##################
# Performance Model Version
44

####################
# COMBs
# number of combinations
4

####################
# COMB_3
# number of types devices
1
####################
# DEV_0
# device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3, SCC - 4)
0
####################
# DEV_0
# device id 
0
####################
# DEV_0
# number of cores 
1
##########
# number of implementations
1
#####
# Model for cpu0_impl0 (Comb3)
# number of entries
3
# sumlnx	sumlnx2		sumlny		sumlnxlny	alpha		beta		n	minx		maxx
0.000000e+00   	0.000000e+00   	0.000000e+00   	0.000000e+00   	nan            	nan            	0	0              	0              
# a		b		c
nan            	nan            	nan            
# hash		size		flops		mean (us)	dev (us)	sum		sum2		n
ff82dda0	14745600       	0.000000e+00   	8.795690e+04   	4.598673e+03   	1.715160e+07   	1.512725e+12   	195
d39bff17	6553600        	0.000000e+00   	2.744119e+04   	1.740624e+03   	4.390591e+06   	1.209678e+11   	160
2c1922b7	1638400        	0.000000e+00   	4.091631e+03   	5.062810e+02   	7.283104e+05   	3.025603e+09   	178

####################
# COMB_1
# number of types devices
1
####################
# DEV_0
# device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3, SCC - 4)
1
####################
# DEV_0
# device id 
0
####################
# DEV_0
# number of cores 
1
##########
# number of implementations
1
#####
# Model for cuda0_impl0 (Comb1)
# number of entries
3
# sumlnx	sumlnx2		sumlny		sumlnxlny	alpha		beta		n	minx		maxx
0.000000e+00   	0.000000e+00   	0.000000e+00   	0.000000e+00   	nan            	nan            	0	0              	0              
# a		b		c
nan            	nan            	nan            
# hash		size		flops		mean (us)	dev (us)	sum		sum2		n
ff82dda0	14745600       	0.000000e+00   	6.847320e+03   	1.168001e+03   	8.285257e+05   	5.838253e+09   	121
d39bff17	6553600        	0.000000e+00   	2.123746e+03   	3.153004e+02   	4.226254e+05   	9.173322e+08   	199
2c1922b7	1638400        	0.000000e+00   	5.446913e+02   	9.530021e+01   	1.040360e+05   	5.840221e+07   	191

####################
# COMB_0
# number of types devices
1
####################
# DEV_0
# device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3, SCC - 4)
1
####################
# DEV_0
# device id 
1
####################
# DEV_0
# number of cores 
1
##########
# number of implementations
1
#####
# Model for cuda1_impl0 (Comb0)
# number of entries
3
# sumlnx	sumlnx2		sumlny		sumlnxlny	alpha		beta		n	minx		maxx
0.000000e+00   	0.000000e+00   	0.000000e+00   	0.000000e+00   	nan            	nan            	0	0              	0              
# a		b		c
nan            	nan            	nan            
# hash		size		flops		mean (us)	dev (us)	sum		sum2		n
ff82dda0	14745600       	0.000000e+00   	6.816836e+03   	1.179433e+03   	1.172496e+06   	8.231973e+09   	172
d39bff17	6553600        	0.000000e+00   	2.055421e+03   	3.154533e+02   	3.864192e+05   	8.129623e+08   	188
2c1922b7	1638400        	0.000000e+00   	6.121868e+02   	1.314710e+02   	9.550115e+04   	6.116094e+07   	156

####################
# COMB_2
# number of types devices
1
####################
# DEV_0
# device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3, SCC - 4)
1
####################
# DEV_0
# device id 
2
####################
# DEV_0
# number of cores 
1
##########
# number of implementations
1
#####
# Model for cuda2_impl0 (Comb2)
# number of entries
3
# sumlnx	sumlnx2		sumlny		sumlnxlny	alpha		beta		n	minx		maxx
0.000000e+00   	0.000000e+00   	0.000000e+00   	0.000000e+00   	nan            	nan            	0	0              	0              
# a		b		c
nan            	nan            	nan            
# hash		size		flops		mean (us)	dev (us)	sum		sum2		n
ff82dda0	14745600       	0.000000e+00   	6.940618e+03   	1.147691e+03   	1.006390e+06   	7.175959e+09   	145
d39bff17	6553600        	0.000000e+00   	2.093041e+03   	3.377347e+02   	3.851195e+05   	8.270585e+08   	184
2c1922b7	1638400        	0.000000e+00   	6.098259e+02   	1.286153e+02   	1.091588e+05   	6.952888e+07   	179