def mem_error(real_time_logfile, sim_time_logfile, real_mem_logfile, sim_mem_logfile):
real_time_log = log_parse.read_timelog(real_time_logfile, skip_header=False)
real_mem_log = log_parse.read_atop_log(real_mem_logfile)
dirty_origin = real_mem_log["dirty_data"][0]
cache_origin = real_mem_log["cache"][0]
real_dirty_amt = [amt for amt in get_atop_mem_prop(real_time_log, real_mem_log, "dirty_data")]
real_cache_amt = [amt for amt in get_atop_mem_prop(real_time_log, real_mem_log, "cache")]
# print(dirty_origin)
print("real:")
print(get_atop_mem_prop(real_time_log, real_mem_log, "dirty_data"))
# print(real_mem_log["dirty_data"])
sim_time_log = log_parse.read_timelog(sim_time_logfile)
sim_mem_log = log_parse.read_sim_log(sim_mem_logfile)
sim_dirty_amt = get_sim_mem_prop(sim_time_log, sim_mem_log, "dirty_data")
sim_cache_amt = get_sim_mem_prop(sim_time_log, sim_mem_log, "cache")
print("sim:")
print(sim_dirty_amt)
dirty_err = [abs(sim - real) / real for real, sim in zip(real_dirty_amt, sim_dirty_amt)]
cache_err = [abs(sim - real) / real for real, sim in zip(real_cache_amt, sim_cache_amt)]
return dirty_err, cache_err
def plot(atop_log_file, timestamps_file, collectl_log_file, input_size):
atop_log = log_parse.read_atop_log(atop_log_file,
dirty_ratio=0.4,
dirty_bg_ratio=0.1)
timestamps = log_parse.read_timelog(timestamps_file, skip_header=False)
# timestamps = None
figure = plt.figure()
plt.tight_layout()
ax1 = figure.add_subplot(2, 1, 1)
ax2 = figure.add_subplot(2, 1, 2, sharex=ax1)
ax1.set_ylim(top=280000, bottom=-10000)
ax1.set_xlim(left=0, right=700)
mem_plot(ax1, atop_log, timestamps, input_size)
collectl_plot(ax2, collectl_log_file, timestamps)
plt.show()
def real_subplot(subplot_ax,
real_time_file,
real_mem_file,
xmin,
xmax,
ymin,
ymax,
bar_alpha=0.2,
line_alpha=1,
linestyle=".-",
linewidth=2,
cond_text=None):
timestamps = log_parse.read_timelog(real_time_file, skip_header=False)
atop_log = log_parse.read_atop_log(real_mem_file,
dirty_ratio=0.4,
dirty_bg_ratio=0.1)
dirty_data = np.array(atop_log["total"])
intervals = len(dirty_data)
time = np.arange(0, intervals)
start = timestamps[0][1]
for i in range(len(timestamps)):
if timestamps[i][0] == "read":
subplot_ax.axvspan(xmin=timestamps[i][1] - start,
xmax=timestamps[i][2] - start,
color="k",
alpha=0.1,
label="Read" if i == 0 else "")
else:
subplot_ax.axvspan(xmin=timestamps[i - 1][2] - start,
xmax=timestamps[i][1] - start,
color="k",
alpha=0.25,
label="Computation" if i == 1 else "")
subplot_ax.axvspan(xmin=timestamps[i][1] - start,
xmax=timestamps[i][2] - start,
color="k",
alpha=0.4,
label="write" if i == 1 else "")
# app_cache = list(np.array(app_mem) + np.array(cache_used))
subplot_ax.plot(time,
atop_log["total"],
color='black',
linewidth=linewidth,
label="Total memory",
alpha=line_alpha)
subplot_ax.plot(time,
atop_log["dirty_ratio"],
color='black',
linewidth=linewidth,
linestyle=":",
label="dirty_ratio",
alpha=line_alpha)
subplot_ax.plot(time,
atop_log["used_mem"],
color='#72190E',
linewidth=linewidth,
linestyle=linestyle,
label="Used memory",
alpha=line_alpha)
subplot_ax.plot(time,
atop_log["cache"],
color='#DC050C',
linewidth=linewidth,
linestyle=linestyle,
label="Cache",
alpha=line_alpha)
subplot_ax.plot(time,
atop_log["dirty_data"],
color='#F4A736',
linewidth=linewidth,
linestyle=linestyle,
label="Dirty data",
alpha=line_alpha)