def collect_online_window_based(current_run_period, benchmark_dir, ncore,
freq_w): #during sniper runTime
W_P = UL.get_window_past()
window_based_feature_list = []
feature_list = []
for w in range(W_P):
feature_list.append([])
for w in range(W_P):
print("frequency[%s][0]= %s" % (w, freq_w[w][0]))
#current_feature_list=get_stats(current_run_period,benchmark_dir,ncore,'ONLINE',freq_w[W-P-1],freq[W-P-1])#actually one of the freq_w is necessary
for w in reversed(range(W_P)):
offset = W_P - 1 - w
if current_run_period - offset >= 1:
print("freq_w[%s] in collect_online_window_based: %s\n" %
(w, freq_w[w]))
feature_list[w] = get_stats(current_run_period - offset,
benchmark_dir, ncore, 'ONLINE',
freq_w[w], freq_w[w])
last_feature_list = feature_list[w]
else:
feature_list[w] = last_feature_list
for w in range(W_P):
window_based_feature_list += feature_list[w]
return window_based_feature_list
def collect_offline_window_based(input_dir,input_filename,output_dir,output_filename,collect_mode): #collects the stats from sqlite files generated earlier
W_P=UL.get_window_past() #Window for Past sequences
#TODO
W_F=1 #UL.get_window_future() #Window for Future sequences # currently 1 step forward prediction, because the DNN just has one output
Rfile_read_freq = file(os.path.join(input_dir, input_filename), 'r')
Wfile_features_labels = file(os.path.join(output_dir,output_filename), 'a')
feature_list = []
for w in range(0,W_P):
feature_list.append([])
line_count=-1
for line in Rfile_read_freq:
line_splitted = line.split('\t')
line_count+=1
if (line_count==0):
num_core = int(line_splitted[0])
if (line_count>W_P):
if (collect_mode=='CORE_BASED'):
for w in reversed(range(0,W_P)):
feature_list[W_P-1-w],labels = get_stats(line_count-w,input_dir,num_core,'OFFLINE',line_splitted)
if (w==0):#current features
old_labels=labels
try:#TODO for W_F > 1
feature_list_trash,labels = get_stats(line_count+(W_F),input_dir,num_core,'OFFLINE',line_splitted)
old_labels=labels
except:
labels=old_labels
for core in range(num_core):
for w in range(0,W_P):
for f in feature_list[w]:
Wfile_features_labels.write('%s,'%f[core])
Wfile_features_labels.write('%s\n'%labels[core])
#for w in (range(0,W_F-1)):
# try:
# feature_list_trash,labels = get_stats(line_count+(w+1),input_dir,num_core,'OFFLINE',line_splitted)
# Wfile_features_labels.write('%s,'%labels[core])
# old_labels=labels
# except:
# Wfile_features_labels.write('%s,'%old_labels[core])
#this version just works for W_F=1
#try:
# feature_list_trash,labels = get_stats(line_count+(W_F),input_dir,num_core,'OFFLINE',line_splitted)
# Wfile_features_labels.write('%s\n'%labels[core])
#except:
# Wfile_features_labels.write('%s\n'%old_labels[core])
Rfile_read_freq.close()
Wfile_features_labels.close()
def collect_online_window_based(current_run_period,benchmark_dir,ncore,freq): #during sniper runTime
W_P=UL.get_window_past()
window_based_feature_list = []
feature_list=[]
for w in range (W_P):
feature_list.append([])
current_feature_list=get_stats(current_run_period,benchmark_dir,ncore,'ONLINE',freq)
for w in reversed(range (W_P)):
offset=W_P-1-w
if current_run_period-offset>=1:
feature_list[w]=get_stats(current_run_period-offset,benchmark_dir,ncore,'ONLINE',freq)
last_feature_list = feature_list[w]
else:
feature_list[w]= last_feature_list
for w in range (W_P):
window_based_feature_list+=feature_list[w]
return window_based_feature_list
def setup(self, args):
args = dict(enumerate((args or '').split(':')))
interval = long(args.get(0, '') or 1000000000)
self.DVFS = 1
self.CMP_based_DNN_flag = 0
self.W_P = UL.get_window_past()
self.freq_w = [] #a window of last frequency values
for i in range(self.W_P):
self.freq_w.append([])
for i in range(self.W_P):
for core in range(sim.config.ncores):
self.freq_w[i].append(2000.0) #defult frequency
self.max_snapshots = long(args.get(1, 0))
self.num_snapshots = 0
self.interval = long(interval * sim.util.Time.NS)
self.next_interval = float('inf')
self.in_roi = False
#sim.util.Every(self.interval, self.periodic, roi_only = True)
self.sd = sim.util.StatsDelta()
self.stats = {
'time': [
self.sd.getter('performance_model', core, 'elapsed_time')
for core in range(sim.config.ncores)
],
'ffwd_time': [
self.sd.getter('fastforward_performance_model', core,
'fastforwarded_time')
for core in range(sim.config.ncores)
],
'instrs': [
self.sd.getter('performance_model', core, 'instruction_count')
for core in range(sim.config.ncores)
],
'coreinstrs': [
self.sd.getter('core', core, 'instructions')
for core in range(sim.config.ncores)
],
}
sim.util.Every(self.interval,
self.periodic,
statsdelta=self.sd,
roi_only=True) #interval_ns * sim.util.Time.NS
######## Get start freq to calculate corrected Cycle ##############
self.start_freq = []
for core in range(sim.config.ncores):
self.start_freq.append(sim.dvfs.get_frequency(core))
## makedir for stats coming out off energystats
if not os.path.exists("%sstats" % sim.config.output_dir):
os.makedirs("%sstats" % sim.config.output_dir, 0777)
## mkdir for outfiles (files should be transfered between sniper and kalman)
if not os.path.exists("%s/outfiles" % sniper_path):
os.makedirs("%s/outfiles" % sniper_path, 0777)
filename = "statsPeriodic.txt"
self.fd = file(os.path.join(sim.config.output_dir, filename), 'w')
#############################
self.filename_DNN_feature_label = 'DNN_feature_label.csv'
self.filename_DNN_frequencies = 'DNN_frequencies.xls'
self.Wfile_DNN_frequencies = file(
os.path.join(sim.config.output_dir, self.filename_DNN_frequencies),
'a')
self.Wfile_DNN_frequencies.write("Interval\t")
for core in range(sim.config.ncores):
self.Wfile_DNN_frequencies.write("%s\t" % core)
self.Wfile_DNN_frequencies.write("\n")
#############################
self.IdleTimePerc = [] #number of cores = 1000 (I used alot)
for core in range(sim.config.ncores):
self.IdleTimePerc.append(0.0)
import sniper_lib
import gen_simout
import DNN_feature_collector as DFC
#############################################
#############################################
#######################################################################################################
# look at /sniper/scripts/user_level.py
FreqList = [
'1000', '1100', '1200', '1300', '1400', '1500', '1600', '1700', '1800',
'1900', '2000'
]
W_P = UL.get_window_past()
freq_w = [] #a window of last frequency values
for i in range(W_P):
freq_w.append([])
for i in range(W_P):
for core in range(sim.config.ncores):
freq_w[i].append(2000.0) #defult frequency
######################################################
class PeriodicStats:
def setup(self, args):
args = dict(enumerate((args or '').split(':')))
interval = long(args.get(0, '') or 1000000000)
self.DVFS = 1