##################
# 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
afdd228b	3276800        	0.000000e+00   	7.065042e+04   	7.118479e+03   	1.271707e+06   	9.075877e+10   	18
617e5fe6	7372800        	0.000000e+00   	2.321971e+05   	3.386520e+04   	2.554168e+06   	6.056858e+11   	11
cea37d6d	819200         	0.000000e+00   	8.644872e+03   	1.175676e+03   	4.581782e+05   	4.034149e+09   	53

####################
# 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 
0
####################
# DEV_0
# number of cores 
1
##########
# number of implementations
1
#####
# Model for cuda0_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
afdd228b	3276800        	0.000000e+00   	3.469534e+04   	1.243993e+03   	9.714695e+05   	3.374879e+10   	28
617e5fe6	7372800        	0.000000e+00   	8.533007e+04   	9.757927e+03   	1.194621e+06   	1.032701e+11   	14
cea37d6d	819200         	0.000000e+00   	1.145973e+04   	6.017234e+02   	1.145973e+05   	1.316874e+09   	10

####################
# 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
afdd228b	3276800        	0.000000e+00   	3.498011e+04   	2.179531e+03   	6.996022e+05   	2.456717e+10   	20
617e5fe6	7372800        	0.000000e+00   	8.442764e+04   	6.770170e+03   	1.350842e+06   	1.147818e+11   	16
cea37d6d	819200         	0.000000e+00   	1.080764e+04   	2.151492e+02   	1.188840e+05   	1.285365e+09   	11

####################
# 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 
2
####################
# DEV_0
# number of cores 
1
##########
# number of implementations
1
#####
# Model for cuda2_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
afdd228b	3276800        	0.000000e+00   	3.506064e+04   	2.956747e+03   	6.310915e+05   	2.228383e+10   	18
617e5fe6	7372800        	0.000000e+00   	8.151052e+04   	4.250155e+02   	1.059637e+06   	8.637388e+10   	13
cea37d6d	819200         	0.000000e+00   	1.153062e+04   	1.200141e+03   	1.153062e+05   	1.343956e+09   	10