%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
import datetime

# length of run, in days
SimulatedDays = 2
# Cori-Haswell data
data = np.array([
[ 64 , 124.154 , 256 , 81.015 ],
[ 128 , 63.166 , 512 , 41.254 ],
[ 256 , 36.443 , 1024 , 24.515 ]
])
ice_cores=data[:,0]
ocn_cores=data[:,2]
total_cores = ice_cores + ocn_cores
ice_WCtime=data[:,1]
ocn_WCtime=data[:,3]
total_WCtime = ice_WCtime + ocn_WCtime
SYPD = SimulatedDays/365. /total_WCtime*86300
plt.plot(total_cores,SYPD,'s-')
# Cori-KNL data
data = np.array([
[ 64 , 541.794 , 256 , 224.114 ],
[ 128 , 281.564 , 512 , 121.136 ],
[ 256 , 157.960 , 1024 , 72.075 ],
[ 512 , 87.038 , 2048 , 42.514 ],
])
ice_cores=data[:,0]
ocn_cores=data[:,2]
total_cores = ice_cores + ocn_cores
ice_WCtime=data[:,1]
ocn_WCtime=data[:,3]
total_WCtime = ice_WCtime + ocn_WCtime
SYPD = SimulatedDays/365. /total_WCtime*86300
plt.plot(total_cores,SYPD,'s-')
plt.legend(['Cori-Haswell','Cori-KNL'],loc='upper right')
plt.xlabel('cores')
plt.ylabel('SYPD, no i/o')
date=datetime.datetime.now().strftime("%Y-%m-%d")
plt.title('ACME performance, EC60to30wLI, G case, '+date)
plt.grid(True)
plt.savefig("ACME_performance.png")
plt.show()