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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
- d39bff17 3276800 0.000000e+00 1.416946e+04 8.998511e+02 5.341885e+06 7.599687e+10 377
- ff82dda0 7372800 0.000000e+00 4.394377e+04 1.700468e+03 1.138144e+07 5.008920e+11 259
- 2c1922b7 819200 0.000000e+00 1.978198e+03 1.079993e+02 7.517154e+05 1.491475e+09 380
- ####################
- # COMB_2
- # 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 (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
- d39bff17 3276800 0.000000e+00 2.676312e+03 2.039650e+02 4.549731e+05 1.224722e+09 170
- ff82dda0 7372800 0.000000e+00 6.450199e+03 3.193507e+02 5.482669e+05 3.545099e+09 85
- 2c1922b7 819200 0.000000e+00 7.090855e+02 1.344985e+02 5.247233e+04 3.854602e+07 74
- ####################
- # COMB_1
- # 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 (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
- d39bff17 3276800 0.000000e+00 2.648361e+03 2.330106e+02 2.913197e+05 7.774920e+08 110
- ff82dda0 7372800 0.000000e+00 3.907893e+03 1.767346e+02 3.790657e+05 1.484378e+09 97
- 2c1922b7 819200 0.000000e+00 5.977702e+02 1.137267e+02 6.695026e+04 4.146945e+07 112
- ####################
- # COMB_0
- # 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 (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
- d39bff17 3276800 0.000000e+00 2.649815e+03 2.112061e+02 4.054218e+05 1.081118e+09 153
- ff82dda0 7372800 0.000000e+00 6.517136e+03 3.918474e+02 3.454082e+05 2.259210e+09 53
- 2c1922b7 819200 0.000000e+00 6.507707e+02 8.750699e+01 4.750626e+04 3.147468e+07 73
|
