def gen_plot_data(data_file, is_tgs_only, x_label):
from scripts.utils import load_csv
raw_data = load_csv(data_file)
duplicates = set()
plots = dict()
perf_fig = dict()
for k in raw_data:
parse_entry_info(k, is_tgs_only)
# Handle repeated data
key = (k['Precision'], k['stencil_name'],
k['LIKWID performance counter'], k['mwdt'], k['method'],
k['tgsl'], k['Global NX'], k['OpenMP Threads'])
if key not in duplicates:
duplicates.add(key)
else:
print("Repeated result at: %s" % (k['file_name']))
continue
init_plot_entry(plots, k)
append_meas_data(plots, k)
append_perf_data(perf_fig, k, x_label)
del raw_data
sort_perf_fig(perf_fig)
sort_meas_fig(plots)
return plots, perf_fig
def gen_plot_data(data_file, is_tgs_only, x_label):
from scripts.utils import load_csv
raw_data = load_csv(data_file)
duplicates = set()
plots = dict()
perf_fig = dict()
for k in raw_data:
parse_entry_info(k, is_tgs_only)
# Handle repeated data
key = (
k["Precision"],
k["stencil_name"],
k["LIKWID performance counter"],
k["mwdt"],
k["method"],
k["tgsl"],
k["Global NX"],
k["OpenMP Threads"],
)
if key not in duplicates:
duplicates.add(key)
else:
print ("Repeated result at: %s" % (k["file_name"]))
continue
init_plot_entry(plots, k)
append_meas_data(plots, k)
append_perf_data(perf_fig, k, x_label)
del raw_data
sort_perf_fig(perf_fig)
sort_meas_fig(plots)
return plots, perf_fig
def main():
import sys
from scripts.utils import get_stencil_num, load_csv
from collections import OrderedDict
raw_data = load_csv(sys.argv[1])
req_fields = [('MStencil/s MAX', float), ('Precision', int),
('Global NX', int), ('Number of time steps', int),
('Number of tests', int)]
hw_ctr_fields = {
'': [],
'TLB': [('L1 DTLB miss rate sum', float)],
'DATA': [('Load to Store ratio avg', float)],
'L2': [('L2 data volume sum', float)],
'L3': [('L3 data volume sum', float)],
'MEM': [('Total Memory Transfer', float),
('Sustained Memory BW', float)],
'ENERGY': [('Energy', float), ('Energy DRAM', float), ('Power', float),
('Power DRAM', float)]
}
duplicates = set()
meas_figs = dict()
perf_fig = dict()
for k in raw_data:
# get processor name from the file names
if (k['OpenMP Threads'] != ''):
if (int(k['OpenMP Threads']) == 10):
machine_name = 'ivb10'
elif (int(k['OpenMP Threads']) == 18):
machine_name = 'hw18'
# Use single field to represent the performance
if 'Total RANK0 MStencil/s MAX' in k.keys():
if (k['Total RANK0 MStencil/s MAX'] != ''):
k['MStencil/s MAX'] = k['MWD main-loop RANK0 MStencil/s MAX']
# temporary for deprecated format
if 'RANK0 MStencil/s MAX' in k.keys():
if k['RANK0 MStencil/s MAX'] != '':
k['MStencil/s MAX'] = k['RANK0 MStencil/s MAX']
# add stencil operator
k['stencil'] = get_stencil_num(k)
if k['stencil'] == 0:
k['stencil_name'] = '25_pt_const'
elif k['stencil'] == 1:
k['stencil_name'] = '7_pt_const'
elif k['stencil'] == 4:
k['stencil_name'] = '25_pt_var'
elif k['stencil'] == 5:
k['stencil_name'] = '7_pt_var'
elif k['stencil'] == 6:
k['stencil_name'] = 'solar'
# add the approach
if (k['Time stepper orig name'] == 'Spatial Blocking'):
k['method'] = 'Spt.blk.'
elif (k['Time stepper orig name'] in ['PLUTO', 'Pochoir']):
k['method'] = k['Time stepper orig name']
elif (k['Time stepper orig name'] == 'Diamond'):
if ('_tgs1_' in k['file_name']):
k['method'] = '1WD'
else:
k['method'] = 'MWD'
else:
print("ERROR: Unknow time stepper")
raise
# add mwd type
k['mwdt'] = 'none'
if (k['method'] == 'MWD'):
mwd = k['Wavefront parallel strategy'].lower()
if ('fixed' in mwd) and ('relaxed' in mwd):
k['mwdt'] = 'fers'
elif ('fixed' in mwd):
k['mwdt'] = 'fe'
elif ('relaxed' in mwd):
k['mwdt'] = 'rs'
elif ('wavefront' in mwd):
k['mwdt'] = 'block'
# add precision information
p = 1 if k['Precision'] in 'DP' else 0
k['Precision'] = p
# TLB measurement for LIKWID 4
if 'L1 DTLB load miss rate avg' in k.keys():
if k['L1 DTLB load miss rate avg'] != '':
hw_ctr_fields['TLB'] = [('L1 DTLB load miss rate avg', float)]
hw_ctr_labels['TLB'] = [('L1 DTLB load miss rate avg', 'tlb_',
'tlb')]
entry = {}
# parse the general fileds' format
for f in req_fields + hw_ctr_fields[k['LIKWID performance counter']]:
try:
entry[f[0]] = map(f[1], [k[f[0]]])[0]
except:
print(
"ERROR: results entry missing essential data at file:%s" %
(k['file_name']))
print f[0]
print k
return
#find repeated data
key = (entry['Precision'], k['stencil_name'],
k['LIKWID performance counter'], k['mwdt'], k['method'],
entry['Global NX'])
if key not in duplicates:
duplicates.add(key)
else:
print("Repeated result at: %s" % (k['file_name']))
continue
# Initialize plot entry if does not exist for current data entry
# for m,n in entry.iteritems(): print m,n
measure_list = [
'n', 'perf', 'total energy', 'tlb', 'mem bw', 'l2 bw', 'l3 bw',
'mem vol', 'l2 vol', 'l3 vol', 'data', 'tgs', 'thx', 'thy', 'thz',
'blk size', 'diam width', 'bs_z'
]
plot_key = (entry['Precision'], k['stencil_name'],
k['LIKWID performance counter'])
line_key = (k['mwdt'], k['method'])
if plot_key not in meas_figs.keys():
meas_figs[plot_key] = {}
if line_key not in meas_figs[plot_key].keys():
meas_figs[plot_key][line_key] = {meas: [] for meas in measure_list}
# append the measurement data
meas_figs[plot_key][line_key]['n'].append(entry['Global NX'])
# meas_figs[plot_key][line_key]['perf'].append(entry['MStencil/s MAX']/1e3)
N = entry['Global NX']**3 * entry['Number of time steps'] * entry[
'Number of tests'] / 1e9
# Memory
if k['LIKWID performance counter'] == 'MEM':
meas_figs[plot_key][line_key]['mem bw'].append(
entry['Sustained Memory BW'] / 1e3)
meas_figs[plot_key][line_key]['mem vol'].append(
entry['Total Memory Transfer'] / N)
# Energy
elif k['LIKWID performance counter'] == 'ENERGY':
entry['cpu energy pj/lup'] = entry['Energy'] / N
entry['dram energy pj/lup'] = entry['Energy DRAM'] / N
entry['total energy pj/lup'] = entry['cpu energy pj/lup'] + entry[
'dram energy pj/lup']
if (entry['total energy pj/lup'] < 3e3):
# entry['total energy pj/lup'] = 0
meas_figs[plot_key][line_key]['total energy'].append(
entry['total energy pj/lup'])
else:
del meas_figs[plot_key][line_key]['n'][-1]
# TLB
elif k['LIKWID performance counter'] == 'TLB':
meas_figs[plot_key][line_key]['tlb'].append(
entry[hw_ctr_fields['TLB'][0][0]])
# L2
elif k['LIKWID performance counter'] == 'L2':
meas_figs[plot_key][line_key]['l2 vol'].append(
entry['L2 data volume sum'] / N)
#L3
elif k['LIKWID performance counter'] == 'L3':
meas_figs[plot_key][line_key]['l3 vol'].append(
entry['L3 data volume sum'] / N)
#CPU
elif k['LIKWID performance counter'] == 'DATA':
meas_figs[plot_key][line_key]['data'].append(
entry['Load to Store ratio avg'])
#Diamond tiling data
if (k['method'] == '1WD' or k['method'] == 'MWD'):
meas_figs[plot_key][line_key]['diam width'].append(
int(k['Intra-diamond width']))
meas_figs[plot_key][line_key]['tgs'].append(
int(k['Thread group size']))
meas_figs[plot_key][line_key]['thx'].append(
int(k['Threads along x-axis']))
meas_figs[plot_key][line_key]['thy'].append(
int(k['Threads along y-axis']))
meas_figs[plot_key][line_key]['thz'].append(
int(k['Threads along z-axis']))
meas_figs[plot_key][line_key]['blk size'].append(
int(k['Total cache block size (kiB)']) / 1024.0)
meas_figs[plot_key][line_key]['bs_z'].append(
int(k['Multi-wavefront updates']))
# append the performance data
plot_key = (entry['Precision'], k['stencil_name'])
line_key = (k['mwdt'], k['method'])
if plot_key not in perf_fig.keys(): # figure
perf_fig[plot_key] = dict()
perf_line = perf_fig[plot_key]
if line_key not in perf_line.keys(): # line
perf_line[line_key] = dict()
perf_point = perf_line[line_key]
nx = entry['Global NX']
if nx not in perf_point.keys(): # points
perf_point[nx] = [entry['MStencil/s MAX'] / 1e3]
else:
perf_point[nx].append(entry['MStencil/s MAX'] / 1e3)
del raw_data
#sort performance results
for k, v in perf_fig.iteritems():
for k2, v2 in perf_fig[k].iteritems():
perf_line = perf_fig[k][k2]
perf_fig[k][k2] = OrderedDict(
sorted(perf_fig[k][k2].iteritems(), key=lambda x: x[0]))
# for k,v in perf_fig.iteritems():
# print(k, "##########")
# for k2,v2 in perf_fig[k].iteritems():
# print(k2,v2)
#sort the plot lines
for p in meas_figs:
for l in meas_figs[p]:
pl = meas_figs[p][l]
#remove unused fields
empty = []
for key, val in pl.iteritems():
if (val == []):
empty.append(key)
for key in empty:
del pl[key]
lines = []
[lines.append(pl[val]) for val in measure_list if val in pl.keys()]
lines = sorted(zip(*lines))
idx = 0
for val in measure_list:
if (val in pl.keys()):
if (pl[val]):
pl[val] = [x[idx] for x in lines]
idx = idx + 1
# for m,n in meas_figs.iteritems():
# print "##############",m
# for i,j in n.iteritems():
# print i,j
plot_all(perf_fig, meas_figs, machine_name)
def main():
import sys
from scripts.utils import get_stencil_num, load_csv
from collections import OrderedDict
raw_data = load_csv(sys.argv[1])
req_fields = [('MStencil/s MAX', float), ('Precision', int), ('Global NX', int), ('Number of time steps', int), ('Number of tests', int)]
hw_ctr_fields = {
'':[],
'TLB':[('L1 DTLB miss rate sum', float)],
'DATA':[('Load to Store ratio avg', float)],
'L2':[('L2 data volume sum', float)],
'L3':[('L3 data volume sum', float)],
'MEM':[('Total Memory Transfer', float),('Sustained Memory BW', float)],
'ENERGY':[('Energy', float), ('Energy DRAM', float), ('Power',float), ('Power DRAM', float)]}
duplicates = set()
meas_figs = dict()
perf_fig = dict()
for k in raw_data:
# get processor name from the file names
if(k['OpenMP Threads']!=''):
if(int(k['OpenMP Threads']) == 10):
machine_name = 'ivb10'
elif(int(k['OpenMP Threads']) == 18):
machine_name = 'hw18'
# Use single field to represent the performance
if 'Total RANK0 MStencil/s MAX' in k.keys():
if(k['Total RANK0 MStencil/s MAX']!=''):
k['MStencil/s MAX'] = k['MWD main-loop RANK0 MStencil/s MAX']
# temporary for deprecated format
if 'RANK0 MStencil/s MAX' in k.keys():
if k['RANK0 MStencil/s MAX']!='':
k['MStencil/s MAX'] = k['RANK0 MStencil/s MAX']
# add stencil operator
k['stencil'] = get_stencil_num(k)
if k['stencil'] == 0:
k['stencil_name'] = '25_pt_const'
elif k['stencil'] == 1:
k['stencil_name'] = '7_pt_const'
elif k['stencil'] == 4:
k['stencil_name'] = '25_pt_var'
elif k['stencil'] == 5:
k['stencil_name'] = '7_pt_var'
elif k['stencil'] == 6:
k['stencil_name'] = 'solar'
# add the approach
if(k['Time stepper orig name'] == 'Spatial Blocking'):
k['method'] = 'Spt.blk.'
elif(k['Time stepper orig name'] in ['PLUTO', 'Pochoir']):
k['method'] = k['Time stepper orig name']
elif(k['Time stepper orig name'] == 'Diamond'):
if('_tgs1_' in k['file_name']):
k['method'] = '1WD'
else:
k['method'] = 'MWD'
else:
print("ERROR: Unknow time stepper")
raise
# add mwd type
k['mwdt']='none'
if(k['method'] == 'MWD'):
mwd = k['Wavefront parallel strategy'].lower()
if('fixed' in mwd) and ('relaxed' in mwd):
k['mwdt'] = 'fers'
elif('fixed' in mwd):
k['mwdt'] = 'fe'
elif('relaxed' in mwd):
k['mwdt'] = 'rs'
elif('wavefront' in mwd):
k['mwdt'] = 'block'
# add precision information
p = 1 if k['Precision'] in 'DP' else 0
k['Precision'] = p
# TLB measurement for LIKWID 4
if 'L1 DTLB load miss rate avg' in k.keys():
if k['L1 DTLB load miss rate avg']!='':
hw_ctr_fields['TLB'] = [('L1 DTLB load miss rate avg', float)]
hw_ctr_labels['TLB'] = [('L1 DTLB load miss rate avg', 'tlb_', 'tlb')]
entry = {}
# parse the general fileds' format
for f in req_fields + hw_ctr_fields[k['LIKWID performance counter']]:
try:
entry[f[0]] = map(f[1], [k[f[0]]] )[0]
except:
print("ERROR: results entry missing essential data at file:%s"%(k['file_name']))
print f[0]
print k
return
#find repeated data
key = (entry['Precision'], k['stencil_name'], k['LIKWID performance counter'], k['mwdt'], k['method'], entry['Global NX'])
if key not in duplicates:
duplicates.add(key)
else:
print("Repeated result at: %s"%(k['file_name']))
continue
# Initialize plot entry if does not exist for current data entry
# for m,n in entry.iteritems(): print m,n
measure_list = ['n', 'perf', 'total energy', 'tlb', 'mem bw', 'l2 bw', 'l3 bw', 'mem vol', 'l2 vol', 'l3 vol', 'data', 'tgs', 'thx', 'thy', 'thz', 'blk size', 'diam width', 'bs_z']
plot_key = (entry['Precision'], k['stencil_name'], k['LIKWID performance counter'])
line_key = (k['mwdt'], k['method'])
if plot_key not in meas_figs.keys():
meas_figs[plot_key] = {}
if line_key not in meas_figs[plot_key].keys():
meas_figs[plot_key][line_key] = {meas:[] for meas in measure_list}
# append the measurement data
meas_figs[plot_key][line_key]['n'].append(entry['Global NX'])
# meas_figs[plot_key][line_key]['perf'].append(entry['MStencil/s MAX']/1e3)
N = entry['Global NX']**3 * entry['Number of time steps'] * entry['Number of tests']/1e9
# Memory
if k['LIKWID performance counter'] == 'MEM':
meas_figs[plot_key][line_key]['mem bw'].append(entry['Sustained Memory BW']/1e3)
meas_figs[plot_key][line_key]['mem vol'].append(entry['Total Memory Transfer']/N)
# Energy
elif k['LIKWID performance counter'] == 'ENERGY':
entry['cpu energy pj/lup'] = entry['Energy']/N
entry['dram energy pj/lup'] = entry['Energy DRAM']/N
entry['total energy pj/lup'] = entry['cpu energy pj/lup'] + entry['dram energy pj/lup']
if (entry['total energy pj/lup'] < 3e3):
# entry['total energy pj/lup'] = 0
meas_figs[plot_key][line_key]['total energy'].append(entry['total energy pj/lup'])
else:
del meas_figs[plot_key][line_key]['n'][-1]
# TLB
elif k['LIKWID performance counter'] == 'TLB':
meas_figs[plot_key][line_key]['tlb'].append(entry[ hw_ctr_fields['TLB'][0][0] ])
# L2
elif k['LIKWID performance counter'] == 'L2':
meas_figs[plot_key][line_key]['l2 vol'].append(entry['L2 data volume sum']/N)
#L3
elif k['LIKWID performance counter'] == 'L3':
meas_figs[plot_key][line_key]['l3 vol'].append(entry['L3 data volume sum']/N)
#CPU
elif k['LIKWID performance counter'] == 'DATA':
meas_figs[plot_key][line_key]['data'].append(entry['Load to Store ratio avg'])
#Diamond tiling data
if(k['method'] == '1WD' or k['method'] == 'MWD'):
meas_figs[plot_key][line_key]['diam width'].append(int(k['Intra-diamond width']))
meas_figs[plot_key][line_key]['tgs'].append(int(k['Thread group size']))
meas_figs[plot_key][line_key]['thx'].append(int(k['Threads along x-axis']))
meas_figs[plot_key][line_key]['thy'].append(int(k['Threads along y-axis']))
meas_figs[plot_key][line_key]['thz'].append(int(k['Threads along z-axis']))
meas_figs[plot_key][line_key]['blk size'].append(int(k['Total cache block size (kiB)'])/1024.0)
meas_figs[plot_key][line_key]['bs_z'].append(int(k['Multi-wavefront updates']))
# append the performance data
plot_key = (entry['Precision'], k['stencil_name'])
line_key = (k['mwdt'], k['method'])
if plot_key not in perf_fig.keys(): # figure
perf_fig[plot_key] = dict()
perf_line = perf_fig[plot_key]
if line_key not in perf_line.keys(): # line
perf_line[line_key] = dict()
perf_point = perf_line[line_key]
nx = entry['Global NX']
if nx not in perf_point.keys(): # points
perf_point[nx] = [entry['MStencil/s MAX']/1e3]
else:
perf_point[nx].append(entry['MStencil/s MAX']/1e3)
del raw_data
#sort performance results
for k,v in perf_fig.iteritems():
for k2,v2 in perf_fig[k].iteritems():
perf_line = perf_fig[k][k2]
perf_fig[k][k2] = OrderedDict(sorted(perf_fig[k][k2].iteritems(), key=lambda x:x[0]))
# for k,v in perf_fig.iteritems():
# print(k, "##########")
# for k2,v2 in perf_fig[k].iteritems():
# print(k2,v2)
#sort the plot lines
for p in meas_figs:
for l in meas_figs[p]:
pl = meas_figs[p][l]
#remove unused fields
empty = []
for key, val in pl.iteritems():
if(val==[]):
empty.append(key)
for key in empty:
del pl[key]
lines = []
[lines.append(pl[val]) for val in measure_list if val in pl.keys()]
lines = sorted(zip(*lines))
idx=0
for val in measure_list:
if(val in pl.keys()):
if(pl[val]):
pl[val] = [x[idx] for x in lines]
idx = idx+1
# for m,n in meas_figs.iteritems():
# print "##############",m
# for i,j in n.iteritems():
# print i,j
plot_all(perf_fig, meas_figs, machine_name)