrap', ['boot', 'setup_1'] , '#c6dbef'],
['Warmup' , ['warm' ] , '#f0f0f0'],
['Schedule' , ['exec_queue','exec_prep', 'unschedule'] , '#c994c7'],
['Exec RP' , ['exec_rp', 'exec_sh', 'term_sh', 'term_rp'], '#fdbb84'],
['Exec Cmd' , ['exec_cmd'] , '#e31a1c'],
['Cooldown' , ['drain'] , '#addd8e']
]
metrics = [
['Bootstrap', ['boot', 'setup_1'] , '#ffffff'],
['Warmup' , ['warm' ] , '#ffffff'],
['Schedule' , ['exec_queue','exec_prep', 'unschedule'] , '#ffffff'],
['Exec RP' , ['exec_rp', 'exec_sh', 'term_sh', 'term_rp'], '#ffffff'],
['Exec Cmd' , ['exec_cmd'] , '#839dc9'],
['Cooldown' , ['drain'] , '#ffffff']
]
## Weak Scaling
#os.environ['RADICAL_PILOT_DBURL'] = 'mongodb://pascuzzi:slriUTnc7NrM8o5t@95.217.193.116/lavinlie'
### Adaptive Experiment
# rp.session.login3.okilic1.019534.0004 #=> Sync --debug
# rp.session.login3.okilic1.019534.0007 #=> Workload Async --debug
# rp.session.login3.okilic1.019534.0010 #=> Task Async --debug
# rp.session.login3.okilic1.019534.0012 #=> Sync --Full
# rp.session.login3.okilic1.019534.0013 #=> Workload Async --Full
# rp.session.login3.okilic1.019534.0014 #=> Task Async --Full
sids = ['rp.session.login3.okilic1.019534.0004',#, #=> Sync --debug
'rp.session.login3.okilic1.019534.0007', #=> Workload Async --debug
'rp.session.login3.okilic1.019534.0010', #=> Task Async --debug
'rp.session.login3.okilic1.019534.0012', #=> Sync --Full
'rp.session.login3.okilic1.019534.0013', #=> Workload Async --Full
'rp.session.login3.okilic1.019534.0014'] #=> Task Async --Full
#sids = ['rp.session.login2.okilic1.019489.0011', # dg2-asyn
# 'rp.session.login4.okilic1.019489.0010'] # dg1-asyn
#sids = ['rp.session.login4.okilic1.019489.0010', # dg1-asyn
# 'rp.session.login2.okilic1.019489.0011', # dg2-asyn
# 'rp.session.login4.okilic1.019489.0010', # dg1-asyn
# 'rp.session.login2.okilic1.019489.0011'] # dg2-asyn
sdir = '../rawdata/'
sessions = [sdir + s for s in sids]
for sid in sids:
sp = sdir+sid+'.tgz'
tar = tarfile.open(sp, mode='r:gz')
tar.extractall(path=sdir)
tar.close()
ss = {}
for sid in sids:
sp = sdir + sid
ss[sid] = {'s': ra.Session(sp, 'radical.pilot')}
ss[sid].update({'p': ss[sid]['s'].filter(etype='pilot', inplace=False),
't': ss[sid]['s'].filter(etype='task' , inplace=False)})
print()
print(sid, sp, ss[sid]['s'], ss[sid]['p'], ss[sid]['t'])
print(ss[sid]['s'])
print(ss[sid]['p'])
print(ss[sid]['t'])
# print([e.uid for e in ss[sid]['s'].get()])
print([e.uid for e in ss[sid]['p'].get()])
print([e.uid for e in ss[sid]['t'].get()])$ radical-stack
1698242234.548 : radical.analytics : 287581 : 140188404437056 : INFO : radical.analytics version: 1.34.0-v1.34.0@HEAD-detached-at-v1.34.0
python : /home/merzky/radical/radical.analytics.devel/ve3/bin/python3
pythonpath :
version : 3.11.5
virtualenv : /home/merzky/radical/radical.analytics.devel/ve3
radical.analytics : 1.34.0-v1.34.0@HEAD-detached-at-v1.34.0
radical.entk : 1.37.0
radical.gtod : 1.20.1
radical.pilot : 1.37.0
radical.saga : 1.36.0
radical.utils : 1.33.0Hi Andre, Filtering works, and I can get a filtered list of tasks when I change 't': ss[sid]['s'].filter(etype='task' , inplace=False)}) with 't': ss[sid]['s'].filter(uid=[pat1, pat2] , inplace=False)}) after setting the pat1 and pat2. However, I cannot get data using the filtered dictionary. Here is the code:
#!/usr/bin/env python3
import os
import tarfile
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.ticker as mticker
import radical.utils as ru
import radical.pilot as rp
import radical.entk as re
import radical.analytics as ra
import re as re1
plt.style.use(ra.get_mplstyle('radical_mpl'))
from IPython.display import display, HTML
mpl.rcParams['figure.dpi']= 600
metrics = [
['Bootstrap', ['boot', 'setup_1'] , '#c6dbef'],
['Warmup' , ['warm' ] , '#f0f0f0'],
['Schedule' , ['exec_queue','exec_prep', 'unschedule'] , '#c994c7'],
['Exec RP' , ['exec_rp', 'exec_sh', 'term_sh', 'term_rp'], '#fdbb84'],
['Exec Cmd' , ['exec_cmd'] , '#e31a1c'],
['Cooldown' , ['drain'] , '#addd8e']
]
metrics = [
['Bootstrap', ['boot', 'setup_1'] , '#ffffff'],
['Warmup' , ['warm' ] , '#ffffff'],
['Schedule' , ['exec_queue','exec_prep', 'unschedule'] , '#ffffff'],
['Exec RP' , ['exec_rp', 'exec_sh', 'term_sh', 'term_rp'], '#ffffff'],
['Exec Cmd' , ['exec_cmd'] , '#839dc9'],
['Cooldown' , ['drain'] , '#ffffff']
]
## Weak Scaling
#os.environ['RADICAL_PILOT_DBURL'] = 'mongodb://pascuzzi:slriUTnc7NrM8o5t@95.217.193.116/lavinlie'
### Adaptive Experiment
# rp.session.login3.okilic1.019534.0004 #=> Sync --debug
# rp.session.login3.okilic1.019534.0007 #=> Workload Async --debug
# rp.session.login3.okilic1.019534.0010 #=> Task Async --debug
# rp.session.login3.okilic1.019534.0012 #=> Sync --Full
# rp.session.login3.okilic1.019534.0013 #=> Workload Async --Full
# rp.session.login3.okilic1.019534.0014 #=> Task Async --Full
sids = ['rp.session.login3.okilic1.019534.0004']#, #=> Sync --debug
# 'rp.session.login3.okilic1.019534.0007', #=> Workload Async --debug
# 'rp.session.login3.okilic1.019534.0010', #=> Task Async --debug
#
# 'rp.session.login3.okilic1.019534.0012', #=> Sync --Full
# 'rp.session.login3.okilic1.019534.0013', #=> Workload Async --Full
# 'rp.session.login3.okilic1.019534.0014'] #=> Task Async --Full
#sids = ['rp.session.login2.okilic1.019489.0011', # dg2-asyn
# 'rp.session.login4.okilic1.019489.0010'] # dg1-asyn
#sids = ['rp.session.login4.okilic1.019489.0010', # dg1-asyn
# 'rp.session.login2.okilic1.019489.0011', # dg2-asyn
# 'rp.session.login4.okilic1.019489.0010', # dg1-asyn
# 'rp.session.login2.okilic1.019489.0011'] # dg2-asyn
sdir = '../rawdata/'
sessions = [sdir + s for s in sids]
for sid in sids:
sp = sdir+sid+'.tgz'
tar = tarfile.open(sp, mode='r:gz')
tar.extractall(path=sdir)
tar.close()
pat1 = re1.compile(r'^t10\..*0$')
pat2 = re1.compile(r'^t4\..*0$')
ss = {}
for sid in sids:
print("THIS IS SID: ", sid)
sp = sdir + sid
ss[sid] = {'s': ra.Session(sp, 'radical.pilot')}
ss[sid].update({'p': ss[sid]['s'].filter(etype='pilot', inplace=False),
#'t': ss[sid]['s'].filter(uid=[pat1, pat2] , inplace=False)})
't': ss[sid]['s'].filter(etype='task' , inplace=False)})
print()
print(sid, sp, ss[sid]['s'], ss[sid]['p'], ss[sid]['t'])
print(ss[sid]['s'])
print(ss[sid]['p'])
print(ss[sid]['t'])
# print([e.uid for e in ss[sid]['s'].get()])
print([e.uid for e in ss[sid]['p'].get()])
print([e.uid for e in ss[sid]['t'].get()])
#This part I copied
#exp = ss["rp.session.login3.okilic1.019534.0014"]
exp = ra.Experiment(sessions, stype='radical.pilot')
p_zeros = ra.get_pilots_zeros(exp)
# Type of resource we want to plot: cpu or gpu
rtypes=['cpu', 'gpu']
print("Metrics: ", metrics)
print("Types: ", rtypes)
provided, consumed, stats_abs, stats_rel, info = exp.utilization(metrics=metrics, rtype=rtypes[1])
print("provided: ", provided)
print("consumed: ", consumed)
print("stats_abs: ", stats_abs)
print("stats_rel: ", stats_rel)
print("info: ", info)
#for s in sessions:
# print("path: ",os.path.basename(s))
# sessions you want to plot
splot = [os.path.basename(s) for s in sessions]
nsids = len(splot)
# Create figure and 1 subplot for each session
# Use LaTeX document page size (see RA Plotting Chapter)
fwidth, fhight = ra.get_plotsize(300, subplots=(1, 1))
fig, axarr = plt.subplots(2, 1, sharex='col', figsize=(fwidth, fhight))
# Avoid overlapping between Y-axes ticks and sub-figures
plt.subplots_adjust(wspace=0.45)
# Generate the subplots with labels
legend = None
for k, rtype in enumerate(rtypes):
_, consumed, _, _, _ = exp.utilization(metrics=metrics, rtype=rtype)
#print("consumed: ", consumed)
j = 'a'
#print("j: ",j)
#print("splot3: ", splot[3:])
#print("splot: ", splot)
for i, sid in enumerate(splot[0:]):
# we know we have only 1 pilot
#pid = ss[sid]['t'].list('uid')[0]
pid = ss[sid]['p'].list('uid')[0]
print ("PID:: ",pid)
print ("p_zeroes: ", p_zeros)
# Plot legend, patched, X and Y axes objects
legend, patches, x, y = ra.get_plot_utilization(metrics, consumed, p_zeros[sid][pid], sid)
# Place all the patches, one for each metric, on the axes
for patch in patches:
axarr[k].add_patch(patch)
# Title of the plot. Facultative, requires info about session (see RA
# Info Chapter). We set the title only on the first raw of plots
# if rtype == 'cpu':
# # axarr[k][i].set_title('%s Tasks - %s Nodes' % (ss[sid]['ntask'],
# # int(ss[sid]['nnodes'])))
# axarr[k].set_title('%s Tasks - %s Nodes' % (ss[sid]['ntask'],
# 16))
# Format axes
# axarr[k][i].set_xlim([x['min'], x['max']])
# axarr[k].set_xlim([0, 2000])
# if i == 0:
# axarr[k].set_xlim([0, 1800])
# if i == 1:
# axarr[k].set_xlim([0, 1400])
axarr[k].set_xlim([0, 300])
axarr[k].set_ylim([y['min'], int(y['max'])])
# axarr[k][i].set_ylim([0, 680])
print('work-flow run-time (%s, %s): %f' % (str(k), str(i), x['max']))
axarr[k].yaxis.set_major_locator(mticker.MaxNLocator(5))
axarr[k].xaxis.set_major_locator(mticker.MaxNLocator(7))
axarr[k].tick_params(axis='x', labelsize=8)
axarr[k].tick_params(axis='y', labelsize=8)
# axarr[k].set_xticklabels(['0', '300', '900', '1200', '1500', '1800']) # ddmd-seq
# axarr[k].set_xticklabels(['0', '300', '900', '1200', '1500', '1800']) # ddmd-async
for axis in ['top','bottom','left','right']:
axarr[k].spines[axis].set_linewidth(0.5)
axarr[k].tick_params(width=0.5)
if rtype == 'cpu':
# Specific to Summit when using SMT=4 (default)
axarr[k].yaxis.set_major_formatter(
mticker.FuncFormatter(lambda z, pos: int(z/4)))
# axarr[k][i].set_ylabel('CPU\nCores', fontsize=6, labelpad=4)
# plot axis labels
if k == 0: #and (i == 0 or i==2):
axarr[k].set_ylabel('CPU Cores', fontsize=10, labelpad=3)
if k == 1: #and (i == 0 or i==2):
axarr[k].set_ylabel('GPUs', fontsize=10, labelpad=6)
# Set x labels to letters for references in the paper.
# Set them only for the bottom-most subplot
# if rtype == 'gpu':
# axarr[k][i].set_xlabel('(%s)' % j, labelpad=10)
# if k == 1 and i == 0:
# axarr[k][i].set_ylabel('GPUs', fontsize=6, labelpad=7)
if k == 1:
axarr[k].set_xlabel('Total Time to Execution [s]', fontsize=10, labelpad=4)
# update session id and raw identifier letter
j = chr(ord(j) + 1)
break
# Add legend
# fig.legend(legend, [m[0] for m in metrics],
# loc='upper center', bbox_to_anchor=(0.5, 1.25), ncol=6)
# Add axes labels
# fig.text(0.22, -0.15, 'Workflow Run-Time [s]', fontsize=6)
# fig.text(0.63, -0.15, 'Workflow Run-Time [s]', fontsize=6)
fig.savefig('Filtered.pdf', bbox_inches="tight")
Hey @okilic1 - that is a different issue than what is covered in this one, so you may want to open a new ticket. But either way, please try https://github.com/radical-cybertools/radical.analytics/pull/184 which should address that problem.
okilic1
commented
8 months ago I tested the filtering works. I will open a new ticket for #184
To allow plotting graphs based on the types of the task via either color coding or filtering.