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- ##################
- # Performance Model Version
- 45
- ####################
- # COMBs
- # number of combinations
- 4
- ####################
- # COMB_3
- # number of types devices
- 1
- ####################
- # DEV_0
- # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3)
- 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
- # not multiple-regression-base
- 0
- # hash size flops mean (us) dev (us) sum sum2 n
- 617e5fe6 7372800 0.000000e+00 2.515766e+05 2.096151e+04 2.515766e+06 6.373017e+11 10
- afdd228b 3276800 0.000000e+00 7.350482e+04 4.292777e+03 9.555626e+05 7.047802e+10 13
- cea37d6d 819200 0.000000e+00 9.586125e+03 1.023620e+03 2.108948e+05 2.044715e+09 22
- ####################
- # COMB_1
- # number of types devices
- 1
- ####################
- # DEV_0
- # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3)
- 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
- # not multiple-regression-base
- 0
- # hash size flops mean (us) dev (us) sum sum2 n
- 617e5fe6 7372800 0.000000e+00 6.990473e+04 4.071360e+03 1.118476e+06 7.845196e+10 16
- afdd228b 3276800 0.000000e+00 2.992444e+04 7.760944e+02 4.787910e+05 1.433719e+10 16
- cea37d6d 819200 0.000000e+00 9.620220e+03 2.335102e+02 1.058224e+05 1.018635e+09 11
- ####################
- # COMB_0
- # number of types devices
- 1
- ####################
- # DEV_0
- # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3)
- 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
- # not multiple-regression-base
- 0
- # hash size flops mean (us) dev (us) sum sum2 n
- 617e5fe6 7372800 0.000000e+00 6.793522e+04 8.600858e+02 6.793522e+05 4.615934e+10 10
- afdd228b 3276800 0.000000e+00 2.989699e+04 1.490344e+03 3.587638e+05 1.075261e+10 12
- cea37d6d 819200 0.000000e+00 9.974140e+03 1.055336e+03 1.097155e+05 1.106569e+09 11
- ####################
- # COMB_2
- # number of types devices
- 1
- ####################
- # DEV_0
- # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3)
- 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
- # not multiple-regression-base
- 0
- # hash size flops mean (us) dev (us) sum sum2 n
- 617e5fe6 7372800 0.000000e+00 6.962168e+04 1.952172e+02 1.322812e+06 9.209711e+10 19
- afdd228b 3276800 0.000000e+00 3.047853e+04 4.777511e+01 4.571780e+05 1.393415e+10 15
- cea37d6d 819200 0.000000e+00 1.119488e+04 2.171263e+03 1.231437e+05 1.430437e+09 11
|
